Charge Scheduling of an Energy Storage System under Time-of-Use Pricing and a Demand Charge
A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential cu...
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| Veröffentlicht in: | TheScientificWorld Jg. 2014; H. 2014; S. 1 - 9 |
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| Sprache: | Englisch |
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Cairo, Egypt
Hindawi Publishing Corporation
01.01.2014
John Wiley & Sons, Inc Wiley |
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| ISSN: | 2356-6140, 1537-744X, 1537-744X |
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| Abstract | A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithmcan reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power. |
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| AbstractList | A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power. A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power.A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power. A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithmcan reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power. A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power. |
| Audience | Academic |
| Author | Kim, Yong-Hyuk Yoon, Yourim |
| AuthorAffiliation | 1 Department of Computer Engineering, College of Information Technology, Gachon University, 1342 Seongnamdaero, Sujeong-gu, Seongnam-si, Gyeonggi-do 461-701, Republic of Korea 2 Department of Computer Science & Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 139-701, Republic of Korea |
| AuthorAffiliation_xml | – name: 2 Department of Computer Science & Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 139-701, Republic of Korea – name: 1 Department of Computer Engineering, College of Information Technology, Gachon University, 1342 Seongnamdaero, Sujeong-gu, Seongnam-si, Gyeonggi-do 461-701, Republic of Korea |
| Author_xml | – sequence: 1 fullname: Yoon, Yourim – sequence: 2 fullname: Kim, Yong-Hyuk |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25197720$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | Copyright © 2014 Yourim Yoon and Yong-Hyuk Kim. COPYRIGHT 2014 John Wiley & Sons, Inc. Copyright © 2014 Yourim Yoon and Yong-Hyuk Kim. Yourim Yoon et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright © 2014 Y. Yoon and Y.-H. Kim. 2014 |
| Copyright_xml | – notice: Copyright © 2014 Yourim Yoon and Yong-Hyuk Kim. – notice: COPYRIGHT 2014 John Wiley & Sons, Inc. – notice: Copyright © 2014 Yourim Yoon and Yong-Hyuk Kim. Yourim Yoon et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. – notice: Copyright © 2014 Y. Yoon and Y.-H. Kim. 2014 |
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| SubjectTerms | Algorithms Alternative energy sources Computer Simulation Conservation of Energy Resources - economics Costs and Cost Analysis - methods Dynamic programming Electric Power Supplies - economics Electric utilities Electricity Energy policy Energy storage Fee Schedules Genetic algorithms Methods Pricing policies Renewable energy Scheduling (Management) Time Factors |
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| Title | Charge Scheduling of an Energy Storage System under Time-of-Use Pricing and a Demand Charge |
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