考虑分布式电源和多样性负荷主动特性的复杂配电系统动态随机规划模型与方法

项目名称： 考虑分布式电源和多样性负荷主动特性的复杂配电系统动态随机规划模型与方法

项目编号： No.51477116

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 电工技术

项目作者： 刘洪

作者单位： 天津大学

项目金额： 78万元

中文摘要： 可再生能源发电与电动汽车的广泛分布接入在大幅促进城市节能减排的同时，也将对传统电网运行带来巨大的不利影响。为此，充分协调未来系统中源/网/荷等元素的主/被动运行特性，建立配电系统规划的数学模型并提出求解方法，以期提升系统接纳低碳能源的能力和可靠高效运行的水平。首先，通过分布式电源、储能和多样性负荷的特性建模，构建恒定可靠性水平的源/储/荷置信容量评估方法，并提出配电系统电力需求预测与平衡方法。其次，面向用户投资回报、可靠性、资产利用水平、售电收益等多主体效益，提出基于机会约束规划的分布式发电与储能的最优接入容量与位置方法。再次，基于考虑用户职住特征与充电习惯的电动汽车出行仿真模型，研究针对不同路网的电动汽车充电设施选址定容的随机优化方法。最后，基于分布式电源波动性出力、负荷可控特性与网络联络容量的综合协调，构建面向供电能力与可靠性等多目标的复杂配电系统随机动态规划方法。

中文关键词： 有源主动配电系统；配电系统规划；随机动态规划；分布式电源；电动汽车

英文摘要： Widespread integration of renewable energy and electric vehicles substantially promote city energy saving, but they also bring huge harm to traditional power grid's operation. In this respect, active/passive operation characteristics of source/grid/load in future system need to be fully coordinated, mathematical model of distribution system planning should be built and solution method be proposed, in order to enhance the system's acceptance level of low-carbon energy and improve operation reliability and efficiency. First, by building characteristic models of distributed generation, energy storage and diversify load, the constant reliability level source/grid/load confidence capacity assessment method was designed, and the distribution system power demand forecasting and balanced approach was proposed. Second, based on the electric vehicles travel model considering user's residence characteristic and charging habit, the stochastic optimization methods of electric vehicle charging facilities' locating and sizing for different road map was studied. Finally, based on the comprehensive coordination of distributed power output intermittency, load controllability and network contacts capacity, the complex distribution system stochastic dynamic programming method facing multi-target( power supply capacity, reliability, etc) was built.

英文关键词： Active power distribution system;Distribution system planning;Stochastic dynamic programming;Distributed energy resource;Electrical vehicle