Power Management for Hybrid Energy Systems Using Droop Control

Abstract

The aim of this work is to develop a strategy of power flow during variable loading conditions because the load is stochastic in nature. Fluctuations of load can affect the supply frequency and thus can affect the reliability and quality of power supply. Here comes a need of controller to compensate this effect and maintain supply reliability and proper power flow. In this work, a power management strategy using artificial neural network (ANN) controller as a droop control is proposed. To obtain the desirable power management among the generation, load, and storage system, a droop control via ANN control scheme has been utilized. Droop characteristics scheme is employed to minimize the frequency deviation (∆f) and power fluctuations from WTG and DG. In this work, the used micro-grid (MG) system basically consists of distributed power generation (PG), i.e., wind turbine generator (WTG), diesel engine generator (DG), and a battery is being used as energy storage system (ESS). This work contributes among the field of power flow control for MG system, and the proposed methodology resolves the issue of frequency control. Finally, a comparative analysis is also performed between ANN and PID-based control schemes.KeywordsDroop controlArtificial neural network (ANN)Micro-grid (MG) systemPID controlFrequency control