Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy
Internet of Things enabled smart grid (SG) is one of the most advanced technologies, which plays a key role in maintaining a balance between demand and supply by implementing demand response (DR) program. In SG, the main focus of the researchers is on home energy management (HEM) system, which is ca...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8070309/ |
| _version_ | 1818323365015846912 |
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| author | Saqib Kazmi Nadeem Javaid Muhammad Junaid Mughal Mariam Akbar Syed Hassan Ahmed Nabil Alrajeh |
| author_facet | Saqib Kazmi Nadeem Javaid Muhammad Junaid Mughal Mariam Akbar Syed Hassan Ahmed Nabil Alrajeh |
| author_sort | Saqib Kazmi |
| collection | DOAJ |
| description | Internet of Things enabled smart grid (SG) is one of the most advanced technologies, which plays a key role in maintaining a balance between demand and supply by implementing demand response (DR) program. In SG, the main focus of the researchers is on home energy management (HEM) system, which is called demand side management. Appliance scheduling is an integral part of HEM system as it manages energy demand according to supply, by automatically controlling the appliances and shifting the load from peak to off peak hours. In this paper, the comparative performance of HEM controller embedded with heuristic algorithms, such as harmony search algorithm, enhanced differential evolution, and harmony search differential evolution, is evaluated. The integration of renewable energy source (RES) in SG makes the performance of HEM system more efficient. The electricity consumption in peak hours usually creates peaks and increases the cost but integration of RES makes the electricity consumer able to use the appliances in the peak hours. We formulate our problem using multiple knapsack theory that the maximum capacity of the consumer of electricity must be in the range, which is bearable for consumer with respect to electricity bill. Feasible regions are computed to validate the formulated problem. Finally, simulation of the proposed techniques is conducted in MATLAB to validate the performance of proposed scheduling algorithms in terms of cost, peak-to-average ratio, and waiting time minimization. |
| first_indexed | 2024-12-13T11:11:32Z |
| format | Article |
| id | doaj.art-a6fa77f9d5844bf08a4bbc86fb4e43bb |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T11:11:32Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-a6fa77f9d5844bf08a4bbc86fb4e43bb2022-12-21T23:48:44ZengIEEEIEEE Access2169-35362019-01-017242672428110.1109/ACCESS.2017.27636248070309Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of EnergySaqib Kazmi0Nadeem Javaid1https://orcid.org/0000-0003-3777-8249Muhammad Junaid Mughal2Mariam Akbar3Syed Hassan Ahmed4https://orcid.org/0000-0002-1381-5095Nabil Alrajeh5COMSATS Institute of Information Technology, Islamabad, PakistanCOMSATS Institute of Information Technology, Islamabad, PakistanCOMSATS Institute of Information Technology, Islamabad, PakistanCOMSATS Institute of Information Technology, Islamabad, PakistanSchool of Computer Science and Engineering, Kyungpook National University, Daegu, South KoreaCollege of Applied Medical Sciences, King Saud University, Riyadh, Saudi ArabiaInternet of Things enabled smart grid (SG) is one of the most advanced technologies, which plays a key role in maintaining a balance between demand and supply by implementing demand response (DR) program. In SG, the main focus of the researchers is on home energy management (HEM) system, which is called demand side management. Appliance scheduling is an integral part of HEM system as it manages energy demand according to supply, by automatically controlling the appliances and shifting the load from peak to off peak hours. In this paper, the comparative performance of HEM controller embedded with heuristic algorithms, such as harmony search algorithm, enhanced differential evolution, and harmony search differential evolution, is evaluated. The integration of renewable energy source (RES) in SG makes the performance of HEM system more efficient. The electricity consumption in peak hours usually creates peaks and increases the cost but integration of RES makes the electricity consumer able to use the appliances in the peak hours. We formulate our problem using multiple knapsack theory that the maximum capacity of the consumer of electricity must be in the range, which is bearable for consumer with respect to electricity bill. Feasible regions are computed to validate the formulated problem. Finally, simulation of the proposed techniques is conducted in MATLAB to validate the performance of proposed scheduling algorithms in terms of cost, peak-to-average ratio, and waiting time minimization.https://ieeexplore.ieee.org/document/8070309/Smart gridknapsackenhanced differential evolutionharmony search algorithmhome energy management systemdemand side management |
| spellingShingle | Saqib Kazmi Nadeem Javaid Muhammad Junaid Mughal Mariam Akbar Syed Hassan Ahmed Nabil Alrajeh Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy IEEE Access Smart grid knapsack enhanced differential evolution harmony search algorithm home energy management system demand side management |
| title | Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy |
| title_full | Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy |
| title_fullStr | Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy |
| title_full_unstemmed | Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy |
| title_short | Towards Optimization of Metaheuristic Algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy |
| title_sort | towards optimization of metaheuristic algorithms for iot enabled smart homes targeting balanced demand and supply of energy |
| topic | Smart grid knapsack enhanced differential evolution harmony search algorithm home energy management system demand side management |
| url | https://ieeexplore.ieee.org/document/8070309/ |
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