高渗透率光伏配电网储能系统优化配置理论与方法

项目名称： 高渗透率光伏配电网储能系统优化配置理论与方法

项目编号： No.51507094

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 电工技术

项目作者： 陈健

作者单位： 山东大学

项目金额： 18万元

中文摘要： 随着越来越多的分布式光伏接入配电网，对配电网安全稳定运行提出了一系列的挑战。储能系统作为实现配电网消纳高渗透率分布式光伏的重要手段得到了越来越多的关注，其中储能系统的优化配置是其能否充分发挥效用的关键因素。本项目在充分考虑含高渗透率分布式光伏配电网运行特性、蓄电池储能系统充放电与寿命特性、蓄电池储能系统功率和能量等不同功能用途的基础上，从蓄电池储能系统模型耦合特性、蓄电池储能系统协调运行机制、协同优化配置模式，以及仿真实验四个方面展开深入研究，建立蓄电池储能系统的充放电与寿命耦合模型，设计考虑多功能有功和无功协调的蓄电池储能系统控制策略方案，提出计及蓄电池储能系统不同时间尺度效益和不同控制策略影响的协同优化配置模型与方法。该项目的研究成果为高渗透率分布式光伏配电网中蓄电池储能系统优化配置提供了理论和技术支撑。

中文关键词： 储能系统；优化配置；高渗透率光伏；耦合模型；协同优化

英文摘要： As more and more distributed photovoltaics are connected to distribution network, it puts forward a series of challenges to the safety and reliability of distribution network. As an important means to implement photovoltaic consumption in distribution network, energy storage system has received more and more attention. The optimal sizing issue of energy storage system is the key element to have its full effects. Based on operation characteristics of distribution network with high photovoltaic penetration, charging-discharging characteristic and life-characteristic of battery energy storage system, different functional uses of power and energy of battery energy storage system, four aspects including the coupling characteristics of battery energy storage system model, the mechanism of coordinated operation, collaborative optimal sizing mode, and simulation and experiment are further studied. The purposes are to establish charging-discharging and life coupling model of battery energy storage system, design operation strategy of battery energy storage system considering multifunction and coordination between active and reactive power, propose collaborative optimal sizing model and method considering different time-scale benefits and influences of different operation strategies. The research results provide theoretical and technical support for optimal sizing of battery energy storage system in distribution network with high distributed photovoltaic penetration.

英文关键词： energy storage system;optimal sizing;high photovoltaic penetration;coupling model;collaborative optimization