考虑风电和储能接入电网的多目标协同博弈区间经济调度

Interval economic dispatch of multi-objective cooperative game considering wind power and energy storage connected to power grid

中文关键词  经济性  安全性  区间优化  经济调度  协同博弈  均衡协调  多目标优化

英文关键词  economy  security  interval optimization  economic dispatch  cooperative game  equilibrium coordination  multi-objective optimization

中文摘要

      针对风电的不确定性对电网调度的经济和安全运行造成影响的问题, 充分考虑储能灵活充放电的运行优 势, 提出了一种基于改进均衡协调算法的多目标区间储能经济调度优化方法. 本文综合考虑有功调度与无功优化之 间的内在耦合关系, 以典型日运行的电压偏差和系统综合运行总成本最小化为优化目标, 建立多目标区间储能经济 调度优化模型. 在优化过程中, 首先考虑在直流潮流的区间调度模型中, 通过优化储能和发电机的有功出力来实现 对风电不确定性的处理, 然后采用改进均衡协调算法对考虑交流潮流的有功–无功储能调度模型进行综合优化, 从 而获得兼顾电网安全性与经济性的均衡最优解. 本文还从风电的不同区间波动以及风电场并网规模的角度出发, 分 析了对系统储能调度运行的影响. 最后本文将改进算法获得的最优解与采用带权重系数的理想点法分析获得的 Pareto最优解进行对比分析, 可避免确定权重因子时的人为主观因素. 本文通过对IEEE RTS–24节点系统进行算例 仿真, 验证了所提模型的合理性和可行性.

英文摘要

      In view of the impact of wind power uncertainty on the economic and safe operation of power grid dispatching, fully considering operational advantages of flexible charging and discharging of energy storage, a multi-objective interval energy storage economic dispatch optimization method based on improved equilibrium coordination algorithm is proposed. Considering inherent coupling relationship between active power dispatch and reactive power optimization, a multi-objective interval energy storage economic dispatch optimization model is established to minimize voltage deviation and overall operation cost of typical daily operation. During the optimization, firstly in the interval dispatching model considering DC power flow, the uncertainty of wind power is handled by optimizing outputs of energy storage and generators. Then, the improved algorithm is used to optimize active-reactive dispatching model to obtain equilibrium optimal solution by considering AC power flow as well as the security and economy of the grid. The paper also analyzes the impact on system dispatch operation from the perspective of different interval fluctuations of wind power and the scale of wind farms connected to the grid. Finally, this paper compares optimal solution of the improved algorithm with Pareto optimal solution obtained by ideal point method with weight coefficients, which can avoid subjective factors when determining the weight factors. The rationality and feasibility of the proposed model are verified through the simulation of IEEE RTS–24 system.