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In this paper, an agent based intelligent energy management system is proposed to facilitate power trading among microgrids and allow customers to participate in demand response. The proposed intelligence uses demand response, and diversity in electricity consumption patterns of the customers and availability of power from distributed generators as the vital means in managing power in the system. A new priority index is proposed for customers participating in the market based on frequency and size of load participating in demand response. In order to validate the proposed method, a case study with two interconnected microgrids is simulated. Based on extensive simulation results of the system developed using Java Agent DEvelopment framework (JADE), it has been found that multi-agent based demand response is successful in reducing the system peak in addition to cost benefit for the customers with high priority index.Index Terms-Demand response, demand side management, energy markets simulation, microgrids, multiagent systems, smart distribution system.

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.

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