FUZZY INFERENCE BASED STABILITY OPTIMIZATION FOR IOT DATA CENTERS DC MICROGRIDS: IMPACT OF CONSTANT POWER LOADS ON SMART GRID COMMUNICATION OVER THE POWERLINE

Abstract

Direct Current (dc) microgrids due to their efficiency and energy savings are being deployed to provide power for servers in Internet of Things (IoT) data centers, in more electric aircrafts (MEA), electric ships and in rail systems round the word. In this paper, Takagi-Sugeno fuzzy inference method is used to establish a Lyapunov stability candidate for a 380 V ring bus dc microgrid modeled with Matlab. To determine suitability of using powerline communication (PLC) to monitor stability condition on the 380 V dc microgrid, impact of distortion caused by microgrid constant power loads (CPL) on signals transmitted over the dc microgrid PLC channel is examined. It is shown in this paper that while Lyapunov asymptotic stability is maintained on the dc bus, increasing CPL on the microgrid causes the dc microgrid PLC channel to experience growing signal distortion.