Real Power Control of Storage Free Hybrid Microgrid

Abstract

A smart microgrid should be well equipped with an efficient power flow control mechanism so that the consumer may use renewable energy sources in more economical way to reduce the use of fossil fuel based conventional sources. Control of power flow and frequency in a hybrid microgird in islanded mode is different compared to the same while operating in grid-connected mode. The proposed scheme presented in this thesis is an effort to show the spinning reserve effect of Solar Photovoltaic (SPV) generator in storage free Diesel-SPV based hybrid microgrid. It is proposed that maximum utilization of reserve power of SPV generator in to dc load is possible by using Neural Network Back Propagation Algorithm (BPA). This is an algorithm for coordinated control strategy of Diesel Engine (DE) and SPV generator. This thesis is also an effort to suggest an Adaptive Neuro fuzzy Inference (ANFI) Logic based control system having variable reference input which makes it able to model uncertain and non-linear conditions. To show the virtual inertia effect of SPV generator an ANFI based controller is proposed which can coordinate the control scheme of SPV and DE based hybrid microgrid having both AC and DC loads. The above two proposed control strategies facilitate efficient energy management which controls the individual power flow of SPV generator and DE to fulfill the real power demand by Critical Load (CL). The operation and performance of the proposed controller are verified through simulation MATLAB package.