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计及风、光消纳的风电-光伏-光热互补发电二层优化调度
引用本文:熊伟,马志程,张晓英,王琨,周强,陈伟.计及风、光消纳的风电-光伏-光热互补发电二层优化调度[J].太阳能学报,2022,43(7):39-48.
作者姓名:熊伟  马志程  张晓英  王琨  周强  陈伟
作者单位:1.兰州理工大学电气工程与信息工程学院,兰州 730050; 2.国网甘肃省电力公司电力科学研究院,兰州 730000; 3.国网甘肃省电力公司营销服务中心计量部,兰州 730000
基金项目:国家自然科学基金(51867015);;甘肃省科技重大专项计划(19ZD2GA003);
摘    要:以风电、光伏、光热构成新能源互补发电模式,计及风、光资源消纳,建立将高载能负荷作为可调度资源参与新能源互补发电系统的二层优化调度模型,采用NSGA-Ⅱ和二进制粒子群算法求解模型。上层优化模型以互补系统输出功率波动最小和并网效益最大为优化指标确定各机组的出力,并且计算出弃风弃光量。在此基础上,下层优化模型针对上层优化模型造成的弃风弃光量,选取能够有效消纳风、光的高载能负荷参与电网调度。最后,以甘肃地区实际数据为例,验证了所提方法的可行性和有效性。仿真结果表明,光热电站的参与增加了44.3%的经济效益,减小了65.8%的输出功率波动,高载能负荷的参与减小了86.3%的弃风弃光量。

关 键 词:调度  遗传算法  多目标优化  消纳  二层规划  高载能负荷  
收稿时间:2020-10-27

TWO-LAYER OPTIMAL DISPATCH OF WF-PV-CSP HYBRID POWER GENERATION CONSIDERING WIND POWER AND PHOTOVOLTAIC CONSUMPTION
Xiong Wei,Ma Zhicheng,Zhang Xiaoying,Wang Kun,Zhou Qiang,Chen Wei.TWO-LAYER OPTIMAL DISPATCH OF WF-PV-CSP HYBRID POWER GENERATION CONSIDERING WIND POWER AND PHOTOVOLTAIC CONSUMPTION[J].Acta Energiae Solaris Sinica,2022,43(7):39-48.
Authors:Xiong Wei  Ma Zhicheng  Zhang Xiaoying  Wang Kun  Zhou Qiang  Chen Wei
Affiliation:1. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; 2. State Grid Gansu Electric Power Research Institute, Lanzhou 730000, China; 3. State Grid Gansu Electric Power Company Marketing Service Center, Department of Metering, Lanzhou 730000, China
Abstract:This paper makes a new energy hybrid power generation model, composed of wind power, photovoltaics, and concentrating solar power (CSP). Considering the consumption of wind and solar resources, a two-tier optimal scheduling model that uses high-load energy loads as schedulable resources to participate in the new energy complementary power generation system has been established. The fast non-dominated sorting genetic algorithm (NSGA-Ⅱ) with elite strategy and binary particle swarm algorithm are used to solve the two-layer model. The upper-level optimization model uses the minimum output power fluctuation of the hybrid system and the maximum grid connection benefit as the optimization indicators to determine the output of each unit, to calculates the amount of wind and solar abandonment. On this basis, the lower-level optimization model selects the high-energy loads that can effectively absorb wind and light to participate in the grid dispatching according to the amount of wind and light abandonment caused by the upper-level optimization model. Finally, the actual data in Gansu district of China verifies the feasibility and effectiveness of the proposed method. The simulation results show that the participation of CSP stations increases the economic benefits by 44.3%, the output power fluctuations drops by 65.8%, and the participation of high-energy loads reduces the amount of wind and solar abandonment by 86.3%
Keywords:scheduling  genetic algorithms  multi objective optimization  consumption  two-layer optimization  high energy load  
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