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含储能系统及风电的电力系统动态经济调度 被引量:4

Environmental and Economic Dispatch of Grid Connected Large-scale Wind Farm Energy and Storage System
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摘要 风电的随机性和波动性给传统的调度带来困难﹐为此在模型中引入储能系统﹐分析了储能系统对含风电的电力系统经济调度的影响﹐尤其是对系统调峰的影响。将含风电和储能系统的经济调度描述为一个非线性优化问题﹐建立了一个风电场与储能系统相配合的清洁经济调度模型﹐其目标函数在传统火电机组运行费用的基础上兼顾了火电的排污成本﹐寻求经济和环保总成本的最优解﹐采用粒子群算法对该模型进行求解。通过6机系统算例分析﹐表明该模型能够有效地控制储能系统的出力;储能系统的引入可明显降低系统的运行费用﹐尤其是火电机组调峰的费用﹐且提高了风能利用率。 Due to random and fluctuant nature of wind power, difficulty of economic dispatch (ED) is increased. As a result, the en-ergy storage system (ESS) is proposed for power system. This paper presents a simulation method that can assess the impact of ESS on ED problem especially on the power system in peak load shaving. The ED problem with wind power and ESS is formulated as a nonlinear optimization problem. We constructed an optimized economic and environment-friendly model, in which the effect of wind farm and ESS is considered. Besides traditional operation cost, the thermal unit's pollution discharge is introduced in this model in order to seek the best solution for the total costs of economy and environmental protection. The ED model is optimized by particle swarm optimization (PSO) method. A case which contains 6 thermal units and a large-scale wind farm is present to study the im-pacts of ESS. The results show that the model is correct and the introduction of ESS is effective to reduce operation cost and utilize wind power as much as possible.
出处 《重庆师范大学学报(自然科学版)》 CAS CSCD 北大核心 2013年第6期140-146,共7页 Journal of Chongqing Normal University:Natural Science
基金 输配电及系统安全与新技术国家重点实验室自主研究项目(No.2007DA10512712205)
关键词 电力系统 风力发电 动态经济调度 储能系统 粒子群优化算法 power system wind power dynamic economic dispatch energy storage system particle swarm optimization
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