Bi-Directional Optimization of V2G Strategy Based on Multi-Objective Optimization: Balancing Grid Load and Reducing Electric Vehicle Charging Costs
DOI:
https://doi.org/10.61173/75xhcx48Keywords:
V2G, Peak Shaving and Valley Filling, Multi-objective Optimization, Time-of-Use Pricing StrategyAbstract
With the rapid increase in the number of electric vehicles (EVs), vehicle-to-grid (V2G) technology plays a vital role in reducing the burden on the power system. This technology optimizes network load distribution through a two-way charging mechanism and effectively alleviates network load fluctuations. However, potential negative impacts on EV battery life should also be a cause for concern. Furthermore, the technology does not fundamentally change the charging behavior of electric vehicles. Against this background, this study proposes a multi-objective optimization strategy to adapt electricity price policy to network load fluctuations to control charging behavior. This strategy optimizes battery attenuation, charging costs, and network load fluctuations, aiming to alleviate network load fluctuations while completely solving user concerns about charging and battery maintenance costs. Simulation analysis has verified the effectiveness of this model in reducing grid load fluctuations and balancing user costs.
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