This study focuses on the potential role of plugin electric vehicles(PEVs) as a distributed energy storage unit to provide peak demand minimization in power distribution systems. Vehicle-to-grid(V2 G) power and curren...This study focuses on the potential role of plugin electric vehicles(PEVs) as a distributed energy storage unit to provide peak demand minimization in power distribution systems. Vehicle-to-grid(V2 G) power and currently available information transfer technology enables utility companies to use this stored energy. The V2 G process is first formulated as an optimal control problem.Then, a two-stage V2 G discharging control scheme is proposed. In the first stage, a desired level for peak shaving and duration for V2 G service are determined off-line based on forecasted loading profile and PEV mobility model. In the second stage, the discharging rates of PEVs are dynamically adjusted in real time by considering the actual grid load and the characteristics of PEVs connected to the grid. The optimal and proposed V2 G algorithms are tested using a real residential distribution transformer and PEV mobility data collected from field with different battery and charger ratings for heuristic user case scenarios. The peak shaving performance is assessed in terms of peak shaving index and peak load reduction. Proposed solution is shown to be competitive with the optimal solution while avoiding high computational loads. The impact of the V2 G management strategy on the system loading at night is also analyzed by implementing an off-line charging scheduling algorithm.展开更多
基于油浸式变压器的顶层油温-绕组等效热路,提出了一种主变压器绕组热点温度的解析模型,该模型能够根据当前采集的主变负载系数和顶层油温数据,实时计算热点温度。相应提出了绕组时间常数的确定方案。通过对某334 MV·A/500 k V主...基于油浸式变压器的顶层油温-绕组等效热路,提出了一种主变压器绕组热点温度的解析模型,该模型能够根据当前采集的主变负载系数和顶层油温数据,实时计算热点温度。相应提出了绕组时间常数的确定方案。通过对某334 MV·A/500 k V主变压器进行实例计算与分析,并将结果与通过GB/T 15164—1994标准中的热点温度计算公式计算的结果进行比较,验证了所提出热点温度模型及计算方法的有效性和正确性,同时指出了GB/T 15164—1994标准中热点温度计算公式存在的缺陷。展开更多
基金supported in part by the Scientific and Technological Research Council of Turkey through the International Post Doctoral Fellowship Program under Grant 2219the support of Baskent Electricity Distribution Company that provided the distribution transformer data within the scope of the project DAGSIS(Impact Analysis and Optimization of Distribution-Embedded Systems)funded by Turkish Energy Market Regulatory Authority(EPDK)
文摘This study focuses on the potential role of plugin electric vehicles(PEVs) as a distributed energy storage unit to provide peak demand minimization in power distribution systems. Vehicle-to-grid(V2 G) power and currently available information transfer technology enables utility companies to use this stored energy. The V2 G process is first formulated as an optimal control problem.Then, a two-stage V2 G discharging control scheme is proposed. In the first stage, a desired level for peak shaving and duration for V2 G service are determined off-line based on forecasted loading profile and PEV mobility model. In the second stage, the discharging rates of PEVs are dynamically adjusted in real time by considering the actual grid load and the characteristics of PEVs connected to the grid. The optimal and proposed V2 G algorithms are tested using a real residential distribution transformer and PEV mobility data collected from field with different battery and charger ratings for heuristic user case scenarios. The peak shaving performance is assessed in terms of peak shaving index and peak load reduction. Proposed solution is shown to be competitive with the optimal solution while avoiding high computational loads. The impact of the V2 G management strategy on the system loading at night is also analyzed by implementing an off-line charging scheduling algorithm.
