计及虚拟电厂内需求侧灵活性资源的实时电价和V2G协调优化调度策略OACSTPCD
The Real-time Electricity Price and V2G Coordinated Optimal Scheduling Strategy Considering Demand-side Flexibility Resources in VPP
制定合理有效的电价策略和电动汽车充放电策略,可以为电网的经济稳定运行提供保障.文章综合考虑负荷用户、虚拟电厂运营商和上层电网利益,建立了以平抑净负荷功率波动为目标的价格型需求响应实时电价模型,通过引入多种群交互、模拟退火、最优个体扰动等机制对粒子群算法进行改进,并利用算法进行求解得到实时电价方案;然后结合住宅区电动汽车时移特性,在虚拟电厂两日的经济调度时间尺度上,考虑虚拟电厂和电动汽车用户利益建立优化调度模型.算例分析表明所述策略提高了虚拟电厂运行的稳定性、经济性,减少了与上层电网的平均交互电量和峰谷差.
The formulation of reasonable and effective electricity price strategy and EV charging and discharging strategy can provide guarantee for the economic and stable operation of power grids.In this paper,considering the interests of load users,virtual power plant operators and the upper power grid,a real-time electricity price model based on price demand response is established to smooth the fluctuation of net load power.The particle swarm optimization algorithm is improved by introducing multi-population interaction,simulated annealing,optimal individual disturbance and other mechanisms,and the real-time electricity price scheme is obtained by using the algorithm.Then,based on the time-shift characteristics of EVs in residential areas,the optimal scheduling model is established with the maximum benefit of VPP and the minimum charging cost of EVs as scheduling objectives on the two-day economic scheduling time scale of VPP.The calculation example verifies that the strategy improves the stability and economy of VPP operation,and reduces the average interaction electricity and peak-valley difference with the upper power grid.
任帅;肖楚鹏;梁新龙;刘进进;徐梁;徐贺
安徽南瑞继远电网技术有限公司,安徽省 合肥市 230088||南瑞集团有限公司/国网电力科学研究院有限公司,江苏省 南京市 210000南瑞集团有限公司/国网电力科学研究院有限公司,江苏省 南京市 210000||国网电力科学研究院武汉能效测评有限公司,湖北省 武汉市 430074安徽南瑞继远电网技术有限公司,安徽省 合肥市 230088
动力与电气工程
需求响应优化调度虚拟电厂粒子群算法教与学优化算法实时电价
demand responseoptimal schedulingvirtual power plantparticle swarm optimization algorithmteaching-learning based optimization algorithmreal-time electricity price
《电力信息与通信技术》 2024 (008)
27-36 / 10
国家电网南瑞集团有限公司项目资助"面向双碳目标的新型电力系统可调节负荷资源智能互动关键技术及装置研制"(SGNR0000KJJS2105361).
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