Abstract

Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control &#x0028 AGC &#x0029 with diverse renewable sources and a modified-cascaded controller are presented in the paper. Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution &#x0028 hITLBO-DE &#x0029 algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative &#x0028 PID &#x0029, integral double derivative &#x0028 IDD &#x0029 and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change. The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5&#x0025 of the connected load and robustness analysis is shown by modifying essential factors simultaneously by &#x2213 30&#x0025. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.

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