An optimal joint planning of DGs and electric vehicle charging stations in grid‐connected and islanded microgrids

Abstract

This paper proposes a new framework for the planning of both distributed generators (DGs) and electric vehicle charging stations (EVCSs). The proposed method efficiently produces a unified solution for the joint planning of DGs and EVCSs for both gridconnected and islanded scenarios. The problem is formulated as a novel two-stage planning problem. The first stage determines the locations and sizes of the DGs with locations of EVCSs in grid-connected scenario, whereas the second stage planning identifies the optimal islands under the islanded microgrid scenario. A non-dominated sorting genetic algorithm (NSGA-II) is applied to solve the first stage planning problem; in this stage, the algorithm minimizes two objective functions: the system-losses and total cost. In the second stage, another single objective optimization problem is designed which minimizes supply voltage variations to find optimal islands for the DGs and EVCSs to ensure a secure supply of power for EVs. The proposed framework is implemented on the IEEE 33-bus system and verified with four test cases. The results demonstrate the effectiveness of the proposed method and show that the sizes and locations of DGs, and locations of EVCSs are adequate for both grid-connected and islanded microgrids.

Optimum Design of an Electric Vehicle Charging Station Using a Renewable Power Generation System in South Korea

“…To reduce carbon emissions and distribute EVs simultaneously, there is a need for charging EVs using renewable power generation instead of conventional power plants that emit carbon. Renewable power can contribute to various purposes, including lowering peak power [8][9][10], enhancing the resilience [11] of the main grid, demanding response applications [12], and distributing resource operations [13].…”

“…To reduce carbon emissions and distrib EVs simultaneously, there is a need for charging EVs using renewable power genera instead of conventional power plants that emit carbon. Renewable power can contrib to various purposes, including lowering peak power [8][9][10], enhancing the resilience of the main grid, demanding response applications [12], and distributing resource op tions [13]. To investigate the integration of renewable energy systems into a power grid and their optimization [15][16][17], the HOMER (Hybrid Optimization of Multiple Energy Resources) software [18] has been widely applied, as shown in Table 1.…”