The work aims to analyze and examine renewable energy sources (RES) to develop interconnected energy efficiency and energy consumption management system by integrating the software-defined machine-tomachine (M2M) communication. The article’s objectives include analysis of using RES as alternative raw materials for electricity production, the study of intelligent technologies for integrating RES into monitoring and control systems, research of devices and methods for monitoring energy production and consumption, analysis of sensor application for automation of control systems in the energy sector, a study of data transmission and information processing rates. The study results showed that the data transfer rate was delayed by 6 seconds to process 1,000 MB of information. It has been proven that wind energy can be used most efficiently within a 12-hour daily cycle, in contrast to tidal energy and solar energy. It is shown that due to the cyclical nature of obtaining energy from renewable sources, they do not fully provide energy to a large city, on the basis of which it is necessary to additionally use other energy sources. Three different types of power generation facilities were examined and compared. Wind farms were found to have the highest potential for electricity generation, amounting to 1,600-1,700 kW.
Microgrid energy management system for smart home using multi-agent systemIJECEIAES
This paper proposes a multi-agent system for energy management in a microgrid for smart home applications, the microgrid comprises a photovoltaic source, battery energy storage, electrical loads, and an energy management system (EMS) based on smart agents. The microgrid can be connected to the grid or operating in island mode. All distributed sources are implemented using MATLAB/Simulink to simulate a dynamic model of each electrical component. The agent proposed can interact with each other to find the best strategy for energy management using the java agent development framework (JADE) simulator. Furthermore, the proposed agent framework is also validated through a different case study, the efficiency of the proposed approach to schedule local resources and energy management for microgrid is analyzed. The simulation results verify the efficacy of the proposed approach using Simulink/JADE co-simulation.
Micropower system optimization for the telecommunication towers based on var...IJECEIAES
This study investigates the technical and cost-effective performance of options renewable energy sources to develop a green off-grid telecommunication tower to replace diesel generators in Malaysia. For this purpose, the solar, wind, pico-hydro energy, along with diesel generators, were examined to compare. In addition, the modeling of hybrid powering systems was conducted using hybrid optimization model for energy (HOMER) simulation based on techno-economic analysis to determine the optimal economically feasible system. The optimization findings showed that the hybrid high-efficiency fixed photovoltaic (PV) system with battery followed by 2 kW pico-hydropower and battery are the optimal configurations for powering off-grid telecommunication towers in Malaysia with the lowest net present cost (NPC) and cost of energy (COE). These costs of NPC and COE are more down than diesel generator costs with battery by 17.45%, 16.45%, 15.9%, and 15.5%, respectively. Furthermore, the economic evaluation of the high-efficiency solar fixed PV panels system annual cash flow compared to the diesel generator with the battery system indicated a ten-year payback period.
INTELLIGENT ELECTRICAL MULTI OUTLETS CONTROLLED AND ACTIVATED BY A DATA MININ...ijscai
In the proposed paper are discussed results of an industry project concerning energy management in building. Specifically the work analyses the improvement of electrical outlets controlled and activated by a logic unit and a data mining engine. The engine executes a Long Short-Terms Memory (LSTM) neural network algorithm able to control, to activate and to disable electrical loads connected to multiple outlets placed into a building and having defined priorities. The priority rules are grouped into two level: the first level is related to the outlet, the second one concerns the loads connected to a single outlet. This algorithm, together with the prediction processing of the logic unit connected to all the outlets, is suitable for alerting management for cases of threshold overcoming. In this direction is proposed a flow chart applied on three for three outlets and able to control load matching with defined thresholds. The goal of the paper is to provide the reading keys of the data mining outputs useful for the energy management and diagnostic of the electrical network in a building. Finally in the paper are analyzed the correlation between global active power, global reactive power and energy absorption of loads of the three intelligent outlet. The prediction and the correlation analyses provide information about load balancing, possible electrical faults and energy cost optimization.
Intelligent Electrical Multi Outlets Controlled and Activated by a Data Minin...IJSCAI Journal
In the proposed paper are discussed results of an industry project concerning energy management in
building. Specifically the work analyses the improvement of electrical outlets controlled and activated by a
logic unit and a data mining engine. The engine executes a Long Short-Terms Memory (LSTM) neural
network algorithm able to control, to activate and to disable electrical loads connected to multiple outlets
placed into a building and having defined priorities. The priority rules are grouped into two level: the first
level is related to the outlet, the second one concerns the loads connected to a single outlet. This algorithm,
together with the prediction processing of the logic unit connected to all the outlets, is suitable for alerting
management for cases of threshold overcoming. In this direction is proposed a flow chart applied on three
for three outlets and able to control load matching with defined thresholds. The goal of the paper is to
provide the reading keys of the data mining outputs useful for the energy management and diagnostic of the
electrical network in a building. Finally in the paper are analyzed the correlation between global active
power, global reactive power and energy absorption of loads of the three intelligent outlet. The prediction
and the correlation analyses provide information about load balancing, possible electrical faults and energy
cost optimization.
Active and reactive power sharing in micro grid using droop control IJECEIAES
The development of renewable energy contributes to the global objectives of reducing our greenhouse gas emissions, obtaining and increasing our energy efficiency. In the face of these changes, the electric-network must adapt, while maintaining a high level of reliability and a quality of energy production. To meet this objective, it is recommended to use highly developed electrical network by integrating renewable energy sources in order to adapt the energy consumption to their production, using electrotechnical software information and telecommunications technologies. We are talking about intelligent grids (Smart Grid). The main objective of the work presented in this paper is the contribution to the study of intelligent network for efficient management of energy produced by several sources linked to the AC bus via the voltage inverters. Numerical simulations have been presented to validate the performance of the proposed active and reactive power controller (Droop Control).
Implementation of a decentralized real-time management system for electrical ...journalBEEI
Intelligent management of the electrical network is the implementation of an integrated system based on a reliable and secure communication architecture for transmitting end-to-end information between the equipment and the management system. The main objective of this work is to develop an intelligent telecontrol solution for the electrical distribution network combining communication techniques and an intelligent reconfiguration strategy. The solution is based on a graphic model and a secure communication architecture using the internet of things to ensure flexibility in terms of management of the intelligent network. This intelligent multi-criteria solution uses a secure communication architecture and the MQTT protocol to ensure system interoperability and security. The tests were carried out on the IEEE 33 bus network and consequently, an optimization of the losses and a clear improvement in the nodal voltage were recorded despite the variation of the electric charge.
Defining Control Strategies for Micro Grids Islanded Operation with Maximum P...IAES-IJPEDS
This paper explains about an intelligent control method for the maximum
power point tracking (MPPT) of a photo voltaic system with different
temperature and insolation conditions. This method uses a fuzzy logic
controller applied to a DC-DC converter. The different steps of the design of
this controller are presented together with its simulation and the feasibility of
control methods to be adopted for the operation of a micro grid when it
becomes isolated. Normally, the micro grid operates in interconnected mode
with the medium voltage network; however, scheduled or forced isolation
can take place. In such conditions, the micro grid must have the ability to
operate stably and autonomously. An evaluation of the need of storage
devices and load to take off strategies is included in this paper. The MPPT of
a photovoltaic system for Micro Grid operaion using a Fuzzy logic control
scheme is successfully designed and simulated by using MATLAB/Simulink
Software.
Microgrid energy management system for smart home using multi-agent systemIJECEIAES
This paper proposes a multi-agent system for energy management in a microgrid for smart home applications, the microgrid comprises a photovoltaic source, battery energy storage, electrical loads, and an energy management system (EMS) based on smart agents. The microgrid can be connected to the grid or operating in island mode. All distributed sources are implemented using MATLAB/Simulink to simulate a dynamic model of each electrical component. The agent proposed can interact with each other to find the best strategy for energy management using the java agent development framework (JADE) simulator. Furthermore, the proposed agent framework is also validated through a different case study, the efficiency of the proposed approach to schedule local resources and energy management for microgrid is analyzed. The simulation results verify the efficacy of the proposed approach using Simulink/JADE co-simulation.
Micropower system optimization for the telecommunication towers based on var...IJECEIAES
This study investigates the technical and cost-effective performance of options renewable energy sources to develop a green off-grid telecommunication tower to replace diesel generators in Malaysia. For this purpose, the solar, wind, pico-hydro energy, along with diesel generators, were examined to compare. In addition, the modeling of hybrid powering systems was conducted using hybrid optimization model for energy (HOMER) simulation based on techno-economic analysis to determine the optimal economically feasible system. The optimization findings showed that the hybrid high-efficiency fixed photovoltaic (PV) system with battery followed by 2 kW pico-hydropower and battery are the optimal configurations for powering off-grid telecommunication towers in Malaysia with the lowest net present cost (NPC) and cost of energy (COE). These costs of NPC and COE are more down than diesel generator costs with battery by 17.45%, 16.45%, 15.9%, and 15.5%, respectively. Furthermore, the economic evaluation of the high-efficiency solar fixed PV panels system annual cash flow compared to the diesel generator with the battery system indicated a ten-year payback period.
INTELLIGENT ELECTRICAL MULTI OUTLETS CONTROLLED AND ACTIVATED BY A DATA MININ...ijscai
In the proposed paper are discussed results of an industry project concerning energy management in building. Specifically the work analyses the improvement of electrical outlets controlled and activated by a logic unit and a data mining engine. The engine executes a Long Short-Terms Memory (LSTM) neural network algorithm able to control, to activate and to disable electrical loads connected to multiple outlets placed into a building and having defined priorities. The priority rules are grouped into two level: the first level is related to the outlet, the second one concerns the loads connected to a single outlet. This algorithm, together with the prediction processing of the logic unit connected to all the outlets, is suitable for alerting management for cases of threshold overcoming. In this direction is proposed a flow chart applied on three for three outlets and able to control load matching with defined thresholds. The goal of the paper is to provide the reading keys of the data mining outputs useful for the energy management and diagnostic of the electrical network in a building. Finally in the paper are analyzed the correlation between global active power, global reactive power and energy absorption of loads of the three intelligent outlet. The prediction and the correlation analyses provide information about load balancing, possible electrical faults and energy cost optimization.
Intelligent Electrical Multi Outlets Controlled and Activated by a Data Minin...IJSCAI Journal
In the proposed paper are discussed results of an industry project concerning energy management in
building. Specifically the work analyses the improvement of electrical outlets controlled and activated by a
logic unit and a data mining engine. The engine executes a Long Short-Terms Memory (LSTM) neural
network algorithm able to control, to activate and to disable electrical loads connected to multiple outlets
placed into a building and having defined priorities. The priority rules are grouped into two level: the first
level is related to the outlet, the second one concerns the loads connected to a single outlet. This algorithm,
together with the prediction processing of the logic unit connected to all the outlets, is suitable for alerting
management for cases of threshold overcoming. In this direction is proposed a flow chart applied on three
for three outlets and able to control load matching with defined thresholds. The goal of the paper is to
provide the reading keys of the data mining outputs useful for the energy management and diagnostic of the
electrical network in a building. Finally in the paper are analyzed the correlation between global active
power, global reactive power and energy absorption of loads of the three intelligent outlet. The prediction
and the correlation analyses provide information about load balancing, possible electrical faults and energy
cost optimization.
Active and reactive power sharing in micro grid using droop control IJECEIAES
The development of renewable energy contributes to the global objectives of reducing our greenhouse gas emissions, obtaining and increasing our energy efficiency. In the face of these changes, the electric-network must adapt, while maintaining a high level of reliability and a quality of energy production. To meet this objective, it is recommended to use highly developed electrical network by integrating renewable energy sources in order to adapt the energy consumption to their production, using electrotechnical software information and telecommunications technologies. We are talking about intelligent grids (Smart Grid). The main objective of the work presented in this paper is the contribution to the study of intelligent network for efficient management of energy produced by several sources linked to the AC bus via the voltage inverters. Numerical simulations have been presented to validate the performance of the proposed active and reactive power controller (Droop Control).
Implementation of a decentralized real-time management system for electrical ...journalBEEI
Intelligent management of the electrical network is the implementation of an integrated system based on a reliable and secure communication architecture for transmitting end-to-end information between the equipment and the management system. The main objective of this work is to develop an intelligent telecontrol solution for the electrical distribution network combining communication techniques and an intelligent reconfiguration strategy. The solution is based on a graphic model and a secure communication architecture using the internet of things to ensure flexibility in terms of management of the intelligent network. This intelligent multi-criteria solution uses a secure communication architecture and the MQTT protocol to ensure system interoperability and security. The tests were carried out on the IEEE 33 bus network and consequently, an optimization of the losses and a clear improvement in the nodal voltage were recorded despite the variation of the electric charge.
Defining Control Strategies for Micro Grids Islanded Operation with Maximum P...IAES-IJPEDS
This paper explains about an intelligent control method for the maximum
power point tracking (MPPT) of a photo voltaic system with different
temperature and insolation conditions. This method uses a fuzzy logic
controller applied to a DC-DC converter. The different steps of the design of
this controller are presented together with its simulation and the feasibility of
control methods to be adopted for the operation of a micro grid when it
becomes isolated. Normally, the micro grid operates in interconnected mode
with the medium voltage network; however, scheduled or forced isolation
can take place. In such conditions, the micro grid must have the ability to
operate stably and autonomously. An evaluation of the need of storage
devices and load to take off strategies is included in this paper. The MPPT of
a photovoltaic system for Micro Grid operaion using a Fuzzy logic control
scheme is successfully designed and simulated by using MATLAB/Simulink
Software.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Power consumption and energy management for edge computing: state of the artTELKOMNIKA JOURNAL
Edge computing aims to make internet-based services and remote computing power close to the user by placing information technology (IT) infrastructure at the network edges. This proximity provides data centers with low-latency and context-aware services. Edge computing power consumption is mainly caused by data centers, network equipment, and user equipment. With edge computing (EC), energy management platforms for residential, industrial, and commercial sectors are built. Energy efficiency is considered to be one of the key aspects of edge power constraints. This paper provides the state of the art of power consumption and energy management for edge computing, the computation offloading methods, and more important highlights the power efficiency of edge computing systems. Furthermore, renewable energy and related concepts will also be explored and presented since no human participation is required in replacing or recharging batteries when using such energy sources. Based on such study, a recommendation is to develop a dynamic system for energy management in real-time with the assessment of local renewable energy so that the system be reliable with minimum power consumption. Also, regarding energy management, we recommend providing backup energy sources (or using more than one energy source) or (a hybrid technique).
Renewable energy allocation based on maximum flow modelling within a microgridIJECEIAES
This paper designs a microgrid-wide energy allocation mechanism on top of a network flow model from distributed generators to consumer entities. Basically, the flow graph consists of a set of nodes representing consumers or generators as well as a set of weighted links representing the amount of energy generation, consumer-side demand, and transmission cable capacity. The main idea lies in that a special node is added to account for the interaction with the main grid and that two-pass allocation is executed. In the first pass, the maximum flow solver decides the amount of the insufficiency, which must be supplemented by the main power network, usually with predefined cost. The second pass runs the flow solver again to fill the energy lack and calculates the surplus of renewable energy generation. The experiment result observes the stability in energy distribution over the microgrid while the amount of the total energy production can be accommodated by the maximum link capacity.
Study on the performance indicators for smart grids: a comprehensive reviewTELKOMNIKA JOURNAL
This paper presents a detailed review on performance indicators for smart grid (SG) such as voltage stability enhancement, reliability evaluation, vulnerability assessment, Supervisory Control and Data Acquisition (SCADA) and communication systems. Smart grids reliability assessment can be performed by analytically or by simulation. Analytical method utilizes the load point assessment techniques, whereas the simulation technique uses the Monte Carlo simulation (MCS) technique. The reliability index evaluations will consider the presence or absence of energy storage elements using the simulation technologies such as MCS, and the analytical methods such as systems average interruption frequency index (SAIFI), and other load point indices. This paper also presents the difference between SCADA and substation automation, and the fact that substation automation, though it uses the basic concepts of SCADA, is far more advanced in nature.
Fuzzy logic-based controller of the bidirectional direct current to direct cu...IJECEIAES
Microgrids are small-scale power networks that include renewable energy sources, load, energy storage systems, and energy management systems (EMS). Lithium-ion batteries are the most used battery for energy storage in microgrids due to their advantages over other types of batteries. However, to protect the battery from the explosion and to manage to charge and discharge based on state-of-charge (SoC) value, this type of battery requires the use of an energy management system. The main objective of this paper is to propose an intelligent control strategy for energy management in the microgrid to control the charge and discharge of Li-ion batteries to stabilize the system and reduce the cost of electricity due to the high cost of grid electricity. The proposed technique is based on a fuzzy logic controller (FLC) for voltage control. The FLC is based on the measured voltage of the direct current (DC) bus and the fixed reference voltage to generate buck/boost converter signal control. The proposed technique has been simulated and tested using MATLAB/Simulink software which illustrates the tracking of desired power and DC bus voltage regulation. The simulation results confirm that the proposed systems can diminish the deviations of the system's voltage.
To tackle the widespread challenges encountered during the management of power flow in electrical networks, the integration of smart grid (S.G)is proposed as a viable solution to address the environmental and economic concerns. In order to enhance overall functionality of the electric power delivery system, operation of the smart grid is governed by data-driven algorithms where various sensors and smart meters are used to collect this data. On other hand, the fluctuating cost of fossil fuels and its negative impact on the environment has incentivized the exploitation of renewable energies in the smart grid. In the present paper, a hybrid Photovoltaic/Wind (PV/Wind) is suggested to supply a smart grid. The objective of this study is to asses the feasibility of a smart grid supplied solely by renewable energy sources. Conceptual standings of this newly suggested model are validated by simulations.
Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.
Control for Grid Connected and Intentional Islanding of Distributed Power Gen...ijtsrd
As the demand for more reliable and secure power system with greater power quality increases, the concept of distributed generation DG have become more popular. This popularity of DG concept has developed simultaneously with the decrease in manufacturing costs associated with clean and alternative technologies like fuel cells, biomass, micro turbine and solar cell systems. Intentional islanding is the purposeful sectionalisation of the utility system during widespread disturbances to create power “islandâ€. This island can be designed to maintain a continuous supply of power during disturbances of the main distribution system. Ruchali Borkute | Nikita Malwar ""Control for Grid Connected and Intentional Islanding of Distributed Power Generation"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23679.pdf
Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/23679/control-for-grid-connected-and-intentional-islanding-of-distributed-power-generation/ruchali-borkute
ENERGY MANAGEMENT ALGORITHMS IN SMART GRIDS: STATE OF THE ART AND EMERGING TR...ijaia
The electric grid is radically evolving into the smart grid, which is characterized by improved energy
efficiency of available resources. The smart grid permits interactions among its computational and physical
elements thanks to the integration of Information and Communication Technologies (ICTs). ICTs provide
energy management algorithms and allow renewable energy integration and energy price minimization.
Given the importance of renewable energy, many researchers developed energy management (EM)
algorithms to minimize renewable energy intermittency. EM plays an important role in the control of users'
energy consumption and enables increased consumer participation in the market. These algorithms provide
consumers with information about their energy consumption patterns and help them adopt energy-efficient
behaviour. In this paper, we present a review of the state of the energy management algorithms. We define
a set of requirements for EM algorithms and evaluate them qualitatively. We also discuss emerging tools
and trends in this area.
Implementation of modular MPPT algorithm for energy harvesting embedded and I...IJECEIAES
The establishment of the latest IoT systems available today such as smart cities, smart buildings, and smart homes and wireless sensor networks (WSNs) are let the main design restriction on the inadequate supply of battery power. Hence proposing a solar-based photovoltaic (PV) system which is designed DC-DC buck-boost converter with an improved modular maximum power point tracking (MPPT) algorithm. The output voltage depends on the inductor, capacitor values, metal oxide semiconductor field effect transistor (MOSFET) switching frequency, and duty cycle. This paper focuses on the design and simulation of min ripple current/voltage and improved efficiency at PV array output, to store DC power. The stored DC power will be used for smart IoT systems. From the simulation results, the current ripples are observed to be minimized from 0.062 A to 0.02 A maintaining the duty cycle at 61.09 for switching frequencies ranges from 300 kHz to 10 MHz at the input voltage 48 V and the output voltage in buck mode 24 V, boost mode 100 V by maintaining constant 99.7 efficiencies. The improvised approach is compared to various existed techniques. It is noticed that the results are more useful for the self-powered Embedded & Internet of Things systems.
This article presents the system design and prediction performance of a 1kW capacity grid-tied photovoltaic inverter applicable for low or medium-voltage electrical distri-bution networks. System parameters, for instance, the longitude and latitude of the solar plant location, panel orientation, tilt and azimuth angle calculation, feasibility testing, optimal sizing of installment are analyzed in the model and the utility is sim-ulated precisely to construct an efficient solar power plant for residential applications. In this paper, meteorological data are computed to discuss the impact of environmen-tal variables. As regards ensuring reliability and sustenance, a simulation model of the system of interest is tested in the PVsyst software package. Simulation results yield that the optimum energy injected to the national grid from the solar plant, specific pro-duction, and performance ratio are 1676kWh/year, 1552kWh/kWp/year, and 79.29% respectively. Moreover, the predicted carbon footprint reduction is 23.467 tons during the 30 years lifetime of the system. Therefore, the performance assessments affirm the effectiveness of the proposed research.
A review of optimal operation of microgrids IJECEIAES
The term microgrid refers to small-scale power grid that can operate autonomously or in concurrence with the area’s main electrical grid. The intermittent characteristic of DGs which defies the power quality and voltage manifests the requirement for new planning and operation approaches for microgrids. Consequently, conventional optimization methods in new power systems have been critically biased all through the previous decade. One of the main technological and inexpensive tools in this regard is the optimal generation scheduling of microgrid. As a primary optimization tool in the planning and operation fields, optimal operation has an undeniable part in the power system. This paper reviews and evaluates the optimal operation approaches mostly related to microgrids. In this work, the foremost optimal generation scheduling approaches are compared in terms of their objective functions, techniques and constraints. To conclude, a few fundamental challenges occurring from the latest optimal generation scheduling techniques in microgrids are addressed.
A NOVEL CONTROL STRATEGY FOR POWER QUALITY IMPROVEMENT USING ANN TECHNIQUE FO...IJERD Editor
The proposed system presents power-control strategies of a Micro grid-connected hybrid generation
system with versatile power transfer. This hybrid system allows maximum utilization of freely available
renewable energy sources like wind and photovoltaic energies. For this, an adaptive MPPT algorithm along with
standard perturbs and observes method will be used for the system.
The inverter converts the DC output from non-conventional energy into useful AC power for the
connected load. This hybrid system operates under normal conditions which include normal room temperature
in the case of solar energy and normal wind speed at plain area in the case of wind energy. However, designing
an optimal micro grid is not an easy task, due to the fact that primary energy carriers are changeable and
uncontrollable, as is the demand. Traditional design and optimization tools, developed for controlled power
sources, cannot be employed here. Simulation methods seem to be the best solution.
The dynamic model of the proposed system is first elaborated in the stationary reference frame and
then transformed into the synchronous orthogonal reference frame. The transformed variables are used in
control of the voltage source converter as the heart of the interfacing system between DG resources and utility
grid. By setting an appropriate compensation current references from the sensed load currents in control circuit
loop of DG, the active, reactive, and harmonic load current components will be compensated with fast dynamic
response, thereby achieving sinusoidal grid currents in phase with load voltages, while required power of the
load is more than the maximum injected power of the DG to the grid. In addition, the proposed control method
of this paper does not need a phase-locked loop in control circuit and has fast dynamic response in providing
active and reactive power components of the grid-connected loads.
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.
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Power consumption and energy management for edge computing: state of the artTELKOMNIKA JOURNAL
Edge computing aims to make internet-based services and remote computing power close to the user by placing information technology (IT) infrastructure at the network edges. This proximity provides data centers with low-latency and context-aware services. Edge computing power consumption is mainly caused by data centers, network equipment, and user equipment. With edge computing (EC), energy management platforms for residential, industrial, and commercial sectors are built. Energy efficiency is considered to be one of the key aspects of edge power constraints. This paper provides the state of the art of power consumption and energy management for edge computing, the computation offloading methods, and more important highlights the power efficiency of edge computing systems. Furthermore, renewable energy and related concepts will also be explored and presented since no human participation is required in replacing or recharging batteries when using such energy sources. Based on such study, a recommendation is to develop a dynamic system for energy management in real-time with the assessment of local renewable energy so that the system be reliable with minimum power consumption. Also, regarding energy management, we recommend providing backup energy sources (or using more than one energy source) or (a hybrid technique).
Renewable energy allocation based on maximum flow modelling within a microgridIJECEIAES
This paper designs a microgrid-wide energy allocation mechanism on top of a network flow model from distributed generators to consumer entities. Basically, the flow graph consists of a set of nodes representing consumers or generators as well as a set of weighted links representing the amount of energy generation, consumer-side demand, and transmission cable capacity. The main idea lies in that a special node is added to account for the interaction with the main grid and that two-pass allocation is executed. In the first pass, the maximum flow solver decides the amount of the insufficiency, which must be supplemented by the main power network, usually with predefined cost. The second pass runs the flow solver again to fill the energy lack and calculates the surplus of renewable energy generation. The experiment result observes the stability in energy distribution over the microgrid while the amount of the total energy production can be accommodated by the maximum link capacity.
Study on the performance indicators for smart grids: a comprehensive reviewTELKOMNIKA JOURNAL
This paper presents a detailed review on performance indicators for smart grid (SG) such as voltage stability enhancement, reliability evaluation, vulnerability assessment, Supervisory Control and Data Acquisition (SCADA) and communication systems. Smart grids reliability assessment can be performed by analytically or by simulation. Analytical method utilizes the load point assessment techniques, whereas the simulation technique uses the Monte Carlo simulation (MCS) technique. The reliability index evaluations will consider the presence or absence of energy storage elements using the simulation technologies such as MCS, and the analytical methods such as systems average interruption frequency index (SAIFI), and other load point indices. This paper also presents the difference between SCADA and substation automation, and the fact that substation automation, though it uses the basic concepts of SCADA, is far more advanced in nature.
Fuzzy logic-based controller of the bidirectional direct current to direct cu...IJECEIAES
Microgrids are small-scale power networks that include renewable energy sources, load, energy storage systems, and energy management systems (EMS). Lithium-ion batteries are the most used battery for energy storage in microgrids due to their advantages over other types of batteries. However, to protect the battery from the explosion and to manage to charge and discharge based on state-of-charge (SoC) value, this type of battery requires the use of an energy management system. The main objective of this paper is to propose an intelligent control strategy for energy management in the microgrid to control the charge and discharge of Li-ion batteries to stabilize the system and reduce the cost of electricity due to the high cost of grid electricity. The proposed technique is based on a fuzzy logic controller (FLC) for voltage control. The FLC is based on the measured voltage of the direct current (DC) bus and the fixed reference voltage to generate buck/boost converter signal control. The proposed technique has been simulated and tested using MATLAB/Simulink software which illustrates the tracking of desired power and DC bus voltage regulation. The simulation results confirm that the proposed systems can diminish the deviations of the system's voltage.
To tackle the widespread challenges encountered during the management of power flow in electrical networks, the integration of smart grid (S.G)is proposed as a viable solution to address the environmental and economic concerns. In order to enhance overall functionality of the electric power delivery system, operation of the smart grid is governed by data-driven algorithms where various sensors and smart meters are used to collect this data. On other hand, the fluctuating cost of fossil fuels and its negative impact on the environment has incentivized the exploitation of renewable energies in the smart grid. In the present paper, a hybrid Photovoltaic/Wind (PV/Wind) is suggested to supply a smart grid. The objective of this study is to asses the feasibility of a smart grid supplied solely by renewable energy sources. Conceptual standings of this newly suggested model are validated by simulations.
Among the most widespread renewable energy sources is solar energy; Solar panels offer a green, clean, and environmentally friendly source of energy. In the presence of several advantages of the use of photovoltaic systems, the random operation of the photovoltaic generator presents a great challenge, in the presence of a critical load. Among the most used solutions to overcome this problem is the combination of solar panels with generators or with the public grid or both. In this paper, an energy management strategy is proposed with a safety aspect by using artificial neural networks (ANNs), in order to ensure a continuous supply of electricity to consumers with a maximum solicitation of renewable energy.
Control for Grid Connected and Intentional Islanding of Distributed Power Gen...ijtsrd
As the demand for more reliable and secure power system with greater power quality increases, the concept of distributed generation DG have become more popular. This popularity of DG concept has developed simultaneously with the decrease in manufacturing costs associated with clean and alternative technologies like fuel cells, biomass, micro turbine and solar cell systems. Intentional islanding is the purposeful sectionalisation of the utility system during widespread disturbances to create power “islandâ€. This island can be designed to maintain a continuous supply of power during disturbances of the main distribution system. Ruchali Borkute | Nikita Malwar ""Control for Grid Connected and Intentional Islanding of Distributed Power Generation"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23679.pdf
Paper URL: https://www.ijtsrd.com/engineering/electrical-engineering/23679/control-for-grid-connected-and-intentional-islanding-of-distributed-power-generation/ruchali-borkute
ENERGY MANAGEMENT ALGORITHMS IN SMART GRIDS: STATE OF THE ART AND EMERGING TR...ijaia
The electric grid is radically evolving into the smart grid, which is characterized by improved energy
efficiency of available resources. The smart grid permits interactions among its computational and physical
elements thanks to the integration of Information and Communication Technologies (ICTs). ICTs provide
energy management algorithms and allow renewable energy integration and energy price minimization.
Given the importance of renewable energy, many researchers developed energy management (EM)
algorithms to minimize renewable energy intermittency. EM plays an important role in the control of users'
energy consumption and enables increased consumer participation in the market. These algorithms provide
consumers with information about their energy consumption patterns and help them adopt energy-efficient
behaviour. In this paper, we present a review of the state of the energy management algorithms. We define
a set of requirements for EM algorithms and evaluate them qualitatively. We also discuss emerging tools
and trends in this area.
Implementation of modular MPPT algorithm for energy harvesting embedded and I...IJECEIAES
The establishment of the latest IoT systems available today such as smart cities, smart buildings, and smart homes and wireless sensor networks (WSNs) are let the main design restriction on the inadequate supply of battery power. Hence proposing a solar-based photovoltaic (PV) system which is designed DC-DC buck-boost converter with an improved modular maximum power point tracking (MPPT) algorithm. The output voltage depends on the inductor, capacitor values, metal oxide semiconductor field effect transistor (MOSFET) switching frequency, and duty cycle. This paper focuses on the design and simulation of min ripple current/voltage and improved efficiency at PV array output, to store DC power. The stored DC power will be used for smart IoT systems. From the simulation results, the current ripples are observed to be minimized from 0.062 A to 0.02 A maintaining the duty cycle at 61.09 for switching frequencies ranges from 300 kHz to 10 MHz at the input voltage 48 V and the output voltage in buck mode 24 V, boost mode 100 V by maintaining constant 99.7 efficiencies. The improvised approach is compared to various existed techniques. It is noticed that the results are more useful for the self-powered Embedded & Internet of Things systems.
This article presents the system design and prediction performance of a 1kW capacity grid-tied photovoltaic inverter applicable for low or medium-voltage electrical distri-bution networks. System parameters, for instance, the longitude and latitude of the solar plant location, panel orientation, tilt and azimuth angle calculation, feasibility testing, optimal sizing of installment are analyzed in the model and the utility is sim-ulated precisely to construct an efficient solar power plant for residential applications. In this paper, meteorological data are computed to discuss the impact of environmen-tal variables. As regards ensuring reliability and sustenance, a simulation model of the system of interest is tested in the PVsyst software package. Simulation results yield that the optimum energy injected to the national grid from the solar plant, specific pro-duction, and performance ratio are 1676kWh/year, 1552kWh/kWp/year, and 79.29% respectively. Moreover, the predicted carbon footprint reduction is 23.467 tons during the 30 years lifetime of the system. Therefore, the performance assessments affirm the effectiveness of the proposed research.
A review of optimal operation of microgrids IJECEIAES
The term microgrid refers to small-scale power grid that can operate autonomously or in concurrence with the area’s main electrical grid. The intermittent characteristic of DGs which defies the power quality and voltage manifests the requirement for new planning and operation approaches for microgrids. Consequently, conventional optimization methods in new power systems have been critically biased all through the previous decade. One of the main technological and inexpensive tools in this regard is the optimal generation scheduling of microgrid. As a primary optimization tool in the planning and operation fields, optimal operation has an undeniable part in the power system. This paper reviews and evaluates the optimal operation approaches mostly related to microgrids. In this work, the foremost optimal generation scheduling approaches are compared in terms of their objective functions, techniques and constraints. To conclude, a few fundamental challenges occurring from the latest optimal generation scheduling techniques in microgrids are addressed.
A NOVEL CONTROL STRATEGY FOR POWER QUALITY IMPROVEMENT USING ANN TECHNIQUE FO...IJERD Editor
The proposed system presents power-control strategies of a Micro grid-connected hybrid generation
system with versatile power transfer. This hybrid system allows maximum utilization of freely available
renewable energy sources like wind and photovoltaic energies. For this, an adaptive MPPT algorithm along with
standard perturbs and observes method will be used for the system.
The inverter converts the DC output from non-conventional energy into useful AC power for the
connected load. This hybrid system operates under normal conditions which include normal room temperature
in the case of solar energy and normal wind speed at plain area in the case of wind energy. However, designing
an optimal micro grid is not an easy task, due to the fact that primary energy carriers are changeable and
uncontrollable, as is the demand. Traditional design and optimization tools, developed for controlled power
sources, cannot be employed here. Simulation methods seem to be the best solution.
The dynamic model of the proposed system is first elaborated in the stationary reference frame and
then transformed into the synchronous orthogonal reference frame. The transformed variables are used in
control of the voltage source converter as the heart of the interfacing system between DG resources and utility
grid. By setting an appropriate compensation current references from the sensed load currents in control circuit
loop of DG, the active, reactive, and harmonic load current components will be compensated with fast dynamic
response, thereby achieving sinusoidal grid currents in phase with load voltages, while required power of the
load is more than the maximum injected power of the DG to the grid. In addition, the proposed control method
of this paper does not need a phase-locked loop in control circuit and has fast dynamic response in providing
active and reactive power components of the grid-connected loads.
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%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
About
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
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Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
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Development of methods for managing energy consumption and energy efficiency in a common system
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 13, No. 2, April 2023, pp. 1306~1313
ISSN: 2088-8708, DOI: 10.11591/ijece.v13i2.pp1306-1313 1306
Journal homepage: http://ijece.iaescore.com
Development of methods for managing energy consumption and
energy efficiency in a common system
Nigar R. Aslanova1
, Esmira J. Abdullayeva2
, Aleksandr V. Beloglazov3
1
Department of Economics and Business Management, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan
2
Department of Social Development Economics and Evaluation, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan
3
Electrical Engineering Faculty, Tomsk Polytechnical University, Tomsk, Russian Federation
Article Info ABSTRACT
Article history:
Received Jan 24, 2022
Revised Oct 11, 2022
Accepted Oct 31, 2022
The work aims to analyze and examine renewable energy sources (RES)
to develop interconnected energy efficiency and energy consumption
management system by integrating the software-defined machine-to-
machine (M2M) communication. The article’s objectives include analysis of
using RES as alternative raw materials for electricity production, the study
of intelligent technologies for integrating RES into monitoring and control
systems, research of devices and methods for monitoring energy production
and consumption, analysis of sensor application for automation of control
systems in the energy sector, a study of data transmission and information
processing rates. The study results showed that the data transfer rate was
delayed by 6 seconds to process 1,000 MB of information. It has been
proven that wind energy can be used most efficiently within a 12-hour daily
cycle, in contrast to tidal energy and solar energy. It is shown that due to the
cyclical nature of obtaining energy from renewable sources, they do not
fully provide energy to a large city, on the basis of which it is necessary to
additionally use other energy sources. Three different types of power
generation facilities were examined and compared. Wind farms were found
to have the highest potential for electricity generation, amounting to
1,600-1,700 kW.
Keywords:
Data center
Energy sector
Intelligent energy management
Machine-to-machine
communication
Technology integration
This is an open access article under the CC BY-SA license.
Corresponding Author:
Esmira J. Abdullayeva
Department of Social Development Economics and Evaluation, Azerbaijan State University of Economics
Instyglaliyat Str., 6, Baku AZ 1123, Azerbaijan
Email: esm_abdullayeva@rambler.ru
1. INTRODUCTION
Today the energy sector is a crucial element in the functioning and prosperity of economics in many
countries worldwide, with new prospects for a gradual transition from existing traditional to alternative
energy generation methods, particularly renewable energy sources (RES) [1], [2]. Successful implementation
of intelligent energy management (IEM) involves real-time information about the load profile, power supply,
and system operating conditions [3], [4]. However, the communication network needed for IEM is very
different from conventional human-centric telecommunications networks. This type of communication is
characterized by the omnipresent exchange of information between many intelligent machines like sensors,
actuators, intelligent electronic devices (IEDs), excluding the human factor. This resulted in the introduction
of machine-to-machine (M2M) communication technology [5], [6].
Cellular technology is a major driver of M2M due to the pervasive presence of cellular
infrastructure and the availability of high-speed access. The 3rd generation partnership project (3GPP) has
defined several methods to support M2M communication in modern long-term evolution-advanced
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(LTE-advanced) systems [7]. M2M devices may co-exist with human communications on the same network
and use a random-access channel to establish connections to centralized base stations. As a result, M2M
communication, with its self-organization, self-adjustment, and self-healing skills, should be a critical factor
in the reliable functioning of intelligent energy management.
The application-specific method requires full customization of M2M platforms for a specific
application scenario, which does not allow to adapt to a rapidly evolving demand. Managing a large number
of M2M devices is highly inefficient due to the increasing complexity of the system and the significant
heterogeneity of equipment, interconnections, and deployment scenarios. Second, the close interconnectivity
between applications and task-based hardware makes reusing existing M2M physical infrastructure for new
applications impossible. Different or even the same application by different operators require redundant
equipment, resulting in excessive capital and operating costs. Finally, power grid applications have various
quality of service (QoS) requirements regarding latency, packet size, bandwidth, and packet arrival rates. The
co-existence of protection, control, monitoring, and billing traffic in a single communication network creates
new challenges for effective resource allocation in M2M communications [8]. Network design, deployment,
management, and maintenance can be easily implemented on one central controller based on an open
standard rather than directly setting up many heterogeneous devices [9].
This study investigates the SDN-M2M switching relationship and explores the potential for
intelligent control using RES. This work aims to analyze and examine RES in developing a methodology for
energy efficiency and energy consumption management in the overall control system by integrating
software-defined M2M technology. The scientific novelty implies a rational application of RES in the energy
sector through the conversion of energy by wind turbines, solar panels, and hydropower plants based on
software inter-machine communication.
2. METHOD
This study analyzes the use of RES in grid-connected intelligent energy management systems using
software-defined M2M communication. The work investigates the operation of wind farms with sensors for
power generation and monitoring information with rational power distribution; solar panels with irradiation
sensors, solar panel temperature, and surge sensors; hydro power plant (HPP) for power generation with
special monitoring systems and power supply to the plant. The RES considered in this study is wind, solar,
and water.
2.1. Wind power plant
The wind power plant (WPP) is a complex of related equipment and facilities designed to convert
wind flows into energy to produce other types of energy like electricity and mechanical power. The
conversion of wind streams into electrical energy is due to the electric generator, which is contained in the
plant’s construction. A scheme to monitor wind power production is presented in Figure 1.
Figure 1. WPP with wind turbines and communication systems
It comprises three major components: sensors, low-power wide-area network (LPWAN) gateway,
data pathway, database, and visualization solution. Sensors are installed on or around generators that measure
voltage, current, phase, and other necessary parameters for electricity generation. Sensors can also measure
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and monitor infrastructure parameters such as temperature, vibration, and environmental parameters such as
wind speed, humidity, and lighting conditions [10], [11].
2.2. Solar panels and solar energy
A solar panel is a set of photovoltaic converters in the form of semiconductor devices that convert
solar energy into direct electric power. Figure 2 shows a system for monitoring electricity generation through
solar panels and parameter sensors. A low-cost Arduino voltage sensor module with voltage splitters can be
used to measure the output voltage. This module is based on the principle of resistance point pressure, and it
can make the input voltage of the red terminal decrease by a factor of 5 from the original voltage [12], [13].
Figure 2. Sensor-based solar panel control system
2.3. Tidal power plant
Tidal energy is a type of hydroelectric production that uses water as a raw material to generate
electrical energy converted by tidal motion using tidal generators. There are several ways of producing
energy, one of which is through tidal generators or energy converters (TECs). Tidal generators use kinetic
energy from tidal water movement to turbines [14]–[16]. Figure 3 shows HPP with tidal power generation.
Figure 4 shows the way to supply generated hydroelectric power to a small city through HPP through a
special wire transmitter. HPP with tidal hydropower can generate more than 2 MW of electricity.
Figure 3. HPP with tidal power generation
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Figure 4. Power supply to the city by HPPs
2.4. Intelligent energy management with SDN-M2M technology
IEM combines defined machine learning programs to allocate resources in fine granularity and
ensure QoS. Figure 5 shows the SD-M2M architecture comprising such layers as energy sources and control,
application, transmission, management, and administration of information. The data layer represents the
presence of programmable field equipment and network elements involved in M2M communication (sensors,
actuators, smart meters, gateways, switches, routers). They are needed to support autonomous data collection
and transmission with IEM.
The application layer includes IEM application networks (domestic energy management, corporate
energy management, building energy management, micro-grid energy management, electric vehicle energy
management). Using standard application programming interfaces (APIs) between the control layer and the
applications, intelligent energy management applications can communicate the requirements to the
appropriate controllers through the north-facing interface [17]–[19]. IEM using RES is an interconnected set
of equipment, devices, and data carriers to monitor and control energy supply systems and energy
consumption.
Figure 5. SDN-M2M architecture
Figure 6 shows different RES (hydropower, wind turbines, solar panels) data control sensors to
transfer information to DC for further monitoring and control of the equipment. The points in Figure 6 are the
nodes of energy distribution. The electrical substation in Figure 6 is designed to receive, convert, and
distribute electricity with the help of control devices and switchgear. The conversion sub-station serves to
convert the current type and its frequencies.
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Figure 6. Renewable energy complex with data transmission and processing
3. RESULTS AND DISCUSSION
The results of transmitting the signal from the equipment are given in Figure 7. Thus, the data
transmission rate may slow because of the increase in the amount of information over time. The delay in the
transmission rate is because multiple calculation processes are executed simultaneously. The transmission of
data from wind turbines and HPPs, together with the calculation of the joint flow of solar panels, can lead to
a non-significant delay. In addition, natural factors, such as meteorological conditions and sufficiently low
temperatures below 20-25 ℃. The data center information technology determines the node where the power
generated by the plants is measured. It enables the distribution of electricity consumption based on the energy
produced by the power plants.
The rate of data processing in Figure 7 depends on the speed of data transmission through sensors.
They record actual production records of renewable energy equipment and, for their purposes, can monitor
the equipment’s operating status in the event of a malfunction. Figure 7 shows that the data rate is of the
order of 0.1 with data processing from 100 to 1,000 MB, indicating a good performance of information
technology (IT) equipment in DCs. M2M devices serve as phase measurement units integrated into
production and transmission equipment to continuously collect critical grid data such as voltage, current,
harmonics, and frequency. Using excel, we calculated equation that describes correlation between time of
data transmission and their capacity:
𝑇𝑖𝑚𝑒 = 0.0006 × 𝑆𝑖𝑧𝑒 + 0.0995; 𝑅2
= 0.9657 (1)
By incorporating RES and SDN-M2M technology, it is possible to calculate the average daily
production capacity at service stations of RES plants over 12 hours, as shown in Figure 8. The average daily
generation volume of WPPs is more efficient than solar panels and HPPs. The lowest power volume is
350-400 for HPPs for 3 hours due to low tidal activity. Solar panels have the lowest rate after 9 hours, where
the volume decreases from 1,300 to 500 kWh, while the power output of WPPs falls from 1,500 to 850 kWh
at the same time.
Data in Figure 8 allow concluding that the generation of energy from RES is insufficient for
electricity supply in a large city. Furthermore, it is characterized by unforeseen circumstances during the
operation of power plants, decreasing the overall efficiency. To increase energy efficiency and ensure
electricity consumption by consumers, the complex energy produced during the day must be distributed.
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Figure 7. Dependencies of data transmission and processing rates from metering devices to DC
Figure 8. Average daily generation volumes of electricity from RES
This study considers the possible integration of RES into a software-defined M2M communication
system and compares it with existing monitoring, control, and management techniques to identify the current
shortcomings. M2M communication is one of the most active methods for managing power quality with
sufficient equipment safety. It also enables the collection and processing of data at a distance, excluding
human factors. At the same time, it is necessary to analyze the impact of information technology and the
functioning of DCs operating using RES on the environmental situation.
Machine learning and artificial intelligence technologies are of equal importance. They may
anticipate the potential to generate renewable energy through workload planning and implementation to
improve alternative energy use energy efficiency. One such example is a scheduler called “GreenSlot” in
Goiri et al. [20]. It is designed to forecast solar energy production as closely as possible, followed by DC
workload planning to maximize the use of RES while meeting deadlines. This programming approach allows
the DC to consume much more renewable energy by reducing the cost of conventional energy.
Uihlein and Magagna [21], statistical methods or physical models performed wave forecasting for
tidal energy. Statistical approaches involve the application of neural networks and regression methods with
genetic programming. They are represented, for example, by the wave forecasting systems based on physical
models and the weighted average mark (WAM) wave model included in the integrated forecasting system
(IFS) of the European centre for medium-range weather forecasts (ECMWF) [21], where forecasts can be a
maximum of 48 hours ahead.
The integration of RES with DCs is now widely used in practice. Many IT companies have already
built and transitioned to new DC that can operate partly or fully with renewables. One such company is
Apple, which has created a 40 MW solar network for its data center in North Carolina to provide extra energy
[22]–[28].
We summarized our results in 4 findings: i) we have determined that with an increase in the amount
of data transferred, an increase in the duration of their transfer occurs. On average, an increase in the amount
of data by 1 MB leads to an increase in processing time by 0.0006 seconds; ii) an increase in the amount of
simultaneously processed data does not lead to an increase in the processing time; iii) we estimated the
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change in the amount of energy received from wind, solar and tidal energy. It has been established that wind
energy can be used most efficiently within a 12-hour daily cycle, in contrast to tidal energy and solar energy;
and iv) it is shown that due to the cyclical nature of obtaining energy from renewable sources, they do not
fully provide energy to a large city.
4. CONCLUSION
This study analyzes the use of renewables in three ways with the possibility of combining
alternative energy generation methods into a grid-connected system. By integrating RES with the
software-defined communication technologies, a relationship was established between electricity generation
and subsequent transmission of information to DCs. It allows monitoring the electricity generation volumes,
which depend on the data transmission and processing rates from the sensor equipment to remote servers to
display necessary distribution parameters for power supply to the end consumers. The study results showed
that the data transmission speed has a delay of 0.6 seconds for processing information of 1,000 MB. Data
processing rate depends on the speed of data transmission received from the equipment’s sensors when the
speed indicator does not exceed 2 seconds.
The study of three different power plants revealed that wind farms provide the most significant
potential for generating electricity up to 1,600-1,700 kW. The need to combine plant complexes for more
rational electricity use by consumers has been established. Each type of power plant has disadvantages, and
thus, they are highly dependent on favorable conditions for the normal operation of the equipment. That is,
solar panels require sunny weather, wind streams are critical for WPPs, tides and water flows specify the
functioning of HPPs.
ACKNOWLEDGEMENTS
The authors received no financial support for the research, authorship, and/or publication of this
article. The authors declared no potential conflicts of interest with respect to the research, authorship, and/or
publication of this article.
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BIOGRAPHIES OF AUTHORS
Nigar R. Aslanova received the Ph.D. degree from Azerbaijan State University of
Economics (UNEC), Azerbaijan. Currently, she is Senior Lecturer at the Department of
Economics and Business Management of Azerbaijan State University of Economics (UNEC)
in Baku, Azerbaijan. Her research interests include managing energy consumption and energy
efficiency and managing methodology. She can be contacted at ng_aslanova301@rambler.ru.
Esmira J. Abdullayeva holds a Ph.D. from Azerbaijan State University of
Economics (UNEC), Azerbaijan. She is currently Senior Teacher at the Department of Social
Development Economics and Evaluation of Azerbaijan State University of Economics
(UNEC) in Baku, Azerbaijan. Esmira is an expert in energy sources, their integration into
grid-connected system, energy efficiency and consumption. She can be contacted at email:
esm_abdullayeva@rambler.ru.
Aleksandr V. Beloglazov is currently a high-regarded Power Engineer and
graduate of Tomsk Polytechnical University, Russian Federation. His research areas include
power energy source, renewable energy, sustainable development, energy efficiency. He can
be contacted at email: alksbeloglazov@rambler.ru.