Locating Electric Vehicle Solar Charging and Discharging Stations Using Multi-Objective Genetic Algorithm and Fuzzy Decision Making

Shahalami, Seyed Milad; Ahmadnia, Sajjad; Armanfard, Saeed; Kamali, Ali Reza

doi:10.3103/s0003701x22020190

Cited by 3 publications

(1 citation statement)

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“…Electric vehicles (EVs) are at the forefront of the global shift towards sustainable transportation, offering a cleaner, more energy-efficient alternative to traditional engine vehicles [1][2][3]. EVs leverage advances in battery technology, electric motors, and power electronics to provide a driving experience that is not only environmentally friendly but increasingly competitive in terms of performance, range, and cost.…”

Section: Introductionmentioning

confidence: 99%

Game-Theory-Based Design and Analysis of a Peer-to-Peer Energy Exchange System between Multi-Solar-Hydrogen-Battery Storage Electric Vehicle Charging Stations

Duan,

Yuan,

Taylor

et al. 2024

Electronics

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As subsidies for renewable energy are progressively reduced worldwide, electric vehicle charging stations (EVCSs) powered by renewable energy must adopt market-driven approaches to stay competitive. The unpredictable nature of renewable energy production poses major challenges for strategic planning. To tackle the uncertainties stemming from forecast inaccuracies of renewable energy, this study introduces a peer-to-peer (P2P) energy trading strategy based on game theory for solar-hydrogen-battery storage electric vehicle charging stations (SHS-EVCSs). Firstly, the incorporation of prediction errors in renewable energy forecasts within four SHS-EVCSs enhances the resilience and efficiency of energy management. Secondly, employing game theory’s optimization principles, this work presents a day-ahead P2P interactive energy trading model specifically designed for mitigating the variability issues associated with renewable energy sources. Thirdly, the model is converted into a mixed integer linear programming (MILP) problem through dual theory, allowing for resolution via CPLEX optimization techniques. Case study results demonstrate that the method not only increases SHS-EVCS revenue by up to 24.6% through P2P transactions but also helps manage operational and maintenance expenses, contributing to the growth of the renewable energy sector.

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Section: Introductionmentioning

confidence: 99%