Optimal Plug-in Electric Vehicles Management by Aggregators

被引：0

作者：

Benalcazar, Patricio ^{[1
]}

Samper, Mauricio E. ^{[1
]}

Vargas, Alberto ^{[1
]}

机构：

[1] Univ Nacl San Juan, Inst Energia Elect, CONICET, San Juan, Argentina

来源：

2015 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM APPLICATION TO POWER SYSTEMS (ISAP) | 2015年

关键词：

Aggregator; dispersed generators; economic dispatch; energy storage; mean-variance mapping optimization; plug-in electric vehicles; smart distribution grids;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The energy consumption and supply requirements of a large number of plug-in electric vehicles (PEV) should be optimally attended in an economical and controlled form. In this manner, adequate economic remunerations to PEV owners that participate in energy selling/purchase transactions and normal operative conditions in a smart distribution grid (SDG) can be provided. The concept of "aggregators" represents an alternative to manage the new active role that the PEV will perform in the SDG. In this sense, this paper proposes a methodology to dispatch the PEV requirements in an optimal and economical manner. Aggregators located in a SDG are used to optimize the quantities of energy that each PEV can consume and supply. Mean-Variance Mapping Optimization (MVMO) metaheuristic algorithm is used in the optimization process and compared with an exhaustive analysis of the problem. The results show the robustness and the quickness of MVMO to solve this dispatch.

引用

页数：6