Renewable energy prosumers clustering towards target aggregated prosumption profiles based on recursive predictions

This paper introduces a decision making framework for aggregating Microgrids and/or other small energy producers and consumers (i.e. prosumers) into groups, whose purpose is to participate in liberalized electricity markets as single entities. The aggregator is able to offer aggregated Renewable Energy Source (RES) units to the wholesale market, in ways that are more efficient than individual prosumers acting alone. We first present the proposed framework and information flow among the involved market entities. We then focus on the problem of finding the set of prosumers whose aggregate prosumption profile can best fit a given target pattern requested by a market actor. We propose a linear autoregressive forecasting algorithm and a genetic clustering algorithm, which can easily adapt to the requirements set by the various use cases. Numerical results show that the aggregator can produce clusters in real time improving the average deviation from the target pattern by up to 50%.