Application of Artificial Intelligence to Reduce Conventional LFC Capacity in Utility Grid Using Multiple Interconnected Microgrids
摘要
Operating reserves, with the particular subclass of secondary reserves, are one type of ancillary services and fundamental in dealing with disturbances of power system. Operating reserves are an essential component of utility grid to keep electric network stability and reliability. This paper deals with the design of an optimal active power management and Load Frequency Control (LFC) in microgrid including distributed generations (DGs) and hybrid energy storage system (HESS). The investigated microgrid was operated in isolated and grid-connected modes. The proposed strategy involves a multi-stage regulation scheme with optimal combined cascade Proportional-Derivative-Fuzzy-Proportional-Integral-Derivative controller with filter (PD-Fuzzy-PIDN). At the first stage, only the load frequency loop is used to cope with fluctuations, then at the second stage, the hybrid storage system will be activated to support the LFC loop in coordination with the Tie-Line power flow transmission control. The HESS storage system was employed to ensure an optimal power management in presences of DGs for reducing the conventional LFC ability. In doing so, a novel bio-inspired meta-heuristic optimization approach called Artificial Hummingbird Algorithm (AHA) has been used to fine tune the controller parameters. To promote the use of renewable energy sources (RESs) and minimize the use of fuel by reducing the LFC capacity, a novel method have been proposed by using the surplus power of the distributed generations in the microgrid. To prove the effectiveness and superiority of the proposed strategy, various scenarios have been performed and compared.