Intelligent Control Systems and Applications on Smart Grids

Abstract

This chapter discusses advances in intelligent control systems and their applications in Micro Energy Grids (MEG). The first section introduces a PID fuzzy model reference learning controller (FMRLC) implemented in the control loop of Static VAR Compensator (SVC) to stabilize the voltage levels in the islanded mode of the microgrid. FMRLC performance is compared to the conventional PI controller. The introduced results show that SVC with FMRLC has better capabilities to compensate for microgrid nonlinearity and continuous adaptation for dynamic change of the microgrid’s connected loads and sources. The second section discusses performance optimization of micro energy grid. A recent heuristic optimization technique, called Backtracking Search Optimization Algorithm (BSA), is proposed for performance optimization of micro energy grids with AC/DC circuits, where it is used for the selection of the scheme parameters of PWM pulsing stage used with a novel Distributed Flexible AC Transmission System (D-FACTS), type called Green Plug-Energy Economizer (GP-EE). The following section includes simulation models and results to illustrate the merits of the proposed intelligent control designs and their use to achieve high performance micro energy grids.