摘要
近年来,在国家新能源政策支持下,电力系统作为可再生能源装机比例快速提高。然而,风、光等新能源发电具有“靠天吃饭”的特点,存在较大的波动性和随机性,使得新能源发电高峰往往与用电高峰不一致,因此现有电力系统中均需要配置储能系统,即形成风光储联合电力系统。目前对于这种联合系统的调度方法的研究不足,为此本文提出一种多目标线性规划(LP)的风光储联合优化调度模型。该模型考虑功率平衡、充放电效率、爬坡率等因素作为约束,目标为系统运行成本最低和可再生能源消纳最大的协同实现。以我国西部某地区电力系统为例对该模型进行了验证,结果表明:该模型可有效优化电力系统的风光储联合配置,运行成本降低12.7%,弃风弃光率降低超30%。
In recent years,with the support of the new national energy policy,the proportion of renewable energy installed capacity in power systems has rapidly increased.However,renewable energy generation,such as wind and solar power,has the characteristic of“relying on the weather”;that is,it has large fluctuations and randomness,making the peak of renewable energy generation often inconsistent with the peak of electricity consumption.Therefore,existing power systems are requested to be equipped with energy storage systems,that is,to form a wind-solar-energy storage joint power system.Significant deficiencies exist in the research on the optimisation dispatch method of such joint systems.This paper proposed a multi-objective linear programming(LP)model for joint optimisation dispatch of wind,solar and energy storage.This model considered the constraints of power balance,charging and discharging efficiency,and ramp rate,and the objective was to achieve the coordinated realisation of the lowest system operation cost and the maximum consumption of renewable energy.The model was verified through a power system example in a particular area in the West.The calculation results show that the established model can optimise the power system’s joint configuration of wind,solar and energy storage.In the case study,the model can reduce the system operation cost by 12.7%and reduce the wind and solar power curtailment rate by more than 30%.
作者
鲍禄山
BAO Lushan(China Railway First Survey and Design Institute Group Co.,Ltd.,Xi’an 710043,Shaanxi,China)
出处
《电站辅机》
2025年第2期22-25,共4页
Power Station Auxiliary Equipment
关键词
可再生能源
风光储联合系统
优化调度模型
电力系统
renewable energy
wind-solar-energy storage joint system
optimization dispatch model
power system
