Abstract
With the increasing integration of distributed energy resources, demand response, microgrids, and automation technologies in modern distribution networks, a market framework for local energy trading among microgrids and the distribution utility is a reality. However, the expansion planning problem for active distribution networks (ADNs) with multiple microgrids is complex due to uncertainties associated with distributed generation and competitive scenarios. This paper proposes a novel data-driven distributionally robust model that considers energy trading and uncertainties in generation and load to solve the expansion planning problem for ADNs with multiple microgrids. The uncertainties are represented using data bins and their probabilities, and the energy trading strategy is modeled based on game theory. The proposed model enables the distribution system operator (DSO) to find the best expansion planning from their perspective, while each microgrid seeks its own benefits. We exemplify the proposed model using a modified version of the IEEE 123-bus test system. Results demonstrate the effects of surplus generation levels on the energy price strategy and the influence of competitive environments on the expansion planning decision. The proposed model provides a new approach to address the complexities associated with the expansion planning problem for ADNs with multiple microgrids and could have significant implications for the design and operation of future power systems.
Published Version
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