Multiagent-Based Distributed-Energy-Resource Management for Intelligent Microgrids

Abstract

Microgrid is a combination of distributed generators, storage systems and controllable loads connected to low voltage network that can operate either in grid connected or in island mode. High penetration of power at distribution level creates such multiple microgrids. This paper proposes a two level architecture for distributed energy resource management for multiple microgrids using multi agent systems (MAS). In order to match the buyers and sellers in the energy market, symmetrical assignment problem based on naïve auction algorithm is used. The developed mechanism allows the pool members such as generation agents, load agents, auction agents, grid agents and storage agents to participate in market. Three different scenarios are identified based on the supply-demand mismatch among the participating microgrids. At the end of this paper two case studies are presented with two and four interconnected microgrids participating in market. Simulation results clearly indicate that the agent based management is effective in resource management among multiple microgrids economically and profitably.

Reviewing Microgrids from a Multi-Agent Systems Perspective

“…In conclusion, we can observe that the cited works utilize an agent platform implementation to develop their MAS, being JADE the most used (see [15,18,19,[21][22][23][24]). However, we consider that the reviewed works do not make an extensive use of the key features of agent technology in the context of Microgrids:…”

“…Kumar Nunna and Doolla [21] propose a MAS architecture for modeling the electricity market and implements a prototype using JADE. Agents are distributed in two levels: field level, to manage individual micro-grids to match the supply and demand, and market level, to cater the trading among the Microgrids and with the grid.…”

Gestión Óptima de la Potencia Eléctrica en una Microgrid Conectada, basada en el Algoritmo Genético para Optimización Multiobjetivo MOGA

“…En particular, uno de estos retos es la gestión de potencia eléctrica [9] y la complejidad que implica es mucho mayor si se involucran diferentes fuentes de energía, dispositivos de almacenamiento y cargas controlables.…”

Ancillary service provision by demand side management: A real-time power hardware-in-the-loop co-simulation demonstration

“…It exploits the capability of multi-agent system framework to implement scalable, distributed, complex and open Information and Communication Technology infrastructures. In a multi-agent based environment, theoretically, multiple software agents interact and negotiate to reach a common system goal while preserving their local goal [19][20][21]. Similarly, in a PM cluster, the interest of each device, either producing or consuming electricity, is represented by a device agent.…”