电工技术学报  2020, Vol. 35 Issue (13): 2792-2804    DOI: 10.19595/j.cnki.1000-6753.tces.191843
多种可再生能源互补发电系统的规划与运行专题(特约主编:陈哲教授 胡维昊教授) |
市场机制下光伏/小水电/抽水蓄能电站系统容量优化配置
罗仕华1, 胡维昊1, 黄琦1, 韩晓言2, 陈哲3
1.电子科技大学机械与电气工程学院 成都 611731
2.国家电网四川省电力公司 成都 611041
3.奥尔堡大学能源系 奥尔堡 DK-9110
Optimization of Photovoltaic/Small Hydropower/Pumped Storage Power Station System Sizing under the Market Mechanism
Luo Shihua1, Hu Weihao1, Huang Qi1, Han Xiaoyan2, Chen Zhe3
1. School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu 611731 China
2. State Grid Sichuan Electric Power Company Chengdu 611041 China
3. Department of Energy Technology Aalborg University Aalborg DK-9110 Denmark
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摘要 在我国电力市场化改革以及新能源发电技术越加成熟的背景下,新能源发电技术在当前电力市场中无疑具有广阔发展前景。基于混合能源系统的经济效益以及清洁环保的现代化能源体系的需求,该文针对电力市场中的新能源发电技术,提出一种市场机制下光伏/小水电/抽水蓄能电站的混合能源系统容量配置优化方法,旨在获得最大的经济效益。首先建立以光伏电站、小水电站和抽水蓄能电站为主体的混合能源系统模型。其次,基于该模型提出以系统投资成本最小为上层目标函数和以系统获得售电收益最大为下层目标函数的双层规划模型,并采用线性递减惯性权重粒子群算法以及序列二次规划算法对模型的上、下层求解。此外,该模型考虑各个主体投资成本的规模效应。最后,基于收集的数据对混合能源系统容量配置进行仿真分析,得出有储能方式下的混合能源系统在整个项目周期内所获经济效益是无储能方式下的2.6倍,结果验证了提出的模型与方法的有效性。
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陈哲
关键词 混合能源系统双层规划模型线性递减惯性权重粒子群算法序列二次规划算法    
Abstract:Under the background of China's electricity market reform and renewable energy power generation technology becoming more and more mature, renewable energy power generation technology undoubtedly has broad development prospects in current electricity market. Based on the economic benefits of hybrid energy system and the need to build a clean and environmental-friendly modern energy system, this paper puts forward a capacity allocation optimization method for hybrid energy system consist of photovoltaic power station, small hydropower station, pumped storage power station under the market mechanism aiming at renewable energy power generation technology in the electricity market, in order to obtain maximum economic benefits. Firstly, a hybrid energy system model with photovoltaic power station, small hydropower station and pumped storage power station as the main body was established. Secondly, based on this model, a bi-level programming model was proposed, which takes the minimum system investment cost as the objective function of the upper model and the maximum system revenue from electricity sales as the objective function of the lower one. The particle swarm optimization algorithm with linear decreasing inertia weight and sequential quadratic programming algorithm were used to solve the upper and lower layers of the model respectively. In addition, the scale effect of the investment cost of each subject was also introduced into the model. Finally, based on the collected data, the capacity allocation of the hybrid energy system was simulated and analyzed, and it is concluded that the economic benefit of the hybrid energy system with energy storage is expected to be 2.6 times of that without energy storage in the whole project cycle. The results verify the effectiveness of the proposed model and method.
Key wordsHybrid energy system    bi-level programming model    particle swarm optimization algorithm with linear decreasing inertia weight    sequential quadratic programming algorithm   
收稿日期: 2019-12-31     
PACS: TM619  
基金资助:国家重点研发计划资助项目(2018YFB0905200)
通讯作者: 胡维昊 男,1982年生,教授,博士生导师,研究方向为人工智能在电力系统中的应用、可再生能源发电技术。E-mail:whu@uestc.edu.cn   
作者简介: 罗仕华 男,1996年生,硕士研究生,研究方向为可再生能源发电规划与运行。E-mail:luoshhu@std.uestc.edu.cn
引用本文:   
罗仕华, 胡维昊, 黄琦, 韩晓言, 陈哲. 市场机制下光伏/小水电/抽水蓄能电站系统容量优化配置[J]. 电工技术学报, 2020, 35(13): 2792-2804. Luo Shihua, Hu Weihao, Huang Qi, Han Xiaoyan, Chen Zhe. Optimization of Photovoltaic/Small Hydropower/Pumped Storage Power Station System Sizing under the Market Mechanism. Transactions of China Electrotechnical Society, 2020, 35(13): 2792-2804.
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https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.191843          https://dgjsxb.ces-transaction.com/CN/Y2020/V35/I13/2792