Agent-based community coordination of local energy distribution

The diminishing availability of fossil fuels will necessitate a shift toward renewable energy resources to supply vital electrical energy needs in the future. Two abundant renewable energy sources, solar and wind, are increasingly cost-competitive and also offer the potential of decentralized, and hence more robust, sourcing. However, the intermittent nature of solar and wind power can present difficulties in connection with integrating them into the main electric power grid. In this paper, we present an agent-based architecture for coordinating locally connected micro-grids, thereby supporting more cost-effective integration into the main power grid. These interconnected micro-grids, with renewable energy sources and energy storage devices, employ agents so that each micro-grid can choose to save or resell its stored energy in an open market in order to optimize its utility and costs. We show via simulation experiments how the micro-grid agent society operates and adapts under varying conditions of renewable energy availability and energy demand patterns. Such a system provides not only financial advantages but also local autonomy and a more robust energy distribution. In addition, these interconnected agents can also facilitate the reduction of carbon emission. In this connection, we compare five different micro-grid energy trading strategies. Thus, the experimental design and evaluation are motivated by a policy modeling perspective whereby the utility of an energy policy to a community (i.e., the strategy) is computed based on two attributes, the financial gain and the reduction in carbon emissions. Further, by means of “what-if” analysis, different energy policies that can potentially be employed by a community are compared against one another. Also, the implications of these policies for a community are discussed.