| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 398952 | International Journal of Electrical Power & Energy Systems | 2013 | 7 Pages |
This paper introduces an effective method to evaluate the advantages of an energy storage system (ESS) using recycled electric vehicle (EV) batteries (ESS-rEVb). In contrast with previous work mainly to investigate the optimal battery capacity and location under the economic consideration, such as the capital cost and maintenance cost, this paper is an attempt to utilize an optimization algorithm to find out the advantages of the installation of ESS-rEVb in a distribution network from the point of view of power network operation. The Genetic Algorithm (GA), an optimal search technique, was adopted to solve the multi-objective optimization problem. The major objective functions consist of the electric fee saving, line loss reduction, and voltage deviation minimization. Major constraints such as the line thermal limit and allowable maximum voltage deviation are all taken into account in the process. To precisely simulate the influence of charge/discharge time of the ESS-rEVb on the distribution network, the daily load curves and hourly renewable energy generation in Taiwan were also taken into account. The outcomes are of value to power engineers to assess the application of ESS-rEVb both on operation safety and economic benefits.
► Method to evaluate an energy storage system using recycled electric vehicle batteries (ESS-rEVb). ► The Genetic Algorithm was adopted to solve the multi-objective optimization problem. ► Objective functions are electric fee saving, line loss reduction, and voltage deviation minimization. ► The typical daily load curves and hourly renewable energy generation in Taiwan were taken into account.
