scholarly journals MVO-PS Optimized Hybrid FOFPID Controller for Load Frequency Control of an AC Micro-Grid System

2019 ◽  
Vol 8 (2) ◽  
pp. 3805-3812 ◽  

This paper proposes a new approach for load frequency control in a multi micro grid system by using hybrid multi verse with pattern search (hMVO-PS) algorithm based Fractional Order Fuzzy PID controller. A multi micro grid system may be molded by some of the renewable resources (RESs) like photovoltaic (PVs), wind (WTGs), energy storage system (ESSs) and loads. The fractional order fuzzy PID (FOFPID) controller parameters are optimized by novel hybrid Multi verse with pattern search (hMVO-PS) technique. The flexibility and robustness of proposed FOFPID controller is inspected under different disturbance like stochastic variations. The superiority of FOFPID structure over conventional Fuzzy PID/PID and hMVO-PS technique over multi verse optimization (MVO), particle swarm optimization (PSO) and genetic algorithm (GA) has been manifested

2020 ◽  
Vol 17 (5) ◽  
pp. 675-686
Author(s):  
Sonalika Mishra ◽  
Suchismita Patel ◽  
Ramesh Chandra Prusty ◽  
Sidhartha Panda

Purpose This paper aims to implement a maiden methodology for load frequency control of an AC multi micro-grid (MG) by using hybrid fractional order fuzzy PID (FOFPID) controller and linear quadratic Gaussian (LQG). Design/methodology/approach The multi MG system considered is consisting of photovoltaic, wind turbine and a synchronous generator. Different energy storage devices i.e. battery energy storage system and flywheel energy storage system are also integrated to the system. The renewable energy sources suffer from uncertainty and fluctuation from their nominal values, which results in fluctuation of system frequency. Inspired by this difficulty in MG control, this research paper proposes a hybridized FOFPID and LQG controller under random and stochastic environments. Again to confer viability of proposed controller its performances are compared with PID, fuzzy PID and fuzzy PID-LQG controllers. A comparative study among all implemented techniques i.e. proposed multi-verse optimization (MVO) algorithm, particle swarm optimization and genetic algorithm has been done to justify the supremacy of MVO algorithm. To check the robustness of the controller sensitivity analysis is done. Findings The merged concept of fractional calculus and state feedback theory is found to be efficient. The designed controller is found to be capable of rejecting the effect of disturbances present in the system. Originality/value From the study, the authors observed that the proposed hybrid FOPID and LQG controller is robust hence, there is no need to reset the controller parameters with a large change in network parameters.


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