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考虑备用需求和风险的供电企业最优购电计划 被引量:50

OPTIMAL ELECTRICITY PROCUREMENT SCHEDULE FOR LOAD SERVICE ENTITIES INCORPORATING WITH RESERVE AND RISKS
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摘要 电力市场的运行实践和已有的研究成果表明:有效的需求侧竞争能够削弱发电市场力、提高系统运行的可靠性和电源的利用率。作为用户购电代理的供电企业是需求侧竞争的主要参与者。为了满足用户电能和系统备用需要,供电企业应综合考虑在长期合同、现货市场、备用市场上的能量分配和自备电厂的资源优化利用。最优购电和资源规划问题正是在这样的背景下提出的,并已成为供电企业亟待解决的一个新课题。作者对供电企业的电能购买优化问题进行了研究,运用现代投资学理论,提出了以购买费用最小为目标的优化模型,考虑了现货市场价格波动风险和企业的风险容忍度对购电计划的影响,并以风险惩罚项形式并入目标函数。用蒙特卡罗仿真方法实现了对模型的求解。文中以加州电力市场历史数据为例,利用所提出的模型,分别对高峰、肩峰和低谷三个典型运行工况,就不同风险系数、有备用和无备用要求等条件进行了仿真研究和比较,为进一步全面研究需求侧购电决策和资源优化奠定了基础。 The operation experiences of present power markets and the existing researches have proved: effective demand side competition is essential to lessen generator market power, improve the system reliability and the utilization efficiency of power sources. In most power markets, Load Service Entities (LSE) act as the agent of consumers to participate in demand competition, it is the duty of LSE for purchase electricity on their consumers' behalf by actively taking part in the competition of long-term contract markets, spot markets, even reserve markets when having reserve obligations, so how to conduct such electricity procurement and planning activities is becoming a challenging problem. This paper researches LSE's electric energy purchase problem, and adopts modern investment theory to propose an optimal model of the minimum purchase expenditure with the consideration of affect of volatilities of spot prices and LSE's risk tolerance on purchase planning which is formulated as penalty term adding in the objective. Monte Carlo simulation algorithm is developed to solve the objective model. The historical data of California Power Market is used to test the presented approach, three typical points: on-peak, shoulder load and off-peak, are utilized to analyze the influences of different risk weight coefficients, with reserve and without reserve demand on electricity purchase planning. The results prove the proposed approach is effective and could be extended for further electric resource planning considering long run electric energy contract and demand side management. This work is supported partly by Specialized Research Fund for the Doctoral Program of Higher Education by the Ministry of Education (No. 20040079002) and Preliminary Research Fund for Significant Subjects by North China Electric Power University.
出处 《电网技术》 EI CSCD 北大核心 2005年第3期33-38,67,共7页 Power System Technology
基金 高等学校博士学科点专项科研基金(20040079002) 华北电力大学重大项目预研基金 香港特别行政区政府资助基金(RGC)联合资助项目。
关键词 供电企业 电力市场 最优购电计划 风险管理 电力工业 Electric loads Electric power systems Electric utilities Mathematical models Resource allocation Risk assessment Scheduling
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参考文献16

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二级参考文献27

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