用智能代理框架让电网韧性建设既能抗灾又赚钱。
Agentic-AI based Mathematical Framework for Commercialization of Energy Resilience in Electrical Distribution System Planning and Operation
- 双代理强化学习动态优化分布式能源开关配置。
- 10轮测试中韧性得分0.85，投资回报比达0.12。
- 兼顾灾时恢复速度与市场盈利，适合电力运营商参考。
极端天气和网络攻击使配电系统日益脆弱，现有技术多关注韧性指标，却缺乏市场化机制推动韧性投资。传统优化方法难以适应常态与应急场景变化。本文提出融合双代理近端策略优化（PPO）与市场机制的新框架，通过战略代理选择最优分布式能源驱动的开关配置，战术代理在预算与天气约束下微调开关状态。在自建动态仿真环境中，模拟随机灾害事件、预算限制与韧性-成本权衡。设计综合奖励函数，平衡韧性提升与市场收益（最高200倍激励），使灾时85%动作选择含4个分布式能源的配置。10轮测试中，平均韧性得分为0.85±0.08，效益成本比为0.12±0.01，证明了可持续的市场激励机制。该框架为配电系统规划与运行提供了可商业化韧性增强路径。
原文摘要 · Abstract (English)
The increasing vulnerability of electrical distribution systems to extreme weather events and cyber threats necessitates the development of economically viable frameworks for resilience enhancement. While existing approaches focus primarily on technical resilience metrics and enhancement strategies, there remains a significant gap in establishing market-driven mechanisms that can effectively commercialize resilience features while optimizing their deployment through intelligent decision-making. Moreover, traditional optimization approaches for distribution network reconfiguration often fail to dynamically adapt to both normal and emergency conditions. This paper introduces a novel framework integrating dual-agent Proximal Policy Optimization (PPO) with market-based mechanisms, achieving an average resilience score of 0.85 0.08 over 10 test episodes. The proposed architecture leverages a dual-agent PPO scheme, where a strategic agent selects optimal DER-driven switching configurations, while a tactical agent fine-tunes individual switch states and grid preferences under budget and weather constraints. These agents interact within a custom-built dynamic simulation environment that models stochastic calamity events, budget limits, and resilience-cost trade-offs. A comprehensive reward function is designed that balances resilience enhancement objectives with market profitability (with up to 200x reward incentives, resulting in 85% of actions during calamity steps selecting configurations with 4 DERs), incorporating factors such as load recovery speed, system robustness, and customer satisfaction. Over 10 test episodes, the framework achieved a benefit-cost ratio of 0.12 0.01, demonstrating sustainable market incentives for resilience investment. This framework creates sustainable market incentives
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