虚拟电厂源荷双侧热电联合随机优化调度  

Joint Stochastic Optimal Scheduling of Heat and Power Considering Source and Load Sides ofVirtual Power Plant

作　　者：袁桂丽[1] 贾新潮 房方[1] 董金凤 YUAN Guili;JIA Xinchao;FANG Fang;DONG Jinfeng(School of Control and Computer Engineering,North China Electric Power University,Changping District,Beijing 102206,China)

机构地区：[1]华北电力大学控制与计算机工程学院,北京市昌平区102206

出　　处：《电网技术》2020年第8期2932-2940,共9页Power System Technology

基　　金：中国工程院咨询研究项目(2018-XY-22)。

摘　　要："三北"地区作为新能源发电基地,因风光发电具有随机、间歇、不确定、难预测的特点,同时该地区冬季在风电大发期,占主体地位的燃煤热电联产机组"以热定电"的运行方式使其灵活调节能力不足,为系统调度计划制定以及旋转备用决策带来难题。为此将热电厂、风电场、光伏电站、电锅炉和柔性负荷聚合为虚拟电厂(virtualpowerplant,VPP),运用基于拉丁超立方采样的场景法处理风光出力的不确定性,提出了一种基于实时电价的VPP运行策略。基于一定置信水平满足系统可靠性要求与优先利用新能源的同时,以最大化VPP期望经济效益为目标,通过电源侧的多源互补协调优化各发电单元的出力,以及通过源荷协同优化预留旋转备用容量,建立了基于实时电价的VPP随机优化调度模型,并采用两层优化的思想,通过黄金分割法与自适应遗传算法求解模型。仿真结果表明,提出的调度策略可有效应对风光出力的不确定性,优先利用新能源发电,并获得很好的经济效益,实现了电力系统绿色、低碳、安全、经济运行。As a renewable power generation base, "Three-North China" area is characterized by random, intermittent, uncertain and unpredictable wind and photovoltaic power generation. Moreover, during the period of large wind power generation in winter, the "electric power determined by heat" operation mode of coal-fired cogeneration units occupying dominant position makes the region’s flexible regulation ability insufficient, posing difficulties for system scheduling planning and decision-making of spinning reserve. For this reason, thermal power plant, wind farm, photovoltaic power plant, electric boiler and flexible load are aggregated into a virtual power plant(VPP). In addition, the scenario method based on Latin hypercube sampling is used to deal with the uncertainty of wind and photovoltaic power output, and a VPP operation strategy based on real-time pricing is proposed. While prioritizing the use of renewable energy and meeting system reliability requirements at a certain confidence level, the output of each power generation unit is optimized through multi-source complementary coordination on the power supply side, and the spinning reserve capacity is reserved through source-load synergy optimization. Finally, a VPP stochastic optimization scheduling model based on real-time pricing is established with the goal of maximizing VPP expected economic benefits. With the idea of two-level optimization, the model is solved with golden section method and adaptive genetic algorithm. Simulation results show that the proposed scheduling strategy can effectively deal with the uncertainty of wind and photovoltaic power output, give priority to renewable energy, and obtain good economic benefits, realizing green, low-carbon, safe and economic operation of power system.

关 键 词：热电联产机组 旋转备用 虚拟电厂 拉丁超立方采样 不确定性 

分 类 号：TM721[电气工程—电力系统及自动化]