计及需求响应的光热电站参与深度调峰的分层优化调度策略

陈伟, 刘文翰, 魏占宏, 张晓英, 李万伟, 冯智慧

太阳能学报 ›› 2024, Vol. 45 ›› Issue (3) : 579-590.

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (3) : 579-590. DOI: 10.19912/j.0254-0096.tynxb.2022-1789

计及需求响应的光热电站参与深度调峰的分层优化调度策略

  • 陈伟1, 刘文翰1, 魏占宏1, 张晓英1, 李万伟2, 冯智慧2
作者信息 +

HIERARCHICAL OPTIMAL SCHEDULING STRATEGY FOR CONCENTRATING SOLAR POWER PARTICIPATING IN DEEP PEAK SHAVING CONSIDERING DEMAND RESPONSE

  • Chen Wei1, Liu Wenhan1, Wei Zhanhong1, Zhang Xiaoying1, Li Wanwei2, Feng Zhihui2
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文章历史 +

摘要

从源、荷两侧挖掘系统调峰潜力,建立计及需求响应的光热电站参与深度调峰的分层优化调度模型。上层从负荷侧出发,提出一种基于负荷分类的价格需求响应模型,可有效缓解系统调峰压力;中层从电源侧出发,利用光热电站灵活的调节特性在深度调峰时段协调火电机组参与辅助调峰,构建以运行总成本最小为目标函数的日前调度模型;下层提出一种基于模型预测控制的日内动态调整模型,在滚动优化的同时,通过状态反馈环节实时调整光热电站储热装置充放热修正日前调度计划。仿真结果表明,所提调度策略在降低系统调峰成本的同时能有效抑制风光以及负荷的短时功率波动,在保证系统安全稳定运行的前提下提升风光消纳率。

Abstract

The peak regulation potential of the system is excavated from both sides of the source and load, and a hierarchical optimal scheduling strategy for concentrating solar power participating in deep peak shaving considering demand response is established. Starting from the load side, the upper layer proposes a price demand response model based on load classification, which effectively alleviates the pressure of system peak regulation. Starting from the power supply side, the middle layer uses the flexible regulation characteristics of the concentrating solar power to coordinate the thermal power units to participate in the auxiliary peak regulation during the deep peak regulation period, and constructs a day-ahead scheduling model with the minimum total cost as the objective function. In the lower layer, an intra-day dynamic adjustment model based on model predictive control is proposed. While rolling optimization, the day-ahead scheduling plan of the heat storage device of the concentrating solar power is adjusted in real time through the state feedback link. The simulation results show that the proposed scheduling strategy can effectively suppress the short-term power fluctuation of wind-solar and load while reducing the peaking cost of the system, and improve the wind-solar consumption rate under the premise of ensuring the safe and stable operation of the system.

关键词

调度 / 储热 / 模型预测控制 / 光热电站 / 需求响应 / 深度调峰

Key words

scheduling / heat storage / model predictive control / concentrating solar power / demand response / deep peak shaving

引用本文

导出引用
陈伟, 刘文翰, 魏占宏, 张晓英, 李万伟, 冯智慧. 计及需求响应的光热电站参与深度调峰的分层优化调度策略[J]. 太阳能学报. 2024, 45(3): 579-590 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1789
Chen Wei, Liu Wenhan, Wei Zhanhong, Zhang Xiaoying, Li Wanwei, Feng Zhihui. HIERARCHICAL OPTIMAL SCHEDULING STRATEGY FOR CONCENTRATING SOLAR POWER PARTICIPATING IN DEEP PEAK SHAVING CONSIDERING DEMAND RESPONSE[J]. Acta Energiae Solaris Sinica. 2024, 45(3): 579-590 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1789
中图分类号: TM615   

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基金

国家自然科学基金(51767017; 51867015); 甘肃省基础研究创新群体项目(18JR3RA133)

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