中国电机工程学报2016，Vol.36Issue(13)：3451-3462,12.DOI:10.13334/j.0258-8013.pcsee.152491
基于随机模型预测控制的能源局域网优化调度研究
Stochastic Model Predictive Control for Energy Management Optimization of an Energy Local Network
摘要
Abstract
This paper proposed a stochastic model predictive control (SMPC) based energy local network (ELN) optimization and scheduling method for reducing the impacts introduced by the intermittent output of renewable energy resources, fluctuant of load demand and random real-time electricity price of a high renewable energy penetration level ELN. We constructed a mixed integer quadratic programming model as the objective function of the ELN operation by analyzing the features of all the elements in the ELN, and this optimization model can be online operated in a stochastic model predictive control (SMPC) framework. Forecast uncertainty for power production of renewable energy resources, real-time electricity price and load demand were described by scenarios, and a two-stage scenario cutting method was proposed to choose the typical scenarios. Simulation results show that the method proposed in this paper is effective and feasible by comparing with the open-looped operation method and MPC based operation method.关键词
能源互联网/能源局域网/随机模型预测控制/混合整数二次规划/可再生能源Key words
energy internet/energy local network/stochastic model predictive control/mixed integer quadratic programming分类
信息技术与安全科学引用本文复制引用
张彦,张涛,刘亚杰,郭波..基于随机模型预测控制的能源局域网优化调度研究[J].中国电机工程学报,2016,36(13):3451-3462,12.基金项目
国家自然科学基金项目(71571187)；中国博士后科学基金面上项目(2013M542557)。 Project Supported by National Natural Science Foundation of China(71571187) （71571187）
China Postdoctoral Science Foundation(2013M542557 （）
