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计入负荷时空转移特性的风-光-水-蓄互补系统容量配置方法
引用本文:文杰,刘继春,温正楠,李健华,李晨昕.计入负荷时空转移特性的风-光-水-蓄互补系统容量配置方法[J].中国电力,2021,54(2):66-77,97.
作者姓名:文杰  刘继春  温正楠  李健华  李晨昕
作者单位:1. 四川大学 电气工程学院,四川 成都 610065;2. 西南电力设计院,四川 成都 610021
基金项目:国家重点研发计划资助项目(分布式光伏与梯级小水电互补联合发电技术研究及应用示范,2018YFB0905200)。
摘    要:利用梯级水电的快速调节能力和抽蓄机组发电/抽水工况灵活转换的特性,在补偿风/光出力的波动性和不可控性的基础上,建立源端风-光-水-蓄系统互补模型,以增强发电系统的调节能力。同时,在计入现货电价、考虑负荷时间和空间可转移特性的基础上,建立负荷侧模型并在考虑源端风/光出力随机性、系统网络约束基础上,提出基于系统经济性、系统状态均匀度和负荷跟踪等多项系统指标的源-网-荷互动策略。在上述研究基础上,进一步建立互补发电系统多目标容量配置模型。最后通过算例仿真,并利用专业优化软件LINGO进行求解,得到不同规划年和场景下的源端互补系统配置容量,验证了所提方法对系统指标提升的有效性。

关 键 词:需求响应  源-网-荷  风光水蓄  互补系统  电力市场  
收稿时间:2020-02-28
修稿时间:2020-04-08

Capacity Allocation Method for Wind-Solar-Hydro-Storage Complementary System Considering Time and Spatial Transfer Characteristics of Load
WEN Jie,LIU Jichun,WEN Zhengnan,LI Jianhua,LI Chenxin.Capacity Allocation Method for Wind-Solar-Hydro-Storage Complementary System Considering Time and Spatial Transfer Characteristics of Load[J].Electric Power,2021,54(2):66-77,97.
Authors:WEN Jie  LIU Jichun  WEN Zhengnan  LI Jianhua  LI Chenxin
Affiliation:1. College of Electrical Engineering, Sichuan University, Chengdu 610065, China;2. Southwest Electric Power Design Institute Co., Ltd., Chengdu 610021, China
Abstract:By taking advantage of the quick regulation ability of cascade hydropower and the flexible conversion of the working conditions between power generation and pumping of the pumping generator units, and on the basis of compensating the fluctuation and uncontrollability of wind and PV output, a wind-solar-hydro-storage complementary system model is established at the source end to enhance the regulation ability of the power generation system. At the same time, considering the market spot electricity price and the time and spatial transfer characteristics of load, a load-side model is established, and a source-grid-load interaction strategy is proposed based on multiple system indicators such as the economy and state evenness of system and the load tracking, with consideration of the randomness of wind/solar power output at source end and the system network constraints. Based on above study results, a multi-objective capacity allocation model of complementary power generation system is built. Finally, through a case simulation, the nonlinear optimization problem is solved by professional optimization software(LINGO), and the allocation capacities of the source end system under different planning years and scenarios are obtained, which has verified the effectiveness of the proposed method in improving the system indicators.
Keywords:demand response  source-grid-load  wind-solar-hydro-storage system  complementary system  electricity market
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