首页|考虑用户充电行为和光伏不确定性的光储充电站储能容量优化配置

考虑用户充电行为和光伏不确定性的光储充电站储能容量优化配置

Optimal allocation of energy storage capacity for photovoltaic energy storage charg-ing stations considering EV user behavior and photovoltaic uncertainty

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"双碳"背景下,PSCS(光储充电站)逐渐成为EV(电动汽车)充电站的主流形式.为解决PSCS光伏发电和用户充电行为的不确定性问题,同时保障PSCS的盈利,提出一种考虑EV用户行为和光伏不确定性的PSCS储能容量优化配置方法.首先,采用改进K-means算法对光伏出力数据进行聚类,构建典型光伏出力场景及其概率分布规律.其次,分析EV的充电行为特性,计及环境温度变化对EV耗电量的影响,建立EV充电负荷模型.最后,考虑需求响应,建立以购电成本、碳排放成本、售电收益等为目标函数的经济运行模型.算例分析结果表明,在进行PSCS储能容量配置时考虑光伏出力不确定性和需求响应,能够减少碳排放量并保证PSCS的经济效益.
In the context of the"dual carbon"goals,photovoltaic energy storage charging stations(PSCSs)are gradu-ally emerging as the mainstream form of electric vehicle(EV)charging stations.To address the uncertainty associ-ated with photovoltaic(PV)generation and user charging behavior,while ensuring the profitability of PSCSs,the pa-per proposes a method for optimal allocation of energy storage capacity for PSCSs that takes account of EV user behav-ior and PV uncertainty.Firstly,an improved K-means algorithm is employed to cluster PV output data,establishing typical PV output scenarios and their rules of probability distribution.Secondly,the charging behavior characteristics of EVs are analyzed,incorporating the impact of environmental temperature variations on EV power consumption to develop an EV charging load model.Lastly,considering demand response,an economic operational model is formu-lated with the objective functions including purchasing cost,carbon emission cost,and electricity sales revenue.Case study results demonstrate that incorporating PV output uncertainty and demand response during energy storage capacity configuration of PSCSs can reduce carbon emissions and ensure the economic viability of PSCSs.

EVPSCSdemand responsecarbon emissionenergy storage capacity allocation

蒋宇、吕干云、贾德香、于相宜、俞明、吴启宇、单婷婷

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南京工程学院 电力工程学院,南京 211167

国网能源研究院有限公司,北京 102209

国网江苏省电力有限公司南京市溧水区供电分公司,南京 211200

电动汽车 光储充电站 需求响应 碳排放 储能容量配置

国家自然科学基金江苏省"六大人才高峰"创新团队项目国家电网科技项目

51577086TD-XNY004DSY202205

2024

浙江电力
浙江省电力学会 浙江省电力试验研究院

浙江电力

CSTPCD
影响因子:0.438
ISSN:1007-1881
年,卷(期):2024.43(5)
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