Optimal sizing and sitting of EVCS in the distribution system using metaheuristics: A case study

• Main Authors: Liang Chen, Chunxiang Xu, Heqing Song, Kittisak Jermsittiparsert
• Format: Article
• Language: English
• Published: Elsevier 2021-11-01
• Series: Energy Reports
• Subjects: Electric vehicle charging station; Allocation; Optimization; Balanced Mayfly Algorithm; Installation cost
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352484720317364

In this study, a new optimal allocation and sizing have been proposed for an Electric Vehicle Charging Station (EVCS) on a Distribution System in Allahabad, India. The main idea is to optimize the EVCS configuration by considering Voltage Profile Improvement Index (VPII), Reactive Power Loss Reduction Index (QLRI), Real Power Loss Reduction Index (PLRI), and the preliminary development cost to get the minimum value of the installation cost and to provide higher quality of parameters for the power grid. For solving the studied nonlinear mixed-integer optimization problem, a new improved metaheuristic, called Balanced Mayfly Algorithm (BMA) is proposed. The modification is established to improve the accuracy and to resolve the exploration issue of the algorithm. The BMA used two modifications including elite mayfly couples and chaos mechanism to resolve these issues as it is possible. After validating the algorithm, it is applied to 30-bus distribution system in Allahabad, India and its results are compared with GAIPSO and basic MA. The results indicated that the voltage shape is smoothened and a reasonable balance between voltage profile and network losses is obtained. The results also show that the suggested method with 18.358 MW active power loss, 73.826 MVar reactive power loss, 10961 s computational burden, and 415 number of charging ports gives superior performance with lesser power losses. The number of CS allocated through GAIPSO and MA does not satisfy the demand of the city’s consumers.