这篇论文用差分进化+多智能体强化学习搞定了奶牛场电池管理，比规则模型多赚18%，还合规电网。搞能源优化的值得一看。
爱尔兰奶业有巨大可再生能源整合潜力，但分布式发电控制研究主要集中在住宅和商业领域。该论文提出一种基于差分进化与多智能体深度强化学习的双层控制框架：上层使用动态定价，下层负责电池管理。在农村配电线路仿真中，该框架相比基于规则的模型将能源套利利润提升高达18%，同时增加了分布式发电利用率且未显著增加成本，并满足爱尔兰电网电压规范。
Multi-Agent Deep Reinforcement Learning for Multi Objective Battery Management in Dairy Farms
The dairy industry in Ireland has a large potential for the integration of renewable energy and the reduction of carbon emissions. However, researchers of distributed generation control are mainly focused on residential and commercial applications. To contribute to the effective integration of renewable energy in the dairy sector, this paper presents a multi-objective optimisation control system based on differential evolution and multi agent Deep Reinforcement Learning. The proposed control is organised in two layers: the upper layer uses dynamic pricing, and the lower layer is based on multi-agent reinforcement learning for battery management. This paper also simulates the electrical response of the proposed control system in a rural distribution circuit. The simulation results show that the proposed control framework can improve profits from energy arbitrage up to 18% compared to using Rule-based models, increase the use of distributed generation without significantly increasing cost, and comply with the Irish grid code in terms of voltage variation.