This document describes an agent-based model that examines the impact of different approaches for providing energy consumption feedback and data apportionment on changing staff behavior to reduce energy use in an office building. The model divides staff into four stereotypes based on motivation levels and analyzes how factors like feedback, data apportionment at individual or group levels, sanctions, and anonymity impact motivation levels and overall energy consumption. Simulation results indicate greater potential for energy savings when data is apportioned at the group level compared to the individual level. Staff with low and medium motivation levels showed the most significant reductions in energy use.
This document discusses and compares different measures of interestingness that can be used to evaluate association rules generated by data mining algorithms. It first reviews twelve common interestingness measures, including support, confidence, lift, conviction, and p-measure. It then applies these measures to association rules generated from a sample dataset about demographics and hobbies in the western region. The results are summarized in a table comparing the interestingness values calculated by each measure for different rules. The document aims to help users understand and select the most appropriate interestingness measure depending on their application needs.
Environmental constrained electric power generation and dispatch via genetic ...TuhinDas33
Abstract: This article presents how multi-objective bi-level programming (MOBLP)
in a hierarchical structure can be efficiently used for modeling and solving
environmental-economic power generation and dispatch (EEPGDD) problems
through Fuzzy Goal Programming (FGP) based on genetic algorithm (GA) in a
thermal power system operation and planning horizon.
This document outlines the background, aim, objectives, and initial literature review for an honors dissertation project on embedding environmental sustainability within corporate strategy. The project will investigate how environmental sustainability can be embedded into corporate strategy through a case study of a small UK energy company. The literature review provides context on the history of sustainability concepts dating back to the Brundtland Commission in 1987. It also discusses various economic perspectives on sustainability and the need for businesses to generate positive environmental impacts beyond just regulatory compliance. The case study aims to provide practical recommendations for how energy companies can embed sustainability into their strategies.
Initial Optimal Parameters of Artificial Neural Network and Support Vector Re...IJECEIAES
This paper presents architecture of backpropagation Artificial Neural Network (ANN) and Support Vector Regression (SVR) models in supervised learning process for cement demand dataset. This study aims to identify the effectiveness of each parameter of mean square error (MSE) indicators for time series dataset. The study varies different random sample in each demand parameter in the network of ANN and support vector function as well. The variations of percent datasets from activation function, learning rate of sigmoid and purelin, hidden layer, neurons, and training function should be applied for ANN. Furthermore, SVR is varied in kernel function, lost function and insensitivity to obtain the best result from its simulation. The best results of this study for ANN activation function is Sigmoid. The amount of data input is 100% or 96 of data, 150 learning rates, one hidden layer, trinlm training function, 15 neurons and 3 total layers. The best results for SVR are six variables that run in optimal condition, kernel function is linear, loss function is ౬ -insensitive, and insensitivity was 1. The better results for both methods are six variables. The contribution of this study is to obtain the optimal parameters for specific variables of ANN and SVR.
Scale transformation of analytical hierarchy process to likert weighted measu...Siddharth Misra
This document summarizes a research article that analyzes the transformation of scales between the Analytical Hierarchy Process (AHP) and the Likert Weighted Measurement Method (LWMM) in the context of environmental consciousness and brand equity. Specifically, it proposes converting AHP's 9-point scale to LWMM's generalized Likert scale for ranking purposes. The researchers aim to simplify computations while incorporating psychometric methods through this scale transformation.
FACTORS INFLUENCING THE ADOPTION OF E-GOVERNMENT SERVICES IN PAKISTANMuhammad Ahmad
E-government provides opportunities to deliver various services more effectively and better serve citizens. In developing countries, e-government initiatives provide services that have been previously inaccessible to their citizens. However, e-government initiatives in developing countries are still in their infancy and face a wide range of barriers that restrict wide-spread use. Like many other developing countries, Pakistan has a low level of e-government services adoption. Previous research has investigated e-government services in developing countries from the organizational perspective. However, the research stream suffers from an absence of studies that have investigated e-government from a citizen’s perspective. The success of e-government services depends on government support as well as on citizen’s adoption. This paper aims to fill this gap by exploring the challenges and barriers of e-government services from the user’s perspective. In this study, an amended version of the UTAUT model is used to investigate the factors influencing the uptake of e-government services in Pakistan. The results show that the factors influencing the adoption of e-government services in Pakistan are related to ease of use, usefulness, social influence, technological issues, lack of awareness, data privacy, and trust. Implications for e-businesses and government policy decision makers are also considered in this study.
Analysis of the User Acceptance for Implementing ISO/IEC 27001:2005 in Turkis...IJMIT JOURNAL
This study aims to develop a model for the user acceptance for implementing the information security standard (i.e. ISO 27001) in Turkish public organizations. The results of the surveys performed in Turkey reveal that the legislation on information security public which organizations have to obey is significantly related with the user acceptance during ISO 27001 implementation process. The fundamental components of our user acceptance model are perceived usefulness, attitude towards use, social norms, and performance expectancy.
This document discusses and compares different measures of interestingness that can be used to evaluate association rules generated by data mining algorithms. It first reviews twelve common interestingness measures, including support, confidence, lift, conviction, and p-measure. It then applies these measures to association rules generated from a sample dataset about demographics and hobbies in the western region. The results are summarized in a table comparing the interestingness values calculated by each measure for different rules. The document aims to help users understand and select the most appropriate interestingness measure depending on their application needs.
Environmental constrained electric power generation and dispatch via genetic ...TuhinDas33
Abstract: This article presents how multi-objective bi-level programming (MOBLP)
in a hierarchical structure can be efficiently used for modeling and solving
environmental-economic power generation and dispatch (EEPGDD) problems
through Fuzzy Goal Programming (FGP) based on genetic algorithm (GA) in a
thermal power system operation and planning horizon.
This document outlines the background, aim, objectives, and initial literature review for an honors dissertation project on embedding environmental sustainability within corporate strategy. The project will investigate how environmental sustainability can be embedded into corporate strategy through a case study of a small UK energy company. The literature review provides context on the history of sustainability concepts dating back to the Brundtland Commission in 1987. It also discusses various economic perspectives on sustainability and the need for businesses to generate positive environmental impacts beyond just regulatory compliance. The case study aims to provide practical recommendations for how energy companies can embed sustainability into their strategies.
Initial Optimal Parameters of Artificial Neural Network and Support Vector Re...IJECEIAES
This paper presents architecture of backpropagation Artificial Neural Network (ANN) and Support Vector Regression (SVR) models in supervised learning process for cement demand dataset. This study aims to identify the effectiveness of each parameter of mean square error (MSE) indicators for time series dataset. The study varies different random sample in each demand parameter in the network of ANN and support vector function as well. The variations of percent datasets from activation function, learning rate of sigmoid and purelin, hidden layer, neurons, and training function should be applied for ANN. Furthermore, SVR is varied in kernel function, lost function and insensitivity to obtain the best result from its simulation. The best results of this study for ANN activation function is Sigmoid. The amount of data input is 100% or 96 of data, 150 learning rates, one hidden layer, trinlm training function, 15 neurons and 3 total layers. The best results for SVR are six variables that run in optimal condition, kernel function is linear, loss function is ౬ -insensitive, and insensitivity was 1. The better results for both methods are six variables. The contribution of this study is to obtain the optimal parameters for specific variables of ANN and SVR.
Scale transformation of analytical hierarchy process to likert weighted measu...Siddharth Misra
This document summarizes a research article that analyzes the transformation of scales between the Analytical Hierarchy Process (AHP) and the Likert Weighted Measurement Method (LWMM) in the context of environmental consciousness and brand equity. Specifically, it proposes converting AHP's 9-point scale to LWMM's generalized Likert scale for ranking purposes. The researchers aim to simplify computations while incorporating psychometric methods through this scale transformation.
FACTORS INFLUENCING THE ADOPTION OF E-GOVERNMENT SERVICES IN PAKISTANMuhammad Ahmad
E-government provides opportunities to deliver various services more effectively and better serve citizens. In developing countries, e-government initiatives provide services that have been previously inaccessible to their citizens. However, e-government initiatives in developing countries are still in their infancy and face a wide range of barriers that restrict wide-spread use. Like many other developing countries, Pakistan has a low level of e-government services adoption. Previous research has investigated e-government services in developing countries from the organizational perspective. However, the research stream suffers from an absence of studies that have investigated e-government from a citizen’s perspective. The success of e-government services depends on government support as well as on citizen’s adoption. This paper aims to fill this gap by exploring the challenges and barriers of e-government services from the user’s perspective. In this study, an amended version of the UTAUT model is used to investigate the factors influencing the uptake of e-government services in Pakistan. The results show that the factors influencing the adoption of e-government services in Pakistan are related to ease of use, usefulness, social influence, technological issues, lack of awareness, data privacy, and trust. Implications for e-businesses and government policy decision makers are also considered in this study.
Analysis of the User Acceptance for Implementing ISO/IEC 27001:2005 in Turkis...IJMIT JOURNAL
This study aims to develop a model for the user acceptance for implementing the information security standard (i.e. ISO 27001) in Turkish public organizations. The results of the surveys performed in Turkey reveal that the legislation on information security public which organizations have to obey is significantly related with the user acceptance during ISO 27001 implementation process. The fundamental components of our user acceptance model are perceived usefulness, attitude towards use, social norms, and performance expectancy.
Nov 2018 Table of contents; current issue -International Journal on Soft Comp...IJSCAI Journal
The document discusses using machine learning algorithms to analyze the relationship between economic freedom and quality of life. It examines the Economic Freedom of the World index and the Human Development Index with modern machine learning methods. The analysis finds that these advanced algorithms achieve a stronger correlation between the indices than statistical means alone. However, there is still some room for non-liberal interpretations of how to design economic policies to improve people's lives. The goal is to objectively evaluate the impact of economic freedom through a data-driven approach.
Stochastic actor-oriented models (SAOMs) summarize the key components and estimation process of these models. SAOMs model how networks and behaviors change over time as a result of endogenous network effects and influence between connected individuals. The models estimate parameters representing these effects to predict tie formation and changes in behaviors. SAOMs account for selection into the network based on attributes as well as social influence processes within the network. Estimation involves maximum likelihood to estimate parameters of network and behavior functions that represent how individuals make network and behavioral decisions.
Strengthening Supply Chains for a Sustainable Housing Sector in Nepal : Facto...ijmvsc
EU’s main approach to sustainable housing is promoting green practices/products within the building
construction sectors SCs. EU Switch Asia program financed research conducted in Nepal, 2015, to
understand the organization of SCs, identify factors/barriers affecting SCM and existing relationships, the
reasons to adopt green concepts/approaches and recommend support for SMEs to strengthen the sector’s
management and sustainability. 109 companies, non-probabilistic snowball sampling and semi-closed
questionnaires used in the survey. Conclusions: Companies create SCs to increase customer satisfaction,
maintain long-term sales and retain clients. Size of company influences SCs organisation, SCM and
using/producing green products/services; majority of participants had a person in the company to manage
SC’s and had very good knowledge of SC, SCM and greening issues. SMEs need support with:
information/communication technology, promotion and improvement/development of green
products/services. Government should: increases awareness of green building products/services; develop
financial green incentives and simplify administrative procedures to buy solar products.
This document provides an overview of stochastic actor-oriented models (SAOMs), including:
1. The general components of SAOMs including network and behavior objective functions that determine how and when actors change their ties and behaviors.
2. The estimation procedure which uses simulations to refine parameter estimates and minimize the deviation between simulated and observed network statistics.
3. Examples of how to interpret the output including checking for convergence of the model to the observed data.
E-GOVERNANCE ADOPTION IN GOVERNMENT ORGANIZATION OF INDIAijmpict
India, the growing economic super-power proceeded with lightning speed towards the adoption and successful implementation of e-governance. The Government of West Bengal (federal unit of India) implemented e-governance in pension office i.e. Pension Management System (PMS), for faster and efficient delivery of public services. The success of PMS is dependent on many factors and one among them is the successful adoption by the employee which has been empirically analyzed. The study used the
Technology Acceptance Model (TAM) and Trust to build a conceptual model. Data collected from 60 employees working on the system and the model is assessed with regression analyses. The findings show that the determinants of the research model are support. The study also shows that the system doesn’t perform completely error free tasks which the Government of West Bengal should address. This is the first study of employee adoption of e-governance in pension office of India.
A primary research analysis is conducted with Simply Energy. The purpose of the research is to identify and assess how the company provides its consumers with needed services and also to find out satisfaction levels of the customers. Recommendations are made for increasing sustainability initiatives in order for the company to face current competitive situations.
Your Quick Guide to Energy Management for Sustainability and Reduced Business...QuekelsBaro
Learn how to increase energy efficiency, conserve energy, and harness renewable energy for your business, with free access to our energy management plan.
In the present world we are facing lot of electricity problem, lack of natural substances, depletion of fossil fuels etc., hence we should think of acquiring maximum with the limited energy resources. Green computing is the term used to denote efficient use of resources in computing .This paper mainly deals with a regenerative approach towards green computing, to enhance the power backup of battery in the laptops. This paper also throws light on regenerative technique (the heat generated by the processor is utilized) and made to harness energy.
IRJET- An Energy Conservation Scheme based on Tariff ModerationIRJET Journal
This document discusses an energy conservation scheme based on tariff modification for domestic users. It proposes a new tariff rate structure that provides incentives for low consumption and penalties for high consumption. This aims to motivate consumers to reduce energy usage without causing losses for electric utilities. The existing structure provides 100 free units, which does not encourage conservation and causes losses. The proposed system calculates bills based on consumed units and compares to averages to determine incentives or penalties. The goal is to reduce residential energy usage through this modified tariff approach.
Optimization of the Building Energy Performance through Dynamic Modeling, Sys...IJERA Editor
The annual energy consumption in the residential and commercial sectors, in India is rising consistently at about 8% and the overall energy consumption in buildings has seen an increase from a low of 14% in the 1970s to nearly 33% in 2004/05. The electricity sector in India had an installed capacity of 254.049 GW as of end of September 2014. The research paper will deal with the modeling and optimization of the building energy performance by means of the application of the dynamic building simulation, the optimization of the energy systems and the verification of the energy consumptions and comfort conditions. An integrated tool is at an early stage of development to optimize the building energy performance to be expressed in terms of total energy use. The goal of the research paper is to optimize the building energy performance through the potential of the passive building technologies and the increase of efficiency of the building system.
Data Science for Building Energy Management a reviewMigue.docxrandyburney60861
Data Science for Building Energy Management: a review
Miguel Molina-Solanaa,b, Maŕıa Rosa,∗, M. Dolores Ruiza, Juan Gómez-Romeroa, M.J. Martin-Bautistaa
aDepartment of Computer Science and Artificial Intelligence, Universidad de Granada
bData Science Institute, Imperial College London
Abstract
The energy consumption of residential and commercial buildings has risen steadily in recent years, an
increase largely due to their HVAC systems. Expected energy loads, transportation, and storage as well
as user behavior influence the quantity and quality of the energy consumed daily in buildings. However,
technology is now available that can accurately monitor, collect, and store the huge amount of data involved
in this process. Furthermore, this technology is capable of analyzing and exploiting such data in meaningful
ways. Not surprisingly, the use of data science techniques to increase energy efficiency is currently attracting
a great deal of attention and interest. This paper reviews how Data Science has been applied to address the
most difficult problems faced by practitioners in the field of Energy Management, especially in the building
sector. The work also discusses the challenges and opportunities that will arise with the advent of fully
connected devices and new computational technologies.
1. Introduction
There is a general consensus in the world today that human activities are having a negative impact
on the environment and have accelerated both global warming and climate change. These environmental
threats have been intensified by the emissions produced by the energy required for the lighting and HVAC
(heating, ventilation and air-conditioning) systems in building constructions. According to the International
Energy Agency (IEA), residential and commercial buildings are responsible for up to 32% of the total final
energy consumption. In fact, in most IEA countries, they account for approximately 40% of the primary
energy consumption. Similar statistics are given by the World Business Council for Sustainable Development
(WBCSD) within the framework of its Energy Efficiency in Buildings (EEB) project1. Also provided is a
comprehensive review [1] of the state of the art in building energy use (with a primary focus on energy
demand).
These data indicate that inefficient energy management in aging buildings combined with rising construc-
tion activity in developed countries will cause energy consumption to soar in the near future and heighten the
negative impacts associated with this consumption. Moreover, variable energy costs call for the implemen-
tation of more intelligent strategies to adapt and reduce energy consumption as well as to find alternative
and sustainable energy sources. The relevance of these issues is clearly reflected in the research priorities of
the European Union, as stated in its Horizon2020 Societal Challenge “Secure, Clean and Efficient Energy”.
This work program targets a significant reduction in energy consu.
Analysis of Electric Power Consumption using Smart Meter DataIRJET Journal
This document proposes an analytical model to analyze electric power consumption using smart meter data. The model consists of two modules: 1) A consumer-oriented module that clusters consumers with similar appliances and analyzes consumption patterns to provide customized recommendations for reducing usage. 2) A predictive module that uses historical consumption data to identify trends and predict future usage or irregularities. The proposed system first collects smart meter data, preprocesses it, then clusters consumers using k-means clustering based on appliance type and number. Consumption profiles are analyzed within each cluster to develop standards and suggest recommendations. Historical data is also used for predictive modeling and outlier detection.
Prediction of Power Consumption and Leakage Detectionijtsrd
Energy consumption and predictions for residential buildings play an important role within the energy management and system, as the availability and demand of energy resources is the dynamic and seasonal changes. Human beings are unaware of the cost of energy consumed by various appliances and the energy resources available for the next generation. Each appliances in homes will consume different power consumption in different seasons. Accordingly the bill rate changes. Vyshnavi B | Selma P. T | Renin Joy | Sheethal M. S "Prediction of Power Consumption and Leakage Detection" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30589.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/30589/prediction-of-power-consumption-and-leakage-detection/vyshnavi-b
This document summarizes an electrical energy audit conducted at the Nandi Institute of Technology and Management Sciences (NIT&MS) campus in Bangalore, India. The audit found that the total average monthly electrical energy consumption across the campus was 3,842.842 kWh. Personal computers in labs, offices, and libraries accounted for the highest consumption at 39.14% of total usage. Fans were the second highest usage at 21.53%. Recommendations to improve energy efficiency included replacing conventional ballasts with electronic ones, installing motion sensors, replacing CRT monitors with LCDs, and switching to LED lights. Implementing all recommendations could save an estimated 10,435.84 kWh per year and reduce electricity costs by
A new smart approach of an efficient energy consumption management by using a...IJEECSIAES
Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is satisfied. It divides the measured data for actual power (Ap) of the electrical model into two portions: the training portion is selected for different maximum actual powers, and the validation portion is determined based on the minimum output power consumption and then used for comparison with the actual required input power. Simulation results show the energy expenditure problem can be solved with good accuracy in energy consumption by reducing the maximum rate (Ap) in a given time (24) hours for a single house, as well as electricity’s bill cost, is reduced.
A new smart approach of an efficient energy consumption management by using a...nooriasukmaningtyas
This document proposes a new smart approach for efficient energy consumption management using machine learning techniques. It divides measured actual power data into training and validation portions to determine efficient energy consumption. Simulation results showed the approach can accurately reduce energy consumption and costs by lowering the maximum allowed power consumption over a 24-hour period for a single house. The approach connects to cloud services and uses Internet of Things technologies for real-time energy monitoring.
ADOPTING MEASURES TO REDUCE POWER OUTAGESelelijjournal
This work investigates and evaluates the electric energy interruptions to the residential sector resulting
from severe power outages. The study results show that this sector will suffer tangible and intangible losses
should these outages occur during specific times, seasons, and for prolonged durations. To reduce these
power outages and hence mitigate their adverse consequences, the study proposes practical measures that
can be adopted without compromising the consumers’ needs, satisfaction ,and convenience.
This document discusses measures to reduce power outages for the residential sector. It first reviews existing studies on assessing the costs of power outages and energy conservation strategies. It then outlines the objectives of the work, which are to estimate the adverse effects of power outages on residents and propose energy conservation strategies that reduce outages and costs. To achieve this, the author conducted a consumer survey to estimate outage costs based on residents' perceptions and willingness to pay. A mathematical model was also developed relating energy consumption, costs, and outages. The model shows that energy conservation can maximize benefits by reducing consumption and outages. The document evaluates outage costs using both the survey approach and mathematical modeling.
This work investigates and evaluates the electric energy interruptions to the residential sector resulting from severe power outages. The study results show that this sector will suffer tangible and intangible losses should these outages occur during specific times, seasons, and for prolonged durations. To reduce these power outages and hence mitigate their adverse consequences, the study proposes practical measures that
can be adopted without compromising the consumers’ needs, satisfaction, and convenience.
Reinforcement Learning for Building Energy Optimization Through Controlling o...Power System Operation
This paper presents a novel methodology to control HVAC system and minimize energy cost
on the premise of satisfying power system constraints. A multi-agent architecture based on game theory and
reinforcement learning is developed so as to reduce the cost and computational complexity of the microgrid.
The multi-agent architecture comprising agents, state variables, action variables, reward function and cost
game is formulated. The paper lls the gap between multi-agent HVAC systems control and power system
optimization and planning. The results and analysis indicate that the proposed algorithm is benecial to deal
with the problem of ``curse of dimensionality'' for multi-agent microgrid HVAC system control and speed
up learning of unknown power system conditions.
Energy audit, conservation and power factor improvement for bmsit campuseSAT Journals
Abstract The main focus of this paper is to achieve and maintain optimum energy throughout the organization so as to minimize energy costs and improve power quality. Energy Audit is a systematic approach for decision-making in the area of energy management. A simple payback period calculation and formulation has been executed. Keywords: LCD, CRT, KW, KVA, KVAR.
Monitoring and analysis of reliaibility of electrical distribution systemIAEME Publication
This document summarizes a study on monitoring and analyzing the reliability of electrical distribution systems using MATLAB. The study develops a reliability analysis program in MATLAB to assess factors that affect distribution reliability. Field visits were conducted to distribution substations in India to collect data. The objectives of the study are to provide reliability data to utility management, allow performance comparisons, determine how design and maintenance affect reliability, and aid maintenance scheduling. The significance of the study is that distribution reliability is important for utilities facing market pressures to satisfy customers while minimizing costs. The MATLAB model allows a new method for evaluating reliability and identifying cost-effective preventative maintenance strategies.
Nov 2018 Table of contents; current issue -International Journal on Soft Comp...IJSCAI Journal
The document discusses using machine learning algorithms to analyze the relationship between economic freedom and quality of life. It examines the Economic Freedom of the World index and the Human Development Index with modern machine learning methods. The analysis finds that these advanced algorithms achieve a stronger correlation between the indices than statistical means alone. However, there is still some room for non-liberal interpretations of how to design economic policies to improve people's lives. The goal is to objectively evaluate the impact of economic freedom through a data-driven approach.
Stochastic actor-oriented models (SAOMs) summarize the key components and estimation process of these models. SAOMs model how networks and behaviors change over time as a result of endogenous network effects and influence between connected individuals. The models estimate parameters representing these effects to predict tie formation and changes in behaviors. SAOMs account for selection into the network based on attributes as well as social influence processes within the network. Estimation involves maximum likelihood to estimate parameters of network and behavior functions that represent how individuals make network and behavioral decisions.
Strengthening Supply Chains for a Sustainable Housing Sector in Nepal : Facto...ijmvsc
EU’s main approach to sustainable housing is promoting green practices/products within the building
construction sectors SCs. EU Switch Asia program financed research conducted in Nepal, 2015, to
understand the organization of SCs, identify factors/barriers affecting SCM and existing relationships, the
reasons to adopt green concepts/approaches and recommend support for SMEs to strengthen the sector’s
management and sustainability. 109 companies, non-probabilistic snowball sampling and semi-closed
questionnaires used in the survey. Conclusions: Companies create SCs to increase customer satisfaction,
maintain long-term sales and retain clients. Size of company influences SCs organisation, SCM and
using/producing green products/services; majority of participants had a person in the company to manage
SC’s and had very good knowledge of SC, SCM and greening issues. SMEs need support with:
information/communication technology, promotion and improvement/development of green
products/services. Government should: increases awareness of green building products/services; develop
financial green incentives and simplify administrative procedures to buy solar products.
This document provides an overview of stochastic actor-oriented models (SAOMs), including:
1. The general components of SAOMs including network and behavior objective functions that determine how and when actors change their ties and behaviors.
2. The estimation procedure which uses simulations to refine parameter estimates and minimize the deviation between simulated and observed network statistics.
3. Examples of how to interpret the output including checking for convergence of the model to the observed data.
E-GOVERNANCE ADOPTION IN GOVERNMENT ORGANIZATION OF INDIAijmpict
India, the growing economic super-power proceeded with lightning speed towards the adoption and successful implementation of e-governance. The Government of West Bengal (federal unit of India) implemented e-governance in pension office i.e. Pension Management System (PMS), for faster and efficient delivery of public services. The success of PMS is dependent on many factors and one among them is the successful adoption by the employee which has been empirically analyzed. The study used the
Technology Acceptance Model (TAM) and Trust to build a conceptual model. Data collected from 60 employees working on the system and the model is assessed with regression analyses. The findings show that the determinants of the research model are support. The study also shows that the system doesn’t perform completely error free tasks which the Government of West Bengal should address. This is the first study of employee adoption of e-governance in pension office of India.
A primary research analysis is conducted with Simply Energy. The purpose of the research is to identify and assess how the company provides its consumers with needed services and also to find out satisfaction levels of the customers. Recommendations are made for increasing sustainability initiatives in order for the company to face current competitive situations.
Your Quick Guide to Energy Management for Sustainability and Reduced Business...QuekelsBaro
Learn how to increase energy efficiency, conserve energy, and harness renewable energy for your business, with free access to our energy management plan.
In the present world we are facing lot of electricity problem, lack of natural substances, depletion of fossil fuels etc., hence we should think of acquiring maximum with the limited energy resources. Green computing is the term used to denote efficient use of resources in computing .This paper mainly deals with a regenerative approach towards green computing, to enhance the power backup of battery in the laptops. This paper also throws light on regenerative technique (the heat generated by the processor is utilized) and made to harness energy.
IRJET- An Energy Conservation Scheme based on Tariff ModerationIRJET Journal
This document discusses an energy conservation scheme based on tariff modification for domestic users. It proposes a new tariff rate structure that provides incentives for low consumption and penalties for high consumption. This aims to motivate consumers to reduce energy usage without causing losses for electric utilities. The existing structure provides 100 free units, which does not encourage conservation and causes losses. The proposed system calculates bills based on consumed units and compares to averages to determine incentives or penalties. The goal is to reduce residential energy usage through this modified tariff approach.
Optimization of the Building Energy Performance through Dynamic Modeling, Sys...IJERA Editor
The annual energy consumption in the residential and commercial sectors, in India is rising consistently at about 8% and the overall energy consumption in buildings has seen an increase from a low of 14% in the 1970s to nearly 33% in 2004/05. The electricity sector in India had an installed capacity of 254.049 GW as of end of September 2014. The research paper will deal with the modeling and optimization of the building energy performance by means of the application of the dynamic building simulation, the optimization of the energy systems and the verification of the energy consumptions and comfort conditions. An integrated tool is at an early stage of development to optimize the building energy performance to be expressed in terms of total energy use. The goal of the research paper is to optimize the building energy performance through the potential of the passive building technologies and the increase of efficiency of the building system.
Data Science for Building Energy Management a reviewMigue.docxrandyburney60861
Data Science for Building Energy Management: a review
Miguel Molina-Solanaa,b, Maŕıa Rosa,∗, M. Dolores Ruiza, Juan Gómez-Romeroa, M.J. Martin-Bautistaa
aDepartment of Computer Science and Artificial Intelligence, Universidad de Granada
bData Science Institute, Imperial College London
Abstract
The energy consumption of residential and commercial buildings has risen steadily in recent years, an
increase largely due to their HVAC systems. Expected energy loads, transportation, and storage as well
as user behavior influence the quantity and quality of the energy consumed daily in buildings. However,
technology is now available that can accurately monitor, collect, and store the huge amount of data involved
in this process. Furthermore, this technology is capable of analyzing and exploiting such data in meaningful
ways. Not surprisingly, the use of data science techniques to increase energy efficiency is currently attracting
a great deal of attention and interest. This paper reviews how Data Science has been applied to address the
most difficult problems faced by practitioners in the field of Energy Management, especially in the building
sector. The work also discusses the challenges and opportunities that will arise with the advent of fully
connected devices and new computational technologies.
1. Introduction
There is a general consensus in the world today that human activities are having a negative impact
on the environment and have accelerated both global warming and climate change. These environmental
threats have been intensified by the emissions produced by the energy required for the lighting and HVAC
(heating, ventilation and air-conditioning) systems in building constructions. According to the International
Energy Agency (IEA), residential and commercial buildings are responsible for up to 32% of the total final
energy consumption. In fact, in most IEA countries, they account for approximately 40% of the primary
energy consumption. Similar statistics are given by the World Business Council for Sustainable Development
(WBCSD) within the framework of its Energy Efficiency in Buildings (EEB) project1. Also provided is a
comprehensive review [1] of the state of the art in building energy use (with a primary focus on energy
demand).
These data indicate that inefficient energy management in aging buildings combined with rising construc-
tion activity in developed countries will cause energy consumption to soar in the near future and heighten the
negative impacts associated with this consumption. Moreover, variable energy costs call for the implemen-
tation of more intelligent strategies to adapt and reduce energy consumption as well as to find alternative
and sustainable energy sources. The relevance of these issues is clearly reflected in the research priorities of
the European Union, as stated in its Horizon2020 Societal Challenge “Secure, Clean and Efficient Energy”.
This work program targets a significant reduction in energy consu.
Analysis of Electric Power Consumption using Smart Meter DataIRJET Journal
This document proposes an analytical model to analyze electric power consumption using smart meter data. The model consists of two modules: 1) A consumer-oriented module that clusters consumers with similar appliances and analyzes consumption patterns to provide customized recommendations for reducing usage. 2) A predictive module that uses historical consumption data to identify trends and predict future usage or irregularities. The proposed system first collects smart meter data, preprocesses it, then clusters consumers using k-means clustering based on appliance type and number. Consumption profiles are analyzed within each cluster to develop standards and suggest recommendations. Historical data is also used for predictive modeling and outlier detection.
Prediction of Power Consumption and Leakage Detectionijtsrd
Energy consumption and predictions for residential buildings play an important role within the energy management and system, as the availability and demand of energy resources is the dynamic and seasonal changes. Human beings are unaware of the cost of energy consumed by various appliances and the energy resources available for the next generation. Each appliances in homes will consume different power consumption in different seasons. Accordingly the bill rate changes. Vyshnavi B | Selma P. T | Renin Joy | Sheethal M. S "Prediction of Power Consumption and Leakage Detection" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30589.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/30589/prediction-of-power-consumption-and-leakage-detection/vyshnavi-b
This document summarizes an electrical energy audit conducted at the Nandi Institute of Technology and Management Sciences (NIT&MS) campus in Bangalore, India. The audit found that the total average monthly electrical energy consumption across the campus was 3,842.842 kWh. Personal computers in labs, offices, and libraries accounted for the highest consumption at 39.14% of total usage. Fans were the second highest usage at 21.53%. Recommendations to improve energy efficiency included replacing conventional ballasts with electronic ones, installing motion sensors, replacing CRT monitors with LCDs, and switching to LED lights. Implementing all recommendations could save an estimated 10,435.84 kWh per year and reduce electricity costs by
A new smart approach of an efficient energy consumption management by using a...IJEECSIAES
Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is satisfied. It divides the measured data for actual power (Ap) of the electrical model into two portions: the training portion is selected for different maximum actual powers, and the validation portion is determined based on the minimum output power consumption and then used for comparison with the actual required input power. Simulation results show the energy expenditure problem can be solved with good accuracy in energy consumption by reducing the maximum rate (Ap) in a given time (24) hours for a single house, as well as electricity’s bill cost, is reduced.
A new smart approach of an efficient energy consumption management by using a...nooriasukmaningtyas
This document proposes a new smart approach for efficient energy consumption management using machine learning techniques. It divides measured actual power data into training and validation portions to determine efficient energy consumption. Simulation results showed the approach can accurately reduce energy consumption and costs by lowering the maximum allowed power consumption over a 24-hour period for a single house. The approach connects to cloud services and uses Internet of Things technologies for real-time energy monitoring.
ADOPTING MEASURES TO REDUCE POWER OUTAGESelelijjournal
This work investigates and evaluates the electric energy interruptions to the residential sector resulting
from severe power outages. The study results show that this sector will suffer tangible and intangible losses
should these outages occur during specific times, seasons, and for prolonged durations. To reduce these
power outages and hence mitigate their adverse consequences, the study proposes practical measures that
can be adopted without compromising the consumers’ needs, satisfaction ,and convenience.
This document discusses measures to reduce power outages for the residential sector. It first reviews existing studies on assessing the costs of power outages and energy conservation strategies. It then outlines the objectives of the work, which are to estimate the adverse effects of power outages on residents and propose energy conservation strategies that reduce outages and costs. To achieve this, the author conducted a consumer survey to estimate outage costs based on residents' perceptions and willingness to pay. A mathematical model was also developed relating energy consumption, costs, and outages. The model shows that energy conservation can maximize benefits by reducing consumption and outages. The document evaluates outage costs using both the survey approach and mathematical modeling.
This work investigates and evaluates the electric energy interruptions to the residential sector resulting from severe power outages. The study results show that this sector will suffer tangible and intangible losses should these outages occur during specific times, seasons, and for prolonged durations. To reduce these power outages and hence mitigate their adverse consequences, the study proposes practical measures that
can be adopted without compromising the consumers’ needs, satisfaction, and convenience.
Reinforcement Learning for Building Energy Optimization Through Controlling o...Power System Operation
This paper presents a novel methodology to control HVAC system and minimize energy cost
on the premise of satisfying power system constraints. A multi-agent architecture based on game theory and
reinforcement learning is developed so as to reduce the cost and computational complexity of the microgrid.
The multi-agent architecture comprising agents, state variables, action variables, reward function and cost
game is formulated. The paper lls the gap between multi-agent HVAC systems control and power system
optimization and planning. The results and analysis indicate that the proposed algorithm is benecial to deal
with the problem of ``curse of dimensionality'' for multi-agent microgrid HVAC system control and speed
up learning of unknown power system conditions.
Energy audit, conservation and power factor improvement for bmsit campuseSAT Journals
Abstract The main focus of this paper is to achieve and maintain optimum energy throughout the organization so as to minimize energy costs and improve power quality. Energy Audit is a systematic approach for decision-making in the area of energy management. A simple payback period calculation and formulation has been executed. Keywords: LCD, CRT, KW, KVA, KVAR.
Monitoring and analysis of reliaibility of electrical distribution systemIAEME Publication
This document summarizes a study on monitoring and analyzing the reliability of electrical distribution systems using MATLAB. The study develops a reliability analysis program in MATLAB to assess factors that affect distribution reliability. Field visits were conducted to distribution substations in India to collect data. The objectives of the study are to provide reliability data to utility management, allow performance comparisons, determine how design and maintenance affect reliability, and aid maintenance scheduling. The significance of the study is that distribution reliability is important for utilities facing market pressures to satisfy customers while minimizing costs. The MATLAB model allows a new method for evaluating reliability and identifying cost-effective preventative maintenance strategies.
Optimal scheduling and demand response implementation for home energy managementIJECEIAES
The optimal scheduling of the loads based on dynamic tariffs and implementation of a direct load control (DLC) based demand response program for the domestic consumer is proposed in this work. The load scheduling is carried out using binary particle swarm optimization and a newly prefaced nature-inspired discrete elephant herd optimization technique, and their effectiveness in minimization of cost and the peak-toaverage ratio is analyzed. The discrete elephant herd optimization algorithm has acceptable characteristics compared to the conventional algorithms and has determined better exploring properties for multi-objective problems. A prototype hardware model for a home energy management system is developed to demonstrate and analyze the optimal load scheduling and DLCbased demand response program. The controller effectively schedules and implements DLC on consumer devices. The load scheduling optimization helps to improve PAR by a value of 2.504 and results in energy cost savings of ₹ 12.05 on the scheduled day. Implementation of DLC by 15% results in monthly savings of ₹ 204.18. The novelty of the work is the implementation of discrete elephant herd optimization for load scheduling and the development of the prototype hardware model to show effects of both optimal load scheduling and the DLC-based demand response program implementation.
This document discusses a thesis submitted by Akhil Ravindran for the degree of MSc in Computer Science. The thesis proposes the Tamagreen project, a mobile application to make young students more aware of energy consumption by displaying images related to energy usage. It acknowledges the support received from the energy analytics firm Wattics, which will provide smart meter data. The literature review covers topics like EU energy policy, the impact of feedback and goals on consumer behavior, energy audits, community initiatives, dynamic pricing, smart meter programs, and gamification of energy savings applications.
Global issue based power generation expansion planning for a power systemeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Global issue based power generation expansion planning for a power systemeSAT Journals
This document discusses global issue based power generation expansion planning for an electric power system. It aims to develop an optimization model that considers factors like growth in fuel prices and fluctuations, benefits of carbon trading, and power system risks. The model is applied to an electric power system for the future. It formulates the problem as a multi-objective model considering investment and generation costs, imported fuels, carbon trading benefits, and environmental impacts. The model is developed in MATLAB and simulated to obtain the optimal output of each power plant at minimum cost for building, production, and fuel.
Global issue based power generation expansion planning for a power systemeSAT Journals
Abstract In This Project an global issue based power generation expansion planning model has been developed for optimization that considers the growth of fuel prices and its fluctuation, benefits of carbon-trading in generation expansion decision, power risks . The Developed model is applied to An Electric Power System for the future. In an electric power system, the electric demand has been running ahead of supply. In addition, of the growth of fuel price can affect the country economy. To minimize these problems, a multi-objective model preceded by electric demand forecasting is developed by considering the unit of power generation and investment cost, imported fuels and benefits of carbon trading, environmental impacts. A model has been developed in the MATLAB and is simulated to get the output of each power plant at a very nominal cost for building the power plants, production and fuel. Keywords: electrical power generation, expansion, planning, Load forecasting, Optimizing, linear model
In today’s commercial buildings, installing an effective
WAGES (water, air, gas, electricity, steam) metering
system can be a source of substantial energy and cost
savings. This white paper examines WAGES metering
as the essential first step toward a comprehensive
energy management strategy. Best practices for
selecting meters, and identifying metering points are
described. In addition, metrics for measuring gains in
energy efficiency are explained.
Similar to Adding Psychological Factor in the Model of Electricity Consumption in Office Building (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
2. Int J Elec & Comp Eng ISSN: 2088-8708
Adding Psychological Factor in the Model of Electricity … (Meredita Susanty)
4487
cleverer tactic from social psychology which had the probability to make a lasting impact called normative
comparison. It gives those same people clear, personalized insights into their energy use, then add context by
comparing them to each other. Scientist believe if this approach is applied to home energy use it is an
astonishingly reliable way to motivate people to make smarter decisions [1], [2], [4].
Bedwell [5] in his literature review indicates greatest potential for energy saving by changing user
behavior. It is said that disaggregation of energy data and apportionment is valuable to leverage data for
behavioural change and is concluded that setting clear specific goal within and coherent with company
strategy is likely to be effective and more so if specific feedback on these goals are provided.
Model socio-technical system of energy consumption in workplace is used in this paper to analyse
the impact of implementing different strategies to promote energy saving awareness and motivate staff to
change their behaviour. This model aims to find the impact of adding psychological factors for electricity
consumption in office building and to understand the impact of applying different approaches of energy data
apportionment to change staff behaviour toward energy consumption reduction.
The paper is organized as follows. In Section 2, present the specification and design of the model. In
Section 3, we describe the experimental design, execution and validation. In Section 4, the simulation results
of the model are presented. Finally, some conclusions are presented in Section 5.
2. MODEL DEVELOPMENT
2.1. Conceptualization
The conceptual model was developed using a framework described in Robinson [6]. It is started
with an understanding of the problem situation. A set of modelling objectives are then determined. These
objectives then drive the derivation of the conceptual model, first by defining the inputs and outputs, and then
by defining the content of the model itself. Table 1 shows Model Specification.
Table 1. Model Specification
Problem Situation Changing of user behaviour may help reduce energy consumption.
Comparative feedback or normative social influence has influence to change user behaviour.
Whether fine-grained energy consumption data should be apportioned at individual or group level remains
debatable.
Objective Observe the most effective strategy to reduce energy consumption.
Observe the total energy consumption per energy awareness stereotype.
Input/ Experimental
Factor
User initial stereotype
Apportionment level
Feedback availability
Data apportionment anonymity
Implementation of sanction
Behaviour threshold
Output/ Response School Energy Consumption per month
Monthly Energy Consumption per stereotype
Number of Stereotype shift per month
Model Scope Model scope is used to identify the key interconnections between the experimental factors and responses and
the other components of the real world. See Table 2 for detail
Model Level of
Detail
The level of detail represents the components defined within the scope and their interconnection with the
other components of the model with sufficient accuracy. See table 3.
Assumption Potential free-riders is 10% of total people in group
Individuals were actively reviewing comparative feedback information and this influenced their behaviour.
Each user use one computer which consist of PC, monitor, and input device such as mouse and keyboard.
Laptop and computer are assumed to consume same amount of electricity power.
Computer will automatically change to standby mode when user leave the room for 20 minutes.
Each user has different motives in performing their action, such as self-achievement and altruism value.
This simulation reflects users who are motivated by achievement.
Simplification This research only focus on comparative feedback and the way feedback is apportioned to user.
This model only allow decision making process once a month.
This project groups staff based on their spatial location.
2.2. Design
This model is a simplification of a former model [3] which consists of 5 object classes; User, Office,
Light, Computer and Main. A new algorithm, which implement psychological factors, for decision making
was added into the user agents and is executed at the end of the month. Table 2 shows model of scope.
Table 3 shows model level of detail.
3. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 6, December 2018 : 4486 - 4495
4488
Table 2. Model of Scope
Element Detail Decision Justification
Actor Staff, Research fellows, PhD
students
Include Regularly occupy office building
UG + MSc Students Exclude Do not have control over their work environment
Visitors Exclude Insignificant energy consumption
Appliances
Heating, Ventilating, Air
Conditioning (HVAC) System
Exclude Only need one major energy consuer to test the theory;
decided to go for electricity
Lighting Include Interacts with users on a daily basis; controlled by user
Computer Include Interacts with users on a daily basis; controlled by user
Monitor Exclude Modelled as part ot the computer
Continuously running
appliances
Exclude Constant consumption of electricity; not controllable by
individuals
Personal appliances Exclude No way to measure consumption
Weather Temperature Exclude Not necessary for proof-of-principle
Natural Light Level Exclude Not necessary for proof-of-principle
Room Office Include Location where electronic appliances are installed
Lab Exclude Mainly used by UG + MSc
Kitchen Include as group
(Other Room)
Common areas frequently used by users
Toilet
Corridor Include Commonly used when users move around
Psychological
Factors
Comparative Feedback Include Effective strategy to reduce energy consumption in
residential building
Informative Feedback Include Effective strategy to remove barriers in performing
specific behavior
Apportionment Level Include Effective strategy to reduce energy consumption in office
building
Freeriding Include Behaviour that differentiate two apportionment strategy
Sanction Include Factor to encounter freeriding behavior
Anonymity Include
Table 3. Model Level of Detail
Model Level
of Detail
Detail Decision Comments
User Awareness Level Include Determine the probability whether user will switch off unnecessary
electronic appliances.
Working time Include Determine total energy consumption.
Location Include User triggers electronic appliances in a certain location.
Appliances Energy Consumption Include Things which is aimed to be reduced.
Usage Time Exclude Reflected from working time.
State (On/Off/Standby) Include Determine the energy consumption.
Energy Consumption Pattern Exclude Reflected from awareness level.
Automatic/Manually On/Off Include Affected by user behaviour and at the end it will give impact to
overall energy consumption.
Brand/Model Exclude Give impact on appliances energy consumption. Assuming that all
appliances in a similar type consume same amount of energy.
Location Exclude Reflected from electrical appliances installed in a room.
Room Capacity Include Shows number of appliances that are installed in a certain room. This
will also determine the total energy consumed in a specific room.
Occupancy Status Exclude Reflected from user location.
Electrical Appliances
Installed
Include Show electric appliances type that are installed in a room.
Number of Occupant Include Needed to apportion data to individual level.
Psychological
Factor
Existence Include Show whether or not the factor is implemented.
Impact Include The thing that are going to be observed in this research.
Pattern/Condition Include The thing that determine motivation increase/decrease.
2.2.1. Behaviour of Electricity User Agents
User, an active agent who triggers energy consumption in workplace, starts to consume electricity
when they arrive in an office building. To find their own office, user walk from one room to another. The
communal room where user passes to reach their own office is generalised as corridor. Besides that, user also
uses other rooms such as toilet, pantry, lab, meeting room. When user leaves office building, their energy
consumption is expected to be zero. However, if they do not switch off their electronic appliances, their
electricity consumption is still counted. These processes are represented in a statechart in the simulation
model. The state in statechart shows location in the office building while state inside it shows user’s action
when they occupy the office. Total electricity which is consumed by each user is calculated using the
following formula:
4. Int J Elec & Comp Eng ISSN: 2088-8708
Adding Psychological Factor in the Model of Electricity … (Meredita Susanty)
4489
𝜖 =
∑ 𝑙
𝑜
+ 𝑐
𝜖: own energy, ∑ 𝑙 : energy of all lights in a room that user is occupied
𝑜: number of occupant, 𝑐: energy of computer
The nature and data about user behaviour that is used in this project was gained from former
research [3], categorized user based on their working time [3] and energy saving awareness [3] used of user’s
movement from one location to the other as their state. While [3] implements three different electricity
management strategy – automated, mixed and manual, this model only implemented the mixed strategy when
user is expected to switch off the electronic appliances manually when they leave a room but in case they do
not switch it off, it will be automatically switch off or standby in a certain time after they leave that room.
New algorithm is based on several psychological factors, namely normative social influence,
behaviour-specific ability and additional factors for group apportionment because of the potential free riding
act, anonymity in data apportionment and the implementation of sanction. Those factors will change user’s
motivation. Since energy saving awareness stereotype determine user’s motivation level, in reverse changes
in user motivation level will also change their stereotype. The flowchart in Figure 2 represents the logic of
the algorithm which links the logic to its rationale in Table 3 based on [5].
Figure 1. (a) User Agent (b) Light Agent (c) Computer Agent (d) Office Agent State Chart
The algorithm is triggered at the end of the month, a summary of user’s total electricity consumption
is presented together with information about the majority of other users’ consumption. Based on this
information, people will make comparison with other people performance and comparison with their
performance in the previous month. Data apportionment to individual and group leads to different formula to
calculate total energy consumption. In a room occupied by more than one user, if data is apportioned to
individual level the total of light energy consumption is divided by the number of room occupant. When data
is apportioned to group level, implementation of sanction will reduce the number of free rider by increasing
their motivation and specific evidence of one’s consumption (not anonymous) will put pressure on
themselves to perform better in the future because of lateral control which will increase their motivation.
Furthermore, there is another factor namely behaviour specific ability that might have impact to
motivation but is not depicted in Figure 1(a). Providing practical tips on how to perform better in conserving
energy in office building is increasing people motivation or in a situation when people’s motivation is
decreasing, the value of motivation decrease is lower than if this practical information is not available. The
availability of practical information is represented as a variable named feedback in the model as shown in
Figure 2.
2.2.2 Behaviour of Light Agents
Light, a passive agent and is installed in each room in the building, has 2 states, on (consume 60W)
and off (0W) [3], shown in Figure 1(b). Initially, lights in a room is off. User presence in a room triggers
automated light sensor which will switch the light on. Light will be off either if user switch it off or if the
sensor does not detect any user presence for 20 minutes.
2.2.3 Behaviour of Computer Agents
Computer, a passive agent and only available in user’s office room, has three states, off (0W), on
(400W) and standby (25W), as shown in Figure 1(c). It changes from on state to off state and vice versa
5. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 6, December 2018 : 4486 - 4495
4490
because of user’s action. When user is not in the room for a certain period and does not switch the computer
off, it will automatically change its state to standby then back to state on when it detects users’ action.
2.2.4 Behaviour of Office Agents
Office agent is a passive agent that represents a certain location in an office building. Computers
and lights are installed in an office, while corridor and other room only have lights. User occupies an office
during the day. It has two states, vacant and occupied, based on user presence as shown in Figure 1(d). When
users occupy a room, their presence triggers the light on and he/she might switch the computer on. Both
actions start energy consumption in a room. Conversely, when user leaves a room energy consumption will
be zero if they switch off all appliances before leaving. Otherwise, after a certain time, the light will
automatically switch off and computer will keep consuming 25W of energy because it enters standby state.
The new algorithm rationale as shown in Table 4. Since apportionment to group level categorised people
based on their spatial location, the formula below is used to calculate group consumption:
∑ 𝑒𝑐 = ∑ 𝑙 + ∑ 𝑐 ∑ 𝑒𝑐: Total Energy Consumption, ∑ 𝑙 : energy of all lights installed in the
room, ∑ 𝑐 : energy of computer installed in the room
Figure 2. New Algorithm Flowchart
Table 4. The New Algorithm Rationale
No. Rationale
1. Having knowledge of other people’s behaviours works as ‘descriptive norms’ to the group, and people will be inclined to
follow these norms and act similarly [9], [10], [11].
Energy feedback often focuses on individual actions and related small costs/savings, which may dishearten individuals
given that they see their actions only having a relatively minor impact [8]. Observing the larger scale consumption
apportioned to a group may increase perceived instrumentality, a significant factor in promoting energy-saving behaviour
[12], [13].
2. With regard to descriptive norms, if in fact it is observed that others tend to consume more, then people may actually increase
their usage as a result [14], [15].
3. Freeriding tends to be more common in larger groups and when individual behaviour is more anonymous [16].
4. Making mechanisms available to identify free-riders [17] and implementing sanctions (social, e.g. gossip, or institutional, e.g.
fines) to prevent further freeriding [18].
5. The injustice of freeriding encourages anger and confrontation [19], and there is potential for unjustified scapegoating when
there is no specific evidence of individual consumption.
6. There are some evidences that not revealing exactly who has consumed what proportion of a resource may result in
increased fear or guilt and lead to reduced consumption overall through compensating behaviour [20], [5].
However, the impact of this was found to be minor, and deliberate attempts to instil uncertainty may clash with more
traditional organisational values of teamwork.
6. Int J Elec & Comp Eng ISSN: 2088-8708
Adding Psychological Factor in the Model of Electricity … (Meredita Susanty)
4491
3. EXPERIMENTATION
3.1. Experimental Design
Although office is closed overnight, there are some electrical appliances that still consume energy.
For example, when users leave the computer on when they leave the office. So, this model is a non-
terminating simulation and the output of non-terminating system often reach a steady state. The simulation
output is stochastic because it depends on user behaviour which is determined by any random event.
3.1.1. Warm up Periode
The model compares monthly energy consumption. However, at the start of the simulation run it
might not the beginning of the month. It might lead to much lower energy consumption which is not realistic.
The inclusion of such data would bias the results obtained from the simulation. Graphical method that
visually inspects time-series output data was used to identify initialization bias and determine the warm-up
period. Because data can be very noisy and make it difficult to spot initialization bias, at least five
replications should be performed [6]. Mean averages of those replications for each month is presented in the
Figure 3 and warm-up period is the point at which the output appears to settle into a steady state. From the
graph in Figure 3, warm-up period for this experiment is 4, which means total energy consumption in the first
month until the fourth month will be omitted in the analysis.
3.1.2. Number of Replication
To obtain sufficient output data, the result from a single replication is not reliable. A graphical
method and confidence interval method were used to determine the number of replication. Graphical method
was performed by plotting cumulative mean of the output data from a series of replications. The number of
replications required was defined by the point at which the line becomes flat.
Confidence interval is used to show how accurately the mean average of a value is being estimated
by using a statistical mean. The narrower the interval the more accurate the estimate it deemed to be.
Confidence interval 95% with significance level 5% was chosen for this model. It means that 95%
probability that the value of the true mean (obtained if the model is run for an infinite period) lies within the
confidence interval. The estimated number of replication for this model is 5.
Figure 3. Warm Up Period Graph
Table 5. Experimentation Result
Replication Average Monthly Energy Consumption
No Apportionment Individual Apportionment Group Apportionment
1 1,013,363.80 917,511.81(-9.46%) 825,872.78(-18.50%)
2 947,377.38 938,763.43(-0.91%) 887,671.28(-6.30%)
3 1,036,726.87 937,589.35(-9.56%) 866,805.62(-16.39%)
4 1,108,863.01 968,278.02(12.68%) 915,456.87(-17.44%)
5 1,097,287.42 938,288.99(-14.49%) 902,786.73(-17.73%)
3.1.3. Run Length
Because non-terminating simulation does not have a natural end point, the length of a simulation run
needs to be determined by the model user. Run-length was calculated by plotting cumulative means and
convergence based in five replications. Although the calculation indicate that the minimum run-length is 6,
7. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 6, December 2018 : 4486 - 4495
4492
the run-length for this simulation is 12 months. It is because the simulation result is going to be compared
with an energy conservation research result from Cornell University [7].
3.2. Experimentation
3.2.1. Experimental Validation
The simulation re-implemented and simplified Zhang’s model [3]. It only simulated combine energy
management strategy where user can manually switch off the light but in case user do not switch it off, light
will automatically switch off after the office is empty for 20 minutes. Without implementation of any
intervention strategy and using same input value (same working time, user energy awareness level, total
number of user that occupy office building also same total number of lights and computer that is installed in
the building), hourly energy consumption between [3] and this model is relatively the same.
The experiment result from individual apportionment was compared with the average energy
reduction from [7] about using comparative feedback to influence workplace energy conservation with case
study in Cornell University [7] to check the validity of the experiment result.
The experimentation result, shown in Table 5, gives higher reduction percentage compared to [7], in
the range of 0.91% to 18.50% and constantly reducing the energy consumption. These differences might be
caused of the simplification of real world in Table 1. First, in the real world reducing energy consumption
month-on-month might not always feasible. The best individual or group might not be able to reduce their
consumption anymore. Second, each person has different motive and goal. People with achievement oriented
will be more motivated when comparative feedback on energy usage is presented to them, since they care
about performance and personal loss/gain, rather than people with altruistic value. Altruistic also more likely
to be demotivated by sanction or free-riding. Last, this simulation only focuses on light and computer (in the
real-world HVAC consume most of energy in non-residential building [21]) while [7] considers all electricity
consumption in the building. Furthermore, the simulation shows that without any intervention the total
energy consumption is considerably stable while [7] shows that there are two buildings that slightly reduce
their energy consumption even though they were not participating in the campaign. It might be because there
are higher number of staff that have altruistic value in those building which is not reflected in this simulation.
3.2.2. Sensitivity Analysis
The presence of estimated data in a simulation leaves some uncertainty about the validity of the
model and would no doubt reduce its credibility. One way to overcome this issue is performing sensitivity
analysis to get insight about the subject of interest.
First, the motivation level as an input is varied for both scenario. One that simulate all staff has very
low motivation level (0) and another one simulates all staff has very high motivation level (98). The effect on
the total energy consumption in a year, Figure 4(a), shows a steep gradient which means there is a significant
shift in the response. It can be concluded that the response is sensitive to the change in the input.
In apportionment strategy to group level, sanction and ability to identify individual consumption in
group also give impact to motivation level. Sensitivity analysis result for sanction and anonymity factor in
Figure 4(b) shows that both factors do not have a significant impact toward total energy consumption.
3.2.3. Scenario
The model consists of 4 office rooms, 1 corridor, and 1 public area, 27 lights installed, and occupied
by 24 people who have their own computer in their own office. 5 replications were executed for each
scenario.
Each user will be assigned a work time stereotype and energy saving awareness stereotype using a
random probability. Their energy saving awareness stereotype determines the motivation level and
motivation level determines user behaviour in using unnecessary electrical appliances. If their motivation
level is higher than threshold value, more likely user will switch off appliances when they are no longer use
it. Otherwise, the appliances will either automatically switch off or enter standby state after a certain period
to conserve energy.
In order to compare the impact between individual and group apportionment, two different scenarios
will be run during experimental stage;
a. Scenario 1: Apportioned to Individual level, Anonymous, Informative Feedback available, sanction
implemented
b. Scenario 2: Apportioned to Group, Anonymous, Informative Feedback available, sanction implemented
Total energy consumption of the whole office that is produced monthly will be analysed to see how
different approaches is affect the outcome.
8. Int J Elec & Comp Eng ISSN: 2088-8708
Adding Psychological Factor in the Model of Electricity … (Meredita Susanty)
4493
Figure 4. (a) Motivation Level (b) Sanction and Anonimity in Group impact toward Total Energy
Consumption
3.2.4. Ouput Comparison from Scenarios
The experiment result as shown in Figure 5 shows that without intervention the total energy
consumption is relatively stable for along the year while presenting energy usage feedback to staff in the
building reduce the total energy consumption. The total energy consumption reduction between
apportionment strategy to individual level and group level shows a similar pattern. However, the total energy
consumption of group apportionment slightly reduces more energy consumption than individual
apportionment. Because visual comparison between individual and group consumption only shows
insignificant difference, further analysis using statistic method need to be performed to observe whether the
difference is statistically significant.
As explained in [5], although underlying group goals on collective consumption provides the
opportunity for individuals to freeride, aggregate amount presented in group apportionment which give
higher or more significant saving is highly motivating compared to small saving on individual action which
may dishearten individuals given that they see their actions only having a relatively minor impact [8].
Nonetheless, it must note that in Section 2.1 it is assumed that the potential free-rider is constantly
10% of the total group member while in the real world very large groups may encourage more free-riding
because an individual may believe that it is easier to hide. Moreover, in the context of energy monitoring the
optimum group size is yet unknown.
3.2.5. Energy Comparison based on user’s awareness
Total energy consumption per energy awareness as shown in Figure 6 shows that the energy
consumed by Big User and General User is almost the same while Energy Saver and Environmental
Champion only consume almost half of Big and General User consumption.
Since there is only slight difference of energy consumption between Energy Saver and Environmental
Champion stereotype, it is not necessary to change staff behaviour to become an Environmental Champion.
They are expected to maintain their level of consumption. Changing user behaviour from Big User or
General User to Energy Saver can save the organisation a lot of money.
3.2.6. Number of Staff per Stereotype per month
Comparative feedback on energy usage influence user’s motivation level. Since users are
categorized to a certain stereotype based on motivation level, the changes of motivation level will change
user’s stereotype. Figure 7 shows that using group apportionment strategy the changes in the total number of
staff per stereotype is faster. Staff starts to shift to a better stereotype around the third month. The shift
significantly occurs around the eighth month.
4. RESULT ANALYSIS
Beside compare the graph visually, deeper analysis using paired-t confident interval comparison was
performed. This method identifies the statistical significance of a difference in the result from two scenarios.
It looks at the mean value of each case, standard deviation and number of replication. Paired-t confidence
interval comparison is calculated using formula defined in [6].
9. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 6, December 2018 : 4486 - 4495
4494
Figure 5. Energy Consumption for Each
Apportionment
Figure 6. Total Energy Consumption per
Stereotype
Five replications were performed for each scenario, then the average monthly energy consumption
within a year is used for this analysis. The calculation result is shown in Table 6. Since the confidence
interval is a to the right of zero, it can be concluded with specified level of confidence (95%) that the result of
Scenario 1 is greater than the result of Scenario 2. However, because the aim is to reduce energy
consumption, Scenario 2 is to be preferred.
Figure 7. The Changes in the total number of staff per stereotype
Table 6. Paired-t Confidence Interval Comparison Calculation
Significance Level 5.0%
Confidence Interval
Replica-
tion
Scenario 1
Result
Scenario 2
Result
Difference Cum. Mean
Difference
Standard
Deviation
Lower
Interval
Upper
Interval
Conclusion
1 917,511.81 825,872.78 91,639.02 91,639.02 n/a n/a n/a n/a
2 938,763.43 887,671.28 51,092.16 71,365.59 28,670.96 -186,232.78 328,963.96 No Difference
3 937,589.35 866,805.62 70,783.74 71,171.64 20,276.21 20,802.73 121,540.55 S1>S2
4 968,278.02 915,456.87 52,821.15 66,584.02 18,927.98 36,465.38 96,702.65 S1>S2
5 938,288.99 902,786.73 35,502.26 60,367.66 21,492.24 33,681.52 87,053.81 S1>S2
5. CONCLUSION
Since collecting fine-grained energy data in workplace is increasingly possible and changing user
behaviour using comparative feedback strategy provides a potential to reduce energy consumption, this
research is aimed to understand the impact of applying different approaches of energy data apportionment to
change staff behaviour toward energy consumption reduction by re-implementing and extending the former
model, add several psychological factors into the model.
The new algorithm reflects psychological factor when comparative feedback campaign is used as an
intervention strategy to change energy behaviour in workplace. From the experimentation result it can be
concluded that motivation plays an important role in changing user behaviour while sanction and ability to
identify individual consumption in group does not. Big and General User are the target of behaviour change
strategy because changing their behaviour has significant impact in lowering whole energy usage thus help
10. Int J Elec & Comp Eng ISSN: 2088-8708
Adding Psychological Factor in the Model of Electricity … (Meredita Susanty)
4495
the organisation saves money. Moreover, apportionment strategy to group level give higher result in energy
consumption reduction for the whole building even though it provides opportunity for individual to freeride.
The conclusion only accurately reflects lights and computer consumption. In the model scope there are some
items that were identified to have significant impact toward energy consumption and energy conservation but
does not included in this research.
REFERENCES
[1] Nolan, J., Schultz, P., Cialdini, R., Goldstein, N., & Griskevicius, V. “Normative Social Influence is
Underdetected”. Personality and Social Psychology Bulletin, 2008; 34(7): 913-923
[2] Carrico, A. R., & Riemer, M. “Motivating energy conservation in the workplace: An evaluation of the use of group-
level feedback and peer education”. Journal of Environmental Psychology, 2011; 31: 1-13.
doi:10.1016/j.jenvp.2010.11.004
[3] T. Zhang, et al., “Modelling electricity consumption in office buildings: An agent-based approach”. Energy
Buildings. 2011 doi:10.1016/j.enbuild.2011.07.007
[4] Webster, John. 'Europe Is Missing Out On A Huge Climate Opportunity - And €2.4Billion A Year In Energy
Savings'. The Huffington Post UK. N.p., 2015. Web. 20 July 2015.
http://www.huffingtonpost.co.uk/johnwebster/europe-is-missing-out-on-_b_5529827.html
[5] Ben Bedwell, Caroline Leygue, Murray Goulden, Derek McAuley, James Colley, Eamonn Ferguson, Nick Banks &
Alexa Spence. “Apportioning energy consumption in the workplace: a review of issues in using metering data to
motivate staff to save energy”, Technology Analysis & Strategic Management. 2014; 26:10, 1196-1211, DOI:
10.1080/09537325.2014.978276
[6] Robinson, S. “Simulation: The Practice of Model Development and Use”. Chichester, Eng.: Wiley. 2004.
[7] Dixon, G. N., Deline, M. B., McComas, K., Chambliss, L., & Hoffmann, M. “Using comparative feedback to
influence workplace energy conservation: A case study of a university campaign”. Environment and Behavior,
2015; 47(6): 667-693.
[8] Spence, A., C. Leygue, B. Bedwell, and C. O’Malley. “Engaging with Energy Reduction: Does a Climate Change
Frame have the Potential for Achieving Broader Sustainable Behaviour?” Journal of Environmental Psychology.
2014; 38: 17–28.
[9] Cialdini, R. B., C. A. Kallgren, and R. R. Reno. “A Focus Theory of Normative Conduct: A Theoretical
Refinement and Reevaluation of the Role of Norms in Human Behaviour.” In Advances in Experimental Social
Psychology, 1991; 201–234. New York, NY: Academic.
[10] Cialdini, R. B. “Crafting Normative Messages to Protect the Environment.” Current Directions in Psychological
Science. 2003; 12 (4): 105–109.
[11] Thogersen, J. “Norms for Environmentally Responsible Behaviour: An Extended Taxonomy.” Journal of
Environmental Psychology. 2006; 26 (4): 247–261.
[12] Locke, E. A., and G. P. Latham. “Building a Practically Useful Theory of Goal Setting and Task Motivation: A 35-
year Odyssey.” American Psychologist. 2002; 57: 705–717.
[13] Spence, A., W. Poortinga, C. Butler, and N. Pidgeon. “Perceptions of Climate Change and Willingness to Save
Energy Related to Flood Experience.” Nature Climate Change, 2011; 1: 46–49.
[14] Brandon, G., and A. Lewis. “Reducing Household Energy Consumption: A Qualitative and Quantitative Field
Study.” Journal of Environmental Psychology. 1999; 19 (1): 75–85.
[15] Fischer, C. “Feedback on Household Electricity Consumption: a Tool for Saving Energy?” Energy Efficiency. 2008
1 (1): 79–104.
[16] Hamburger, H., M. Guyer, and J. Fox. “Group Size and Cooperation.” The Journal of Conflict Resolution. 1975; 19
(3): 503–531.
[17] Haley, K. J., and D. M. T. Fessler. “Nobody’s Watching? Subtle Cues Affect Generosity in an Anonymous
Economic Game.” Evolution and Human Behavior. 2005; 26 (3): 245–256.
[18] Fehr, E., U. Fischbacher, and S. Gächter. “Strong Reciprocity, Human Cooperation and the Enforcement of Social
Norms.” Human Nature. 2002; 13: 1–25.
[19] Carver, C. S., and E. Harmon-Jones. “Anger is an Approach-related Affect: Evidence and Implications.”
Psychological Bulletin. 2009; 135 (2): 183–204.
[20] Elgaaied, L.“Exploring the Role of Anticipated Guilt on Pro-environmental Behavior – A Suggested Typology of
Residents in France Based on their Recycling Patterns.” Journal of Consumer Marketing. 2012; 29 (5): 369–377.
[21] US Energy Information Administration (EIA) Commercial Buildings Energy Consumption Survey (CBECS), 2003
BIOGRAPHY OF AUTHOR
Meredita Susanty received master’s degree in Management of Information Technology from
University of Nottingham in 2015. She is currently working at Department of Computer Science,
University Pertamina.