考虑环境约束和不确定性的虚拟电厂和常规电厂两级优化调度模型

Jun Dong, Lin-Peng Nie, Hui-Juan Huo
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引用次数: 0

摘要

为了有效地实现分布式能源参与系统调度,减少传统电厂的污染物排放,考虑不确定性和环境约束,建立了传统电厂和虚拟电厂的双水平随机优化模型。首先,提出了一种基于区间法和Kantorovich距离的情景生成与约简方法来模拟WPP和PV的输出;其次,建立了虚拟工厂和传统工厂在日前计划下的双级随机最优调度模型。最后,设计了不同的仿真场景来验证所提模型的有效性。结果表明,该模型能够克服不确定性的影响,在环境约束下实现VPP与常规电厂的最优经济联合调度,通过VPP技术实现分布式发电资源的有效整合,具有良好的环境效果。环境绩效高的工厂将获得更大的份额,并产生更多的电力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A bi-level optimal scheduling model for virtual power plants and conventional power plants considering environmental constraints and uncertainty
To effectively realise the distributed energy resources participating in the system scheduling and reduce pollutant emissions from conventional plants, a bi-level stochastic optimal model for conventional plants and VPPs was built considering the uncertainty and environmental constraints. Firstly, a method of scenario generation and reduction is proposed to simulate the output of WPP and PV based on interval method and Kantorovich distance. Secondly, a bi-level stochastic optimal scheduling model for VPPs and conventional plants in a day-ahead plan is constructed. Finally, different simulation scenarios are designed to verify the effectiveness of the proposed model. The results illustrate that the model can overcome the influence of uncertainty and realise optimal economic jointly dispatch for VPPs and conventional plants under environmental constraints, through VPP technology, distributed power generation resources can be integrated effectively and have good environmental effect. Plants with high environmental performance will gain a larger share and generate more power.
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