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

• DOI: 10.1049/rpg2.12686
• Publication Date: 2023-04-19T06:02:42Z
• Authors: Fasiha Zainab; Komal Naz; Khawaja Khalid Me...; Syed Basit Ali Bu...; Abdul Wadood; Hassan Abdullah K...; Herie Park
• Keywords: Microgrid; Distributed Power Generation; 0211 other engineering and technologies; Lithium-ion Battery Management in Electric Vehicles; FOS: Mechanical engineering; Geometry; 02 engineering and technology; Quantum mechanics; Engineering; Vehicle-to-Grid; Machine learning; FOS: Electrical engineering, electronic engineering, information engineering; FOS: Mathematics; Electrical and Electronic Engineering; Grid; Charging Infrastructure; Biology; Virtual Synchronous Generators; Architectural engineering; Sorting; Physics; Mathematical optimization; Integration of Electric Vehicles in Power Systems; Paleontology; Voltage; Power (physics); Computer science; Algorithm; Genetic algorithm; Joint (building); Control and Systems Engineering; Electrical engineering; Physical Sciences; Automotive Engineering; Control and Synchronization in Microgrid Systems; Grid Synchronization; Stage (stratigraphy); Mathematics

AbstractThis 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 grid‐connected 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.