目前,对多能量虚拟电厂在多种不确定性条件下的优化调度问题研究存在不足。针对这些不确定性问题,提出计及激励型需求响应的热电互联虚拟电厂优化调度模型。首先,针对分布式能源发电的不确定性,根据不同时刻风速、光照强度相关性,利用Student-T Copula函数得到风光发电场景;其次,综合考虑电热相关约束,建立以虚拟电厂效益最大为目标函数的优化调度模型;然后,采用改进型多元宇宙算法对所提出的模型进行优化求解;最后,通过算例仿真,验证所提出的优化调度模型能够平缓负荷曲线,减少环境污染,提高虚拟电厂整体经济效益。
Abstract
At present, the research on optimal scheduling of multi energy virtual power plants under various uncertainties is insufficient. To solve these uncertain problems, an optimal scheduling model of thermoelectric interconnected virtual power plant considering incentive demand response is proposed. Firstly, aiming at the uncertainty of distributed energy generation, according to the correlation of wind speed and solar intensity at different times, the wind power and photovoltaic power generation scenarios are obtained by using Student-T copula function. Secondly, considering the thermoelectric constraints, the optimal scheduling model taking the maximum benefit of virtual power plant as the objective function is established. Then, the improved multi-verse optimizer algorithm is used to optimize the proposed model. Finally, an example is given to verify the proposed optimal scheduling model, indicating that the model can smooth the load curve, reduce environmental pollution and improve the overall economic benefits of the virtual power plant.
关键词
虚拟电厂 /
热电互联 /
柔性负荷 /
需求响应 /
场景生成 /
多元宇宙算法
Key words
virtual power plant /
thermoelectric interconnection /
flexible load /
demand response /
scenario generation /
multi-unirerse algorithm
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基金
国家自然科学基金（52077030）; 南通市基础科学研究面上项目（JC22022080）
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