多样化柔性负荷深度互动下的虚拟电厂分布鲁棒购售电策略

随着当前电力改革以及电力市场的不断推进,虚拟电厂的发展已成为其重点组成部分,也是市场交易复杂因素的主要集中部分,其中柔性负荷和清洁能源给虚拟电厂带来了巨大的挑战。考虑不同类别用户柔性负荷的运行特性差异,分别对工业负荷、商业负荷和家用负荷进行了特性分析并建模,充分调动虚拟电厂内部的一些可控资源进行互动,并结合风电、光伏、燃气轮机(gas turbine,GT)运行特性,建立了考虑多样化柔性负荷深度互动的虚拟电厂购售电优化模型。此外,随着清洁能源的发展,针对风电、光伏所带来的不确定性挑战,提出了基于场景数据驱动的两阶段变量的分布鲁棒虚拟电厂购售电优化计算模型,再利用列与约束生成算法求解,算例分析验证了该优化模型的有效性。

Distributional Robust Electricity Trading Strategy of Virtual Power Plant with Deep Interaction of Diversified Flexible Loads

With the current electric power reform and the continuous promotion of the electric power market, the development of virtual power plant has become a key part of them. It is also the main concentration part of the complex factors of market transactions, and the flexible load and clean energy also bring great challenges to the virtual power plant. Considering the operation characteristics of different types of users’ flexible load, this paper analyzes and models the characteristics of industrial, commercial and household loads, fully mobilizes some controllable resources within the virtual power plant to interact, and combines the operation characteristics of wind power, photovoltaic power and gas turbines to establish a purchase and sale optimization model for virtual power plant considering the deep interaction of diversified flexible loads. In addition, with the development of clean energy and the challenge of uncertainty brought by photovoltaic and wind power, a scenario data-driven distributional robust model with two-stage variable for power purchase and sale optimization of virtual power plant is proposed, which is solved by column and constraint generation algorithm. The effectiveness of the optimization model is verified by the analysis of examples.