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基于机会约束规划的购电商长期购电策略
引用本文:关勇,王东海,张蓉,丁晖. 基于机会约束规划的购电商长期购电策略[J]. 电网技术, 2009, 33(13): 96-98
作者姓名:关勇  王东海  张蓉  丁晖
作者单位:关勇,王东海(华北电力大学,工商管理学院,北京市,昌平区,102206);张蓉(北京工程咨询公司,北京市,石景山区,100043);丁晖(国家电力监管委员会济南监管办公室,山东省,济南市,250101)  
摘    要:市场环境下,购电商需要向多个交易市场购电。各个市场的价格波动不同,给购电商带来的风险和收益也不同,因此购电商面临着最优购电策略问题。该文分析了采用方差法度量电价波动风险存在的不足,提出了采用机会约束规划方法对购电商的风险进行管理。以购电商的收益为目标,以购电商所面临的风险为约束,构建了购电商长期购电优化决策模型,并给出了模型求解的遗传算法。利用蒙特卡罗随机模拟和遗传算法相结合的方法对模型进行了仿真计算,验证了该模型和控制策略的正确性和有效性。

关 键 词:购电策略  机会约束规划  风险管理  蒙特卡罗随机模拟  遗传算法  electricity purchasing strategy  chance- constrained programming  risk management  Monte Carlo stochastic simulation  genetic algorithm
收稿时间:2009-06-11
修稿时间:2009-04-24

Long-Term Electricity Purchasing Strategy of Energy Purchaser Based on Chance-Constrained Programming
GUAN Yong,WANG Dong-hai,ZHANG Rong,DING Hui. Long-Term Electricity Purchasing Strategy of Energy Purchaser Based on Chance-Constrained Programming[J]. Power System Technology, 2009, 33(13): 96-98
Authors:GUAN Yong  WANG Dong-hai  ZHANG Rong  DING Hui
Affiliation:1.School of Business Administration;North China Electric Power University;Changping District;Beijing 102206;China;2.Beijing Municipal Engineering Consulting Corporation;Shijingshan District;Beijing 100043;3.Jinan Office of State Electricity Regulatory Commission People's Republic of China;Jinan 250101;Shandong Province;China
Abstract:In the market environment, energy purchasers purchase electricity from multi transaction markets. Different price fluctuations in different markets bring different risks and profit to energy purchasers. The defects of measuring risk of price fluctuation by variance method are analyzed, and it is proposed to manage the risk of energy purchasers by chance-constrained programming. Taking the profit of energy purchaser as objective and the risk that the energy purchaser has to face with as constraint, an optimal decision model of long-term energy purchasing for energy purchaser is built and the genetic algorithm to solve this model is given. The proposed model is simulated by the combination of Monte Carlo stochastic simulation with genetic algorithm, and simulation results show that the proposed method is correct and effective.
Keywords:electricity purchasing strategy  chance-constrained programming  risk management  Monte Carlo stochastic simulation  genetic algorithm  
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