서강대학교

초록/요약

Due to uncertainties of renewable generation, optimal decision making of energy transaction for multiple microgrids is a chllenging task. In this thesis, we present a transaction-based optimal power flow (OPF) mechanism to address the microgird energy transaction problem. Specifically, the proposed technique is based on using predictor corrector proximal multiplier (PCPM) algorithm and naive auction algorithm. We propose that microgrid agents participating in the market estimate optimal power flow using PCPM algorithm and determine transation price using naive auction algorithm. Using OPF to optimally determine diesel generation and renewable resources as power sources is a promising approach to minimize operational cost in distributed networks. Then, the agents of microgrids determine transaction price using naive auction algoritm in auction agent (AA) stage. In addition, insufficient/remaining power of each microgrids is traded at different price from the main grid. The proposed mecahnism produces energy scheduling within each microgrid and decides transaction price across multiple microgrids. The mechanism is implemented in MATLAB using CVX. The proposed mechanism is scalable and can be used for other type of microgrid.