A Reinforcement Learning Approach for Optimal Control in
Microgrids (MGs) provide a promising solution by enabling localized control over energy generation, storage, and distribution. This paper presents a novel reinforcement learning (RL)-based
Stochastic optimal scheduling strategy for a campus-isolated microgrid
In this study, a pilot isolated microgrid system was set up comprising six teaching buildings, three dormitory rooms, one dining hall, and a central scheduling station.
Zhengmao Li''s Homepage
Planning and operation of integrated-energy systems: such as (islanded/grid-connected) microgrids, ships, seaports, smart buildings, etc., with integrated power, thermal, and gas networks.
Optimization model of microgirds operation based on potential game
Both distributed generations and electric load are requiring more individual autonomy of operation. In this paper, potential game theory is introduced to model the coordinated optimization of a standalone
A novel linear search-linear programming method for non-convex multi
Abstract Both the increased utilization of photovoltaic (PV) and the consequent expansion of energy storage, leading to higher costs, are critical factors in the development of a techno
Feedback Linearization Based Distributed Model Predictive Control for
In this paper, a distributed Model Predictive Control (DMPC) is proposed for the secondary voltage and frequency control of islanded microgrid, where each distributed generator
Federated Multi-agent Deep Reinforcement Learning for Multi
Dive into the research topics of ''Federated Multi-agent Deep Reinforcement Learning for Multi-microgrid Energy Management''. Together they form a unique fingerprint.
Design and realisation of a new multifunctional low-cost experimental
This paper mainly describes the current research status of laboratory microgrid, and designs the topology, specific functions and equipment protection of laboratory microgrid, and
Yuanzheng Li
This article investigates the load scheduling problem within a residential microgrid, where the microgrid operator is regarded as a trusted third-party that provides a limited information exchange for all
Dynamic Energy Management of a Microgrid Using Approximate
Zeng, Peng, Hepeng Li, Haibo He, and Shuhui Li. "Dynamic Energy Management of a Microgrid Using Approximate Dynamic Programming and Deep Recurrent Neural Network Learning."
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