Abstract
This article presents a new meta-heuristic algorithm optimized secondary controller called Integral minus Tilt-Derivative (I-TD) for automatic generation control of three area multi-source system. Area-1 comprises of thermal and solar thermal units, area-2 comprises of two thermal units and area-3 comprises of thermal and wind systems. Comparison of system responses using proposed I-TD controller and some other commonly used controller revels better dynamics characteristics of the proposed one. Dynamic responses of the system corresponding to various meta heuristic optimization technique like firefly algorithm (FA), grey-wolf optimization (GWO), grass-hopper algorithm (GHA) explore that GHA provides slightly better dynamics than the other and also converges faster. Further, sensitivity analysis suggests that system dynamics with GHA optimized I-TD controller at various loading conditions are robust and are not reset again.
Highlights
Automatic generation control (AGC) is defined as the method of suppressing deviations in frequency and tie-line power interchange between the control-areas
The controller parameters are optimized by the grasshopper algorithm (GHA) and the optimum value are presented in Table 1. (a)
From the convergences curve in Figure 5. (d) and value of JISE in Table 2. (b) reveals that the GHA converge faster with less JISE value than others. This validates that the obtain optimal value of controller parameters with GHA is more efficient than other optimization techniques
Summary
Automatic generation control (AGC) is defined as the method of suppressing deviations in frequency and tie-line power interchange between the control-areas. The applications of GHA optimization technique in multi-area multisource AGC system with solar-thermal, thermal and wind systems are not found. The application of GHA in AGC can be extended to perform sensitivity analysis at different loading conditions with I-TD controller. Maiden Application of Meta-Heuristic Techniques with Optimized Integral minus Tilt-Derivative Controller for AGC of Multi-area Multi-Source System evolutionary algorithms such as FA, GWO, and GHA and in order to find the best optimization technique. Maiden Application of Meta-Heuristic Techniques with Optimized Integral minus Tilt-Derivative Controller for AGC of Multi-area Multi-Source System evolutionary algorithms such as FA, GWO, and GHA and in order to find the best optimization technique. d) To perform a sensitivity analysis of the best controller under different loading conditions
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