基于可再生能源不确定性的电力系统双侧备用容量优化

在全球能源互联网背景下，以风电为代表的新能源入网给电力系统安全稳定运行带来新的挑战，同时也对备用容量配置提出了更高的要求，为此提出以双侧备用成本期望最小为目标函数的备用容量优化模型。在考虑需求侧响应中的可中断负荷，以及风速预测偏差和负荷预测偏差等不确定性因素的基础上，建立了满足经济性和可靠性要求的备用容量配置原则。并基于蒙特卡罗随机模拟的遗传算法对改进10机测试系统进行了求解,经过算例求解得到考虑需求侧响应的备用容量优化决策的经济性更好。与以往传统的备用容量配置相比，双侧备用容量配置能够在系统整体内实现资源的优化分配，同时也可以提高风电消纳能力，实现电力系统安全性和经济性最优。

Bilateral Reserve Capacity Optimization of Power System Based on Renewable Energy Uncertainty

Under the background of global energy internet, renewable energy represented by wind power insertion into the power system brings new challenges to the security and stability of the system operation and puts forward higher requirements to the configuration of reserve capacity. For this reason, this paper proposes the optimization model of reserve capacity taking the minimum cost expectations on both sides as the objective function. Considering the interruptible load in the demand response and the uncertainty factors such as the deviations of wind speed prediction and load prediction, we set up the allocation principle of reserve capacity that can satisfy the requirements of economy and reliability. Finally, we solve the improved 10-units test system with using the genetic algorithm based on Monte Carlo stochastic simulation. The economy of reserve capacity optimization decision with considering demand response is better, which is obtained through the example. Compared with traditional reserve capacity configuration, the bilateral reserve capacity configuration can achieve the optimal allocation of resources within the system as a whole, and improve the absorption of wind power generation as well, which can achieve the optimum security and economy of power system.