This paper presents a novel decentralized bi-level stochastic optimization approach based on the progressive hedging algorithm for multi-agent systems (MAS) in multi-energy microgrids (MEMGs) to enhance network flexibility. In proposed model, suppliers and consumers of three energy carrier power, heat, hydrogen are considered. system further consists storage such as plug-in electric vehicle agg...

This paper presents a microgrid stability controller (MSC) in order to provide existing distributed generation units (DGs) the additional functionality of working in islanding mode without changing their control strategies in grid-connected mode and to enhance the stability of the microgrid. Microgrid operating characteristics and mathematical models of the MSC indicate that the system is inher...

Island operation of a microgrid increases operation survivability and reliability when there is a large accident in a main grid. However, because a microgrid typically has limited generation capability, a microgrid operator (MGO) has to take the risk of island operation into account in its market participation and generation scheduling to ensure efficient operation. In this paper, a microgrid i...

This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-do...

Integrated monitoring and control of energy storage and other generating sources and loads in microgrids are important to ensure full realization of the benefits of energy storage. This paper describes ongoing projects at the University of California – San Diego (UCSD), 42 MW microgrid that integrates energy storage and associated monitoring and control. The UCSD microgrid power distribution sy...

The multi-directional flow of energy in a multi-microgrid (MMG) system and different dispatching needs multiple sources time location hinder the optimal operation coordination between microgrids. We propose an approach to centrally train all agents achieve coordinated control through individual attention mechanism with deep dense neural network for reinforcement learning. novel allow each agent...

This paper intended to control a DC microgrid in islanded operation mode using decentralized power management strategies. The DC microgrid under study included a wind turbine generator (WTG), photovoltaic (PV), battery energy storage system (BESS) and dc constant power load. According to the newly proposed strategy, each of distributed generation sources of energy and battery energy storage sys...

In this paper, an economic dispatch model with probabilistic modeling is developed for a microgrid. The electric power supply in a microgrid consists of conventional power plants and renewable energy power plants, such as wind and solar power plants. Because of the fluctuation in the output of solar and wind power plants, an empirical probabilistic model is developed to predict their hourly out...