随着可再生能源规模的不断壮大,电网安全性和稳定性受到前所未有的考验,而虚拟电厂为更好解决峰谷不匹配的问题提供了一种新的思路。本文针对内蒙古地区风电消纳和深度调峰问题,提出一种基于两阶段鲁棒优化的聚合多种灵活性资源的虚拟电厂双层优化控制策略。首先,以虚拟电厂在调度周期内收益最大为目标,同时充分考虑火电机组深度调峰带来的成本和利润,依据风、负荷预测数据构建上层模型。其次,在下层模型中,以虚拟电厂运行成本最小为目标,充分考虑风电、负荷的不确定性带来的风险,根据相关系数的调节,得到不同保守度下虚拟电厂的收益,并根据调度周期内获取的收益情况进行实时修正。最后,仿真结果表明提出的模型具有一定普适性和有效性。

As the scale of renewable energy continues to grow, the security and stability of the power grid is subject to unprecedented tests, and in order to better solve the peak-valley mismatch problem, the virtual power plant provides a new way of thinking. In this paper, we propose a two-stage robust optimization-based dual-layer control strategy for virtual power plant aggregating multiple flexibility resources for wind power consumption and deep peaking in Inner Mongolia. First, an upper model is constructed based on wind and load forecast data with the goal of maximizing the revenue of the virtual power plant during the dispatch cycle, while taking into full consideration the cost and profit brought by the deep peaking of thermal power units. In the lower-layer model, with the goal of minimizing the operating cost of the virtual power plant, the risk brought by the uncertainty of wind power and load is fully considered, and the revenue of the virtual power plant under different degrees of conservatism is obtained according to the adjustment of the correlation coefficient. In addition, the model allows the virtual power plant to make real-time corrections according to the gain obtained during the scheduling cycle. Finally, the simulation results show that the proposed model has a certain degree of universality and effectiveness.

2021年内蒙古自治区科技重大专项项目（2021ZD0026）