Hybrid ITLBO-DE Optimized Fuzzy PI Controller for Multi-area Automatic Generation Control with Generation Rate Constraint
The paper projects the gains of a fuzzy controller with its parameter being tuned by the hybrid improved teaching learning based optimization and differential evolution (hITLBO-DE). The foremost apprehension with the operation of AGC is satisfying equivalence of generation and gross demand with reference to a system. The frequency and the interline exchange have to be maintained for a stable and reliable operation of the system. The prime motive addressed in this chapter is to scheme a profligate and accurate controller with ability to sustain the frequency for the power system within nominal operating limits. A two-area reheat thermal system with generation rate constraint is considered, and a fuzzy logic with proportional integral controller is included for the enhanced operation in control of the governor and system response. The comparison of the obtained response for the hITLBO-DE to particle swarm optimization (PSO), pattern search (PS) and recently published results with hPSO-PS technique gives a clear view of the improvement in the system response.
KeywordsAutomatic generation control (AGC) Fuzzy PI controller Hybrid improved teaching learning based optimization and differential evolution (hITLBO-DE)
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