Research Article
Optimal Scheduling Model of Peak-shaving Resources Based on the Quotation for Peak-shaving Capacity
@INPROCEEDINGS{10.4108/eai.18-11-2022.2326912, author={Wei Yuan and Caixia Wang and Qionghui Li and Ning Chen and Liang Xu}, title={Optimal Scheduling Model of Peak-shaving Resources Based on the Quotation for Peak-shaving Capacity}, proceedings={Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China}, publisher={EAI}, proceedings_a={ICEMME}, year={2023}, month={2}, keywords={ancillary service market; peak shaving resources; peak shaving schedule; power generation schedule; mixed integer programming model}, doi={10.4108/eai.18-11-2022.2326912} }
- Wei Yuan
Caixia Wang
Qionghui Li
Ning Chen
Liang Xu
Year: 2023
Optimal Scheduling Model of Peak-shaving Resources Based on the Quotation for Peak-shaving Capacity
ICEMME
EAI
DOI: 10.4108/eai.18-11-2022.2326912
Abstract
The development of the ancillary service market for peak shaving has led to new options for flexible modification of conventional thermal power units and raised the level of utilization of new energy resources. However, the peak shaving schedule is worked out without consideration of the unit power generation schedule and the reserve schedule. This paper proposes a day-ahead optimization model for scheduling the peak shaving resources based on the quotation for the peak shaving capacity of the thermal power unit, which could be used to optimize the unit’s peak shaving schedule, power generation schedule, and reserve schedule as a whole. Based on the established peak shaving compensation benchmark, pricing type, and pricing mechanism of the thermal power units, this model could take the impact on the unit’s power generation schedule resulting from the power generation cost and peak shaving compensation cost into account. Through the analysis of cases selected from typical provinces in China, the results show that the model in this paper could effectively connect the peak shaving ancillary service market and the energy market, and minimize the costs of the peak shaving ancillary services and energy.