Optimal scheduling and energy management of a multi-energy
Abstract Multi-Energy Microgrids (ME-MGs) represent an integrated and advanced energy system, playing a vital role in delivering optimal and sustainable energy solutions in modern
Optimizing Economic Dispatch for Microgrid Clusters
To further enhance the efficiency of solving the economic dispatch model, this study combines chaotic mapping and dynamic opposition-based
AutoGrid AI: Deep Reinforcement Learning Framework for
Using deep reinforcement learning and time-series forecasting models, we optimize microgrid energy dispatch strategies to minimize costs and maximize the utilization of renewable
Diffusion-Modeled Reinforcement Learning for Carbon and Risk
With the growing integration of renewables and increasing system complexity, microgrid communities face significant challenges in real-time energy scheduling and optimization under uncertainty.
A multi-objective robust optimal dispatch and cost allocation model for
In this paper, a microgrid groups with shared hybrid energy storage (MGs-SHESS) operation optimization and cost allocation strategy considering flexible ramping capacity (FRC) is
Prediction and scheduling of multi-energy microgrid based on BiGRU
To predict renewable energy sources such as solar power in microgrids more accurately, a hybrid power prediction method is presented in this paper.
Microgrids as a Tool for Energy Self-Sufficiency
The scale of scientific interest in the area of distributed energy systems is clearly focused on microgrids, which are seen as the most versatile and scalable solution. The number of
Economic optimization scheduling of multi‐microgrid based on
By solving the two-layer model of multi-microgrid and single microgrid, the independent operation of each microgrid is guaranteed, and the decentralized autonomy and centralized coordinated
Stochastic energy management of a microgrid incorporating two
In this study, the stochastic energy management, and scheduling of a renewable microgrid involving energy sources and dynamic storage is performed considering energy resource
Optimizing sustainable energy management in grid connected
This study proposes a novel multi-objective optimization framework for grid-connected microgrids using quantum particle swarm optimization (QPSO) to address the dual challenges of