蚁群算法在电力系统机组优化组合中的应用研究

采用模拟进化优化算法———蚁群优化算法来求解机组最优启停问题。引入了状态、决策、路径等概念,把机组最优启停问题设计成蚁群算法模式,通过附加惩罚项来处理各种约束,用tabu表限制不满足约束的状态,使得蚂蚁的搜索总在可行域内进行,对算法的搜索进程起到了有效的引导作用。仿真证明利用蚁群优化算法求解机组最优启停问题是可行的、有效的。

含储能的高比例风电系统优化运行模型

针对电力系统因风电渗透率不断提高而导致的功率平衡难以实现的问题,提出一种考虑需求响应及碳捕集的含储能高比例风电系统优化运行模型。首先针对电价型、激励型负荷建立了负荷侧需求响应模型,同时建立了碳捕集电厂数学模型及储能模型;在此基础上进一步建立了以系统总成本最低为目标的优化运行模型,并分析了碳捕集价格对系统成本的影响及需求响应对负荷曲线的优化作用,验证了储能对新能源不确定性的积极调控作用,量化了不同比例风电给系统带来的失负荷方面的影响。在MATLAB环境下通过YALMIP工具箱调用Gurobi求解器求解模型。算例结果表明,所提优化模型缓解了高比例风电导致的功率不平衡问题、降低了系统单位供电成本,可在保证系统安全稳定运行的同时降低系统运行总成本。

An Optimization Approach for Unit Commitment of a Power System Integrated with Renewable Energy Sources： A Case Study of Afghanistan

This paper focused on generation scheduling problem with consideration of wind, solar and PHES （pumped hydro energy storage） system. Wind, solar and PHES are being considered in the NEPS （northeast power system） of Afghanistan to schedule all units power output so as to minimize the total operation cost of thermal units plus aggregate imported power tariffs during the scheduling horizon, subject to the system and unit operation constraints. Apart from determining the optimal output power of each unit, this research also involves in deciding the on/off status of thermal units. In order to find the optimal values of the variables, GA （genetic algorithm） is proposed. The algorithm performs efficiently in various sized thermal power system with equivalent wind, solar and PHES and can produce a high-quality solution. Simulation results reveal that with wind, solar and PHES the system is the most-cost effective than the other combinations.