Modelling and Load Frequency Control (LFC) Design of Microgrid Frame-worked As Technological Norm to Multi Energy System (MES)

In today's world, the trend of using renewable energy sources as an alternative energy source is becoming more and more common due to various driving factors, such as energy scarcity (fossil fuel depletion, etc.) and environmental issues (carbon footprint). This trend is leading to a steady increase in the penetration of renewable energy sources (RESs) through microgrid (MG), which is formed from combination of various distribution energy sources (DERs). The inherent intermittent nature of RESs coupled with abrupt load changes can instigate sustained frequency fluctuations and can keep the frequency deviation out of the allowable range that leads to an increased uncertainty and instability in operation with possible collapse of the microgrid (MG) system. Hence, an independent MG operation needs to ensure disruption minimization to the energy supply and critical loads. Accordingly, a detailed and continuously improved control solution is required for stability and operation uncertainty reduction reasons. In this thesis, an advanced LFC scheme using a particle swarm optimization (PSO) optimized balanced reduced-order linear quadratic Gaussian/linear quadratic integrator (LQG/LQI) control scheme is proposed for autonomous microgrid frame-worked to accommodate a multi-energy system (MES), which integrates diverse energy resources and technologies, where this work has also targeted to build on multi-energy system (MES) requirements by introducing holistic approaches that provide 1) better, 2) accurate, and 3) comprehensive dynamic frequency response models for the microgrid components. The effectiveness of the proposed control scheme is validated through MATLAB®/SIMULINK simulations and comparative analysis with other control schemes under various scenarios, which range from distinct load disturbance to combined random disturbance input profiles of all RESs and RESs modeled with virtual inertia (VI). A proportional-integral-derivative (PID) particle swarm optimization (PSO)-tuned and an interval type 1 (IT1) fuzzy controller are the two other control schemes that are used for performance comparison analysis with the proposed controller. The simulation results demonstrated better frequency control performance for the proposed control scheme over the other two types of control schemes. The proposed advanced control scheme also guarantees fast settling time of frequency transients and improves dynamic response and exhibits high resilience to severe stochastic loads and active power disturbances for the subject microgrid.