Journal
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
Volume 16, Issue 2, Pages 671-679Publisher
SPRINGER SINGAPORE PTE LTD
DOI: 10.1007/s42835-020-00613-4
Keywords
Electric vehicles; Micro-grid; Capacity optimization; Users' satisfaction
Categories
Funding
- Wind and Solar Energy Utilization Technology Key Labs Co-constructed by Province
- Ministry of Education Fund [201611]
- Inner Mongolia Scientific Research Innovation Fund [B2018111922Z]
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A multi-objective capacity optimization allocation model was developed to reduce the cost of capacity allocation in AC/DC hybrid micro-grids and improve user satisfaction. The particle swarm optimization algorithm was used to address capacity optimization in EVs across scenarios, proving the rationality and effectiveness of the proposed model.
The increasing number of DC loads, such as electric vehicles (EVs), has resulted in micro-grid undergoing difficulty in satisfying the various demands of such loads. The study develops a multi-objective capacity optimization allocation model for hybrid micro-grid on the bases of users' satisfaction and the orderly charging/discharging of EVs. The proposed model aims to reduce the cost of the capacity allocation of AC/DC hybrid micro-grid and improve users' satisfaction. Particle swarm optimization algorithm is used to address the capacity optimization of hybrid micro-grid in EVs across scenarios. This study verified the rationality and effectiveness of the proposed capacity optimization model by comparing and analyzing the influence of capacity optimization on the orderly/disorderly charging/discharging of EVs and users' satisfaction.
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