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Impact of electric vehicles on optimal power dispatch of a micro-grid in competitive electric market.
- Source :
-
Energy Sources Part A: Recovery, Utilization & Environmental Effects . 2022, Vol. 44 Issue 4, p10181-10200. 20p. - Publication Year :
- 2022
-
Abstract
- In this study, for optimal power dispatch of a grid-connected micro-grid, a new stochastic model has been built up to minimize the operating cost of micro-grid that equipped with plug-in hybrid electric vehicles, renewable energy sources, and storage devices. Impact of electric vehicles on power dispatch is studied by considering its uncertainty charging characteristics. Monte–Carlo simulation is employed for uncertainty modeling. For this work, three different charging strategies are followed up, namely, uncontrolled, controlled, and smart charging strategy to observe the impact of electric vehicles on micro-grid. So, here an endeavor has been made using a potent and robust technique i.e. improved whale optimization algorithm for obtaining optimal power dispatch. The suggested method's appropriateness and effectiveness are evaluated by modeling a grid-connected micro-grid. The outcomes of this technique improve the MG's performances in terms of best solution and economic operation. On different case studies, the outcomes are compared with other methods without and with charging strategy of electric vehicles. It is seen that operating cost obtained without electric vehicles is nearly 300$ and with charging strategy, i.e. uncontrolled, controlled, and smart of electric vehicles are 664$, 390$, and 327$, respectively. So, inclusion of vehicles on MG increases operating cost but its impact on micro-grid significantly reduces the operating cost for smart charging strategy in comparison with other charging strategy. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15567036
- Volume :
- 44
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Energy Sources Part A: Recovery, Utilization & Environmental Effects
- Publication Type :
- Academic Journal
- Accession number :
- 161081710
- Full Text :
- https://doi.org/10.1080/15567036.2022.2143950