Abstract
An operation of energy storage system (ESS) in buildings and factories is gaining popularity owing to its decreasing price and increasing efficiency. However, there is a financial risk in conducting ESS without evaluating its profit in advance. Therefore, this paper analyzes economic benefits of ESS before installation. A mathematical model of ESS and an ESS power scheduling algorithm are presented, which consider both a peak load and an energy cost to maximize user's benefit. The algorithm employs customer baseline load (CBL)-based load forecasting which will facilitate its engagement in Korean electricity market since it is used in order to evaluate load reduction in Korea. In addition, symmetric additive adjustment (SAA) is applied to improve low load forecasting accuracy of the CBL-based load prediction. That is, day ahead optimization is performed by the CBL-based load prediction and it is rescheduled hourly with corrected load by SAA during ESS operation. In case study, ESS scheduling results for an actual load, CBL-based load forecasting, and SAA applied load forecasting are compared for a normal load day and a peak load day.
Original language | English |
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Title of host publication | Proceedings - 2018 53rd International Universities Power Engineering Conference, UPEC 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538629109 |
DOIs | |
State | Published - 20 Nov 2018 |
Event | 53rd International Universities Power Engineering Conference, UPEC 2018 - Glasgow, United Kingdom Duration: 4 Sep 2018 → 7 Sep 2018 |
Publication series
Name | Proceedings - 2018 53rd International Universities Power Engineering Conference, UPEC 2018 |
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Conference
Conference | 53rd International Universities Power Engineering Conference, UPEC 2018 |
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Country/Territory | United Kingdom |
City | Glasgow |
Period | 4/09/18 → 7/09/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- Customer Baseline Load
- Energy Storage System
- Load Prediction
- Peak Reduction