RTP-Based Residential Energy Consumption Scheduling Model with an Energy Storage System as an Independent ProviderRTP-Based Residential Energy Consumption Scheduling Model with an Energy Storage System as an Independent Provider
- Other Titles
- RTP-Based Residential Energy Consumption Scheduling Model with an Energy Storage System as an Independent Provider
- Authors
- Kim, Sehwan; Ok, Changsoo; Seok, Hyesung
- Issue Date
- 1-Jul-2022
- Publisher
- SPRINGER SINGAPORE PTE LTD
- Keywords
- Demand response; Distributed decision making; Fairness; Smart grids; Stackelberg game
- Citation
- JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, v.17, no.4, pp.2135 - 2149
- Journal Title
- JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
- Volume
- 17
- Number
- 4
- Start Page
- 2135
- End Page
- 2149
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/27568
- DOI
- 10.1007/s42835-022-01046-x
- ISSN
- 1975-0102
- Abstract
- Various real-time pricing (RTP)-based residential consumption scheduling models have been developed to deal with the blackout problem and supply electricity more stably. However, most RTP-based models cause a rebound peak problem. Hence, we propose an innovative RTP-based model with an energy storage system (ESS) as an independent power provider, which is a more reliable and practical solution (called RTP with ESS in this study) than previous models. The price competition between the ESS power provider and wholesale market reduces the power consumption cost of the consumer and peak load of the supply. We compared three models: (1) Non-scheduling, (2) RTP-based Scheduling, and (3) RTP with ESS Scheduling models. Test results reveal that the RTP with ESS Scheduling model reduced consumer power usage costs by 35.24% and 25.86% more than the two models above, respectively. In addition, the RTP with ESS Scheduling model reduced the peak-to-average power ratio of power consumption by 35.10% and 8.71% more than those of the non-scheduling and the existing RTP models, respectively. The consumer standard deviation of power consumption cost was 25.70% and 49.25% lower than those of the non-scheduling and existing RTP models, respectively, and had a fair distribution of power usage costs.
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