Open Access

ARTICLE

Peak Shaving Strategy of Concentrating Solar Power Generation Based on Multi-Time-Scale and Considering Demand Response

Lei Fang^*, Haiying Dong, Xiaofei Zhen, Shuaibing Li

School of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China

* Corresponding Author: Lei Fang. Email:

Energy Engineering 2024, 121(3), 661-679. https://doi.org/10.32604/ee.2023.029823

Received 10 March 2023; Accepted 30 May 2023; Issue published 27 February 2024

Abstract

According to the multi-time-scale characteristics of power generation and demand-side response (DR) resources, as well as the improvement of prediction accuracy along with the approaching operating point, a rolling peak shaving optimization model consisting of three different time scales has been proposed. The proposed peak shaving optimization model considers not only the generation resources of two different response speeds but also the two different DR resources and determines each unit combination, generation power, and demand response strategy on different time scales so as to participate in the peaking of the power system by taking full advantage of the fast response characteristics of the concentrating solar power (CSP). At the same time, in order to improve the accuracy of the scheduling results, the combination of the day-ahead peak shaving phase with scenario-based stochastic programming can further reduce the influence of wind power prediction errors on scheduling results. The testing results have shown that by optimizing the allocation of scheduling resources in each phase, it can effectively reduce the number of starts and stops of thermal power units and improve the economic efficiency of system operation. The spinning reserve capacity is reduced, and the effectiveness of the peak shaving strategy is verified.

---

Keywords

---