Study of an Optimized Micro-Grid’s Operation with Electrical Vehicle-Based Hybridized Sustainable Algorithm

Recently, the expansion of energy communities has been aided by the lowering cost of storage technologies and the appearance of mechanisms for exchanging energy that is driven by economics. An amalgamation of different renewable energy sources, including solar, wind, geothermal, tidal, etc., is nece...

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Bibliographic Details
Published in:Sustainability 2022-12, Vol.14 (23), p.16172
Main Authors: Nazir, Muhammad Shahzad, Chu, Zhang, Abdalla, Ahmad N, An, Hong Ki, Eldin, Sayed M, M. Metwally, Ahmed Sayed, Bocchetta, Patrizia, Javed, Muhammad Sufyan
Format: Article
Language:English
Subjects:
Algorithms
Alternative energy sources
Distributed generation
Electric vehicles
Electrical loads
Electricity distribution
Energy
Energy conservation
Energy management
Energy sources
Energy storage
Energy use
Environmental management
Gravity
Load fluctuation
Methods
Optimization
Optimization algorithms
Pollution control
Power supply
R&D
Regional development
Renewable energy sources
Renewable resources
Research & development
Scheduling
Search algorithms
Smoothness
Solar energy
Sustainability
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Summary:Recently, the expansion of energy communities has been aided by the lowering cost of storage technologies and the appearance of mechanisms for exchanging energy that is driven by economics. An amalgamation of different renewable energy sources, including solar, wind, geothermal, tidal, etc., is necessary to offer sustainable energy for smart cities. Furthermore, considering the induction of large-scale electric vehicles connected to the regional micro-grid, and causes of increase in the randomness and uncertainty of the load in a certain area, a solution that meets the community demands for electricity, heating, cooling, and transportation while using renewable energy is needed. This paper aims to define the impact of large-scale electric vehicles on the operation and management of the microgrid using a hybridized algorithm. First, with the use of the natural attributes of electric vehicles such as flexible loads, a large-scale electric vehicle response dispatch model is constructed. Second, three factors of micro-grid operation, management, and environmental pollution control costs with load fluctuation variance are discussed. Third, a hybrid gravitational search algorithm and random forest regression (GSA-RFR) approach is proposed to confirm the method’s authenticity and reliability. The constructed large-scale electric vehicle response dispatch model significantly improves the load smoothness of the micro-grid after the large-scale electric vehicles are connected and reduces the impact of the entire grid. The proposed hybridized optimization method was solved within 296.7 s, the time taken for electric vehicle users to charge from and discharge to the regional micro-grid, which improves the economy of the micro-grid, and realizes the effective management of the regional load. The weight coefficients λ1 and λ2 were found at 0.589 and 0.421, respectively. This study provides key findings and suggestions that can be useful to scholars and decisionmakers.
ISSN:2071-1050
2071-1050
DOI:10.3390/su142316172