薄弱配电网高比例分布式光伏并网消纳规划研究

为了解决薄弱电网高比例分布式光伏难以就地消纳问题,提出储能系统和需求侧响应运行策略,建立了计划接入总量下的高比例分布式光伏双层规划模型。以光伏最大消纳为目标函数,光伏安装位置与容量为优化变量,建立上层模型;以系统净负荷峰谷差期望值最小为目标函数,各时段电价为优化变量,建立下层模型。针对光伏随机出力与负荷的时序性,利用拉丁超立方抽样技术对其进行处理。在此基础上,采用概率潮流法与细胞膜粒子群优化算法相结合的混合智能算法对模型进行求解,并以河北省某贫困县光伏扶贫村网架结构为例进行算例分析。结果表明,解决方案在实现光伏接入容量最优配置的基础上,进一步提高了薄弱配电网分布式光伏的消纳能力。双层规划模型能够在很大程度上提高再生能源的利用率,可为配电网规划提供参考。

Research on grid-connection consumption planning of high proportion distributed photovoltaic in weak distribution network

In view of the difficulty of local consumption of high proportion distributed photovoltaic (PV) in weak power grid, the bi-level programming model under planned total access was proposed in this paper, considering the running strategies of Energy Storage System (ESS) and Demand Response (DR). The upper model took the maximum consumption of PV as the objective function, the installation location and capacity of PV as the optimized variables. The lower model took the minimum expected value of peak-valley net load difference as the objective function, the price of each period as the optimized variable. For the sequential feature of random output of PV and load, the Latin hypercube sampling (LHS) technique was proposed for solving it upon which a hybrid intelligent algorithm combining probabilistic power flow method and Cell Membrane-Improved Particle Swarm Optimization (C-PSO) was employed to solve the model. The grid structure of photovoltaic poverty alleviation village in a poverty-stricken county from Hebei province is taken as an example to analyze the calculation, and the simulation results suggest that the proposed method can improve the consumptive ability of high proportion distributed PV in weak power grid and the utilization of renewable energy on the basis of realizing the optimal configuration of PV access capacity.