Integrating demand forecasting and deep reinforcement learning for real-time electric vehicle charging price optimization

IF 4.4 3区经济学 Q3 ENERGY & FUELS

Utilities Policy Pub Date : 2025-08-28 DOI:10.1016/j.jup.2025.102038

Monowar Mahmud , Tarek Abedin , Md Mahfuzur Rahman , Shamiul Ashraf Shoishob , Tiong Sieh Kiong , Mohammad Nur-E-Alam

引用次数: 0

Abstract

The rapid growth of electric vehicles (EVs) demands efficient, grid-friendly charging systems. This study introduces a dynamic pricing framework combining short-term demand forecasting and deep reinforcement learning. Using Adaptive Charging Network (ACN) data, XGBoost predicts charging demand accurately (R² = 0.84, MAE = 0.45 kW). Compared to a uniform rate applied to all charging usage, set at 0.15 USD/kWh across all hours, with no adjustment for system demand conditions or time-of-day, the optimized strategy enhanced total daily revenue by 133 % and diminished load variance by 72.37 %. The PPO agent also surpassed traditional Time-of-Use and demand-based pricing models by 67–94 %, while ensuring pricing stability with a price standard deviation of 0.132 USD/kWh. The simulation results illustrate the framework's efficacy in facilitating off-peak charging and improving grid reliability.

查看原文本刊更多论文

集成需求预测和深度强化学习的电动汽车充电价格实时优化

电动汽车（ev）的快速增长需要高效、电网友好的充电系统。本研究引入了一个结合短期需求预测和深度强化学习的动态定价框架。XGBoost利用自适应充电网络（ACN）数据，准确预测充电需求（R2 = 0.84, MAE = 0.45 kW）。与适用于所有充电使用的统一费率（在所有时间内设置为0.15美元/千瓦时，不根据系统需求条件或一天中的时间进行调整）相比，优化后的策略使每日总收入增加了133%，负载差异减少了72.37%。PPO代理也比传统的基于使用时间和需求的定价模型高出67 - 94%，同时确保了价格的稳定性，价格标准差为0.132美元/千瓦时。仿真结果表明了该框架在促进非峰充电和提高电网可靠性方面的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Utilities Policy ENERGY & FUELS-ENVIRONMENTAL SCIENCES

CiteScore

6.80

自引率

10.00%

发文量

审稿时长

66 days

期刊介绍： Utilities Policy is deliberately international, interdisciplinary, and intersectoral. Articles address utility trends and issues in both developed and developing economies. Authors and reviewers come from various disciplines, including economics, political science, sociology, law, finance, accounting, management, and engineering. Areas of focus include the utility and network industries providing essential electricity, natural gas, water and wastewater, solid waste, communications, broadband, postal, and public transportation services. Utilities Policy invites submissions that apply various quantitative and qualitative methods. Contributions are welcome from both established and emerging scholars as well as accomplished practitioners. Interdisciplinary, comparative, and applied works are encouraged. Submissions to the journal should have a clear focus on governance, performance, and/or analysis of public utilities with an aim toward informing the policymaking process and providing recommendations as appropriate. Relevant topics and issues include but are not limited to industry structures and ownership, market design and dynamics, economic development, resource planning, system modeling, accounting and finance, infrastructure investment, supply and demand efficiency, strategic management and productivity, network operations and integration, supply chains, adaptation and flexibility, service-quality standards, benchmarking and metrics, benefit-cost analysis, behavior and incentives, pricing and demand response, economic and environmental regulation, regulatory performance and impact, restructuring and deregulation, and policy institutions.