摘要
随着风电规模化入网比例的增加,有效协调风电与其它能源电力的运行已成为电力系统调度面临的新挑战。考虑到风、水、火电的自然特性,以充分利用清洁能源、降低系统运行成本、保证火电机组高效平稳运行为目标,建立风–水–火电力系统协调调度的多目标优化模型。首先采用启发式搜索确定火电机组调度台数,以避免系统容量冗余以及风电随机间歇导致的机组频繁启停或低负荷运行。通过引入免疫算法中的抗体繁殖策略,在传统的粒子群算法中增加浓度认知项,通过10机测试系统验证了改进算法的优越性。采用改进的IEEE 24节点测试系统验证了所提模型和算法的合理性和可行性,为风–水–火电力系统协调运行提供借鉴性策略。
Large-scale integration of wind power has brought profound challenge to traditional power generation dispatch. It becomes necessary to effectively coordinate the operation of wind power and traditional power sources. Considering the nature of wind, hydro and thermal power, a multi-objective optimal dispatch model was established for wind-hydro-thermal power system aiming at fully using clean energy, reducing operation cost and ensuring efficient operation of thermal generators. In order to avoid frequent starting and shutting or part-load operation of thermal generators that caused by capacity redundancy and wind randomness, a heuristic search method was applied to determine the number of dispatched thermal units. By introducing the antibody reproduction stratagem in artificial immune algorithm, the conventional particle swarm algorithm was improved through adding particle concentration cognition item and has been proved its superiority on a 10-unit test system. The modified IEEE 24-bus test system was used to verify the rationality and feasibility of the proposed model and algorithm, meanwhile the coordinated operation strategy of wind, hydro and thermal power was obtained.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2013年第13期27-35,共9页
Proceedings of the CSEE
关键词
风力发电
水力发电
火力发电
新能源电力
短期调度
粒子群算法
粒子浓度认知
wind power generation
hydroelectric powergeneration
thermal power generation
renewable energypower
short-term dispatch
particle swarm algorithm
particleconcentration cognition
