This document summarizes a thesis on implementing an optimized smart home energy management system using IoT applications and the PSO optimization algorithm. It describes a smart plug that monitors and controls appliances remotely, a Raspberry Pi-based energy management controller (EMC) that schedules appliances using MQTT, and a mobile app for remote monitoring and control. Experimental results found that using PSO to schedule appliances based on time-of-use pricing achieved a 24.31% reduction in energy costs compared to other methods. The conclusions discuss using smart plugs and the EMC to accurately read appliance consumption data and schedule appliances optimally via MQTT to reduce user costs.
Energy scavenging using vibrations from bluetooth controlled DC motorTELKOMNIKA JOURNAL
Wide spectrum of research for application-based solutions has grown due to the requirement of automation of general electrical appliances. A low-cost solution is presented in this paper to control DC motor using Bluetooth module and controlled by an ARM processor. The main objective here is to build an efficient closed loop system which is wirelessly controlled by ARM processor 2103 using Bluetooth module and Bluetooth dongle. The system suggested here is expandable and can be integrated with latest technologies as well. The paper gives the details of the prototype for home automation system and gives the expected results with 0.1% tolerance. It also suggests the ways to integrate this system with the mobile phones and hence control the devices with the mobile handsets. The vibration frequency of the DC motor is used to generate electrical potential using MEMS tecnonlogy. A novel idea of self powered DC motor is thus presented by installing MEMS based energy harvester on the motor shaft.
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Increasing cost and demand for energy is imposing us to find smart ways to save energy. To satisfy the energy requirement and at the same time to cut down the cost, consumption of energy must be monitored and controlled. Energy consumption can be well managed with the capabilities of the Internet of Things (IoT). This paper presents an architecture towards IoT-enabled Green campus Energy Management System. In the proposed system, the data acquisition module collects energy consumption information from each device and transmits it to the cloud platform for further processing and analysis. Since lighting and air conditioning appliances contribute to most of the electricity consumption in the campus environment, they have been taken as a prototype to validate the proposed architecture.
Energy scavenging using vibrations from bluetooth controlled DC motorTELKOMNIKA JOURNAL
Wide spectrum of research for application-based solutions has grown due to the requirement of automation of general electrical appliances. A low-cost solution is presented in this paper to control DC motor using Bluetooth module and controlled by an ARM processor. The main objective here is to build an efficient closed loop system which is wirelessly controlled by ARM processor 2103 using Bluetooth module and Bluetooth dongle. The system suggested here is expandable and can be integrated with latest technologies as well. The paper gives the details of the prototype for home automation system and gives the expected results with 0.1% tolerance. It also suggests the ways to integrate this system with the mobile phones and hence control the devices with the mobile handsets. The vibration frequency of the DC motor is used to generate electrical potential using MEMS tecnonlogy. A novel idea of self powered DC motor is thus presented by installing MEMS based energy harvester on the motor shaft.
IOT-ENABLED GREEN CAMPUS ENERGY MANAGEMENT SYSTEM ijesajournal
Increasing cost and demand for energy is imposing us to find smart ways to save energy. To satisfy the energy requirement and at the same time to cut down the cost, consumption of energy must be monitored and controlled. Energy consumption can be well managed with the capabilities of the Internet of Things (IoT). This paper presents an architecture towards IoT-enabled Green campus Energy Management System. In the proposed system, the data acquisition module collects energy consumption information from each device and transmits it to the cloud platform for further processing and analysis. Since lighting and air conditioning appliances contribute to most of the electricity consumption in the campus environment, they have been taken as a prototype to validate the proposed architecture.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
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ABSTRACT: A tap changer control operates to connect appropriate tap position of winding in power transformers to maintain correct voltage level in the power transmission and distribution system. Automatic tap changing can be implemented by using µC. This improved tap-changing decision and operational flexibility of this new technique make it attractive for deployment in practical power system network. This paper deals with the implementation of µC based tap changer control practically, using special purpose digital hardware as a built-in semiconductor chip or software simulation in conventional computers. Two strategies are suggested for its implementation as a software module in the paper. One is to integrate it with the supervisory system in a substation control room operating in a LAN environment. In this configuration, the parallel transformers can be controlled locally. The other is to integrate it into the SCADA (Supervisory Control and Data Acquisition) system, which allows the transformers to be monitored and controlled remotely over a wide area of power-network. The implementation of µC based tap changer control needs interfacing between the power system and the control circuitry. µC s may need to interact with people for the purpose of configuration, alarm reporting or everyday control.
A human-machine interface (HMI) is employed for this purpose. An HMI is usually linked to the SCADA system’s databases and software programs, to provide trending, diagnostic data, and management information such as scheduled maintenance procedures, logistic information, detailed schematics for a particular sensor or machine, and expert-system troubleshooting guides.
OBJECTIVES: The original system can afford the following features:
- Complete information about the plant (circuit breakers status, source of feeding, and level of the consumed power).
- Information about the operating values of the voltage, operating values of the transformers, operating values of the medium voltage, load feeders, operating values of the generators. These values will assist in getting any action to return the plant to its normal operation by minimum costs.
- Information about the quality of the system (harmonics, current, voltages, power factors, flickers, etc.). These values will be very essential in case of future correction.
- Recorded information such case voltage spikes, reducing the voltage on the medium or current interruption.
- implementation of µC based tap changer control practically, using special purpose digital hardware as a built-in semiconductor chip or software simulation in conventional computers.
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a smart meter electronically measures how much energy is being used and how much it costs, and then communicates it to the energy supplier and the customer. Smart meters can also enable the provision of new services to consumers as it can record consumption of electric energy in intervals of an hour or less, and also gather data for remote reporting using two-way communication between the meter and central system.
This slide is an introductory part of the course Computer Application in Power system. it will describe the basic tasks of a computer and different computer application areas.
Peak load scheduling in smart grid using cloud computingjournalBEEI
In this paper present peak, energy management attainable is feasible by monitoring real-time readings of whole loads within the college premises victimization this schedule loads so energy saving is possible. Currently, cloud computing technology offer on-line real-time monitoring knowledge, we have a tendency to create project supported cloud computing application for energy management that is employed for monitoring real time consumption of electricity and load planning. With respect to monitoring knowledge, we have a tendency to be able to plot the load curves so it'll be useful in achieving optimum energy consumption for educational institute.
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International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
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IoT-Based Secure Energy Pricing Management Controller.pptx
1. REPUBLIC OF IRAQ
MINISTRY OF HIGHER EDUCATION AND SCIENTIFIC RESEARCH
MIDDLE TECHNICAL UNIVERSITY
ELECTRICAL ENGINEERING TECHNICAL COLLEGE
By
Rusul Hamdi Hussain
Supervised by
Assist. Prof. Dr. Mohamed Ibrahim Shujaa
IoT-Based Secure Energy Pricing Management Controller
2. Introduction.
Model of Smart Grid System.
Problem statements.
Objective.
Real-Time Pricing scheme.
Theoretical Background.
Experiment Results and Discussion.
Conclusions.
List of papers.
Outlines
3. The Home Energy Management System (HEMS), which incorporates a remote management network using network
technologies, helps consumers to smart home devices .
HEMS consists of hardware and software that allows consumers to effectively handles energy usage through time-consuming
monitoring of intelligent home appliances. HEMS provides advantages in terms of a power schedule problem to optimize
electricity usage and reliability of energy systems.
Introduction
4. Model of Smart Grid System.
Smart grid consists of providers of power supplier (data center), intelligent nodes, power
generators, data network, energy network, and smart buildings or homes.
5. Problem statements
The current electrical networks, the complexity of the distribution network, the widening gap
between energy production and consumption, the ever-increasing demand for electrical energy with
an increasing population, global climate change, energy storage problems, and high initial cost of
renewable energy are the main factors that provide additional limitation on the ability to generate
additional electricity capacity . All these problems provide more incentive to balance the available
generation capacity with the energy demand at all times. Therefore, researchers give more attention
for DR of smart grid, for optimal load scheduling to achieve essential cost and energy saving.
Reading the consumption data for the available household devices is a critical role in load
scheduling . Most of the current available work did not consider the accuracy of load
consumption data. Therefore, effective and accurate consumption data reading provide direct
connection with load management.
Data communication is the foundation of the load management of smart grid. Home area networks
(HAN) provides effective connection with home load to achieve optimal load management. Thus,
scalable and interoperable HAN connection network can support the load scheduling program for
essential cost reduction.
6. Objective
The main objective of this thesis is to implement an optimized smart home energy
management system and IoT application systems with the most suitable optimization using
PSO
A. Designed a Smart plug that helps consumers to remote monitor and controls their electrical appliances.
B. Raspberry Pi has been used and programmed to become one of the main elements of EMC. It can send and
receives commands to a smart plug using the MQTT protocol according to the optimal scheduling time of
household appliances.
C. A mobile application has been built to allow consumers to remotely watch and control the electrical
appliances
D. A public server has been rented (MQTT server) that is used to connect smart plugs, mobile applications, and
EMC with each other.
The main objective is verified through the following sub-objectives:
8. Experiment Results and Discussion
Pricing is used, with off-peak hours of 00:00 to 7:00, 11:00 to 18:00, and peak hours of 7:01 to 10:59
,18:01 to 22:00 being designated. Off-peak rates are 45.54 cents per kWh, whereas peak rates are
144.52 cents per kWh
Cost rate during on-peak and off-peak
10. Experiment Results and Discussion
Appropriate Time Tables for Home Appliances
No. Devices
Power rate
(W)
Duration
(slot/day)
normal
operating periods PSO
Start
(slot)
End
(slot)
Start
(slot)
End
(slot)
1 Micro Wave 827 2 84 86 82 84
Micro Wave 827 2 240 242 214 216
2 Oven 1832 24 228 252 200 224
3 Vacuum 1296 12 156 168 143 155
4 Washing Machine 270 24 144 168 136 160
5 Air conditioner 2108 60 132 192 155 215
Air conditioner 2108 48 216 264 185 233
Air conditioner 2108 72 1 73 1 73
6 Water pump 403 24 192 216 185 209
7 Hair Dryer 1234 6 228 234 208 214
8 Oil Heater 1295 60 1 61 3 63
PSO provides the best results in the shortest amount of time
11. 0
1000
2000
3000
4000
5000
6000
7000
0 25 50 75 100 125 150 175 200 225 250 275 300
Power
(W)
"Time (Slot)"
B. Load distribution using BFO
data before schedule BFO
Experiment Results and Discussion
Total load distribution For PFO
12. 0
1000
2000
3000
4000
5000
6000
0 25 50 75 100 125 150 175 200 225 250 275 300
Power
(W)
"Time (Slot)"
C. Load distribution using Am
data before schedule data Am
Experiment Results and Discussion
Total load distribution For AM
13. Experiment Results and Discussion
Total load distribution For PSO
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
0 25 50 75 100 125 150 175 200 225 250 275 300
Power
(W)
Time (Slot)
A. Load distribution using PSO
data before schedule PSO
PSO achieved a significant costs reduction of 24.31% compared to AM and BFO.
14. Experiment Results and Discussion
Energy and cost results
DR
Scheme
Optimization
Method
Sampling time
(min.)
Total energy (kW
/h)
Peak consumption(kW) Total cost
(R)
Before scheduling - - - 14.308 5.021 11.53
ToU BFO 5 14.308 3.414 8.76
ToU PSO 5 14.308 3.414 8.99
ToU AM 5 14.308 3.414 8.87
PSO show the best results for total cost reductions
20. Contents of the mobile and desktop applications
Message Queuing Telemetry Transport (MQTT)…Cont
21. The proposed of using demand response is to control the energy consumption of individual households, which
helps to reduce the need for additional power plants to meet the growing demand. The utility companies
benefit from lower peak demand, and consumers benefit from lower energy bills. Thus, the percentage of
carbon dioxide released by power plants will be decreased, resulting in environmental protection.
Homeowners can save money on their monthly electricity bills by using a variety of scheduling techniques to
plan when electrical equipment will be used. When compared to other optimization strategies, it has been
found that the suggested PSO method based on the ToU pricing scheme can reduce electricity costs by a
significant amount in a short period of time.
PSO method was applied for consumption data. consumption data are collected using proposed smart plugs
for typical house (in Baghdad), the results found that PSO achieved a significant costs reduction of 24.31%
compared to AM and BFO.
Conclusions
22. Smart plug helps consumer to remote monitoring and control the electrical appliances. In addition, the
possibility to read and store six different types of data representing voltage, current, power, energy, power
factor and frequencyhave been used in the proposed load scheduling algorithm.
Raspberry Pi has been used and programmed to become one of the main elements of EMC. It can send
and receives commands to smart plug using theMQTT protocol according to optimal scheduling time of
household appliances.
Mobile and desktop application has been built to allow consumers to remotely watch and control the
electrical appliances in real time and display their usage information, such as voltage, current and
appliances status (ON or OFF).
A public server has been rented (MQTT server) that is used to connect smart plugs, mobile application,
and EMC with each other.
Conclusions…Cont
23. List of Papers
Rusul H Hussain and Mohamed Ibrahim Shujaa “Data Consumption-Based Home Energy
Management for Residential Platform” AIP Conference Series: “3rd International Conference on
Smart Cities and Sustainable Planning (SCSP)”.
Rusul H Hussain and Mohamed Ibrahim Shujaa “IoT Residential Appliance Monitoring and
Controlling System Using MQTT Protocol” AIP Conference Series: Fourth Scientific
Conference for Electrical Engineering Techniques Research (EETR 2022), Baghdad, Iraq on 8-9
June 2022 (Indexed by: Scopus).
Rusul H Hussain and Mohamed Ibrahim Shujaa “Accuracy Data Consumption-Based for
Residential Platform” Journal of Techniques (MTU).