• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2014, Vol. 35 ›› Issue (4): 122-126.doi: 10.3969/j.issn.1000-7229.2014.04.022

• 电力经济研究 • 上一篇    下一篇

考虑电价-出力关联不确定性的风电场投资分析

曹银利1,刘继春2,张放2,邓创3,王玮1,陈振寰1,张鹏1   

  1. 1.甘肃电力调度通信中心,兰州市 730050;2.四川大学电气信息学院,成都市 610065;3.四川省电力公司电力应急中心,成都市 610041
  • 出版日期:2014-04-01
  • 作者简介:曹银利(1963),男,高级工程师,研究方向为调度技术,E-mail:caoyl@gs.sgcc.com.cn; 刘继春(1975),男,博士,副教授,研究方向为电力系统分析及电力市场,E-mail:jichunliu75@163.com; 张放(1988),女,硕士研究生,研究方向为电力市场,通讯作者, E-mail:zhangfang8877@163.com; 邓创(1983),男,工程师,研究方向为调度自动化,E-mail:eedeng@126.com; 王玮(1970),女,高级工程师,研究方向为调度自动化,E-mail:wangwei@gs.sgcc.com.cn; 陈振寰(1973),男,高级工程师,研究方向为调度技术,E-mail:chenzh@gs.sgcc.com.cn; 张鹏(1977),男,工程师,研究方向为调度技术,E-mail:zhangpeng@gs.sgcc.com.cn。
  • 基金资助:

    国家电网公司科技项目(大规模风电并网调度运行支撑关键技术研究与应用);教育部留学归国人员科研启动基金([2011]1139号)。

Investment Analysis of Wind Farm Considering Electricity Price-Output Associated Uncertainty

CAO Yinli1, LIU Jichun2, ZHANG Fang2, DENG Chuang3, WANG Wei1, CHEN Zhenhuan1, ZHANG Peng1   

  1. 1. Electric Power Dispatching and Communication Center of Gansu Electric Power Company, Lanzhou 730050, China;2. School of Electrical Engineering and Information, Sichuan University, Chengdu 610065, China;3. Power Emergency Center of Sichuan Electric Power Company, Chengdu 610041, China
  • Online:2014-04-01

摘要:

针对电力市场中电价的波动性、风能资源的随机性及可控性差等特性带来的投资风险,运用投资组合理论对风电场集群的投资资金进行合理配置,使得投资者在可承受风险范围内获得更高的资金回报率。首先,计及电价-出力关联不确定性,计算各个风电场每单位装机容量得到的年收益和收益的方差, 建立计及不确定性的风电场投资风险分析模型;而后,运用投资组合理论进行风电场优化配置组合;最后,采用某地区的相关数据模拟仿真,用粒子群算法求解风险投资模型。分析计算结果表明,该方法有效可行。

关键词: 风电场, 相关性, 期望, 风险, 投资组合, 粒子群优化算法

Abstract:

 

Aiming at the investment risk caused by the fluctuation of electricity prices in electricity market, the randomness and poor controllability of wind power, the portfolio theory was utilized to make a rational allocation of investment assets for the wind farm cluster, in order to enable investors to obtain a higher return on capital within the range of acceptable risk. Firstly, the expectations and variances of annual revenue in per unit for each wind farm were calculated with considering the associated uncertainty of electricity price and output, and then an estimation model of wind farm investment risk was established with considering the uncertainty of wind farm. Secondly, the configuration combinations of wind farms were optimized by using portfolio theory. Finally, the related data of a certain area was used for simulation, and particle swarm optimization was used to solve the investment risk model, whose results demonstrated the efficiency of the method.

Key words: wind farm, correlation, expectation, risk, portfolio, particle swarm optimization