Hybrid Intelligence Strategy for Techno-Economic Reactive Power Dispatch Approach to Ensure System Security

Abstract

This work consolidates chaotic maps into a contemporary heuristic approach called Chimp Optimization Algorithm (COA). Augmentation of ten chaotic maps to COA forms the hybrid Chaotic COA (CCOA) which generates solutions in search space with enhanced mobility. A bi-level strategy of validating the robustness of the proposed hybrid method is adopted by first benchmarking it on eighteen assorted benchmark test functions and later by performing statistical analysis. The result obtained candidly establishes that merging of chaotic maps (dominantly Chaotic 4 Iterative type-CCOA4) enhances the performance of COA. The inferences congregated from the benchmark functions and statistical analysis facilitates the application of the recommended algorithm to obtain techno-economic solution in reactive power dispatch (RPD) problem which is manifested as a challenging issue in power system operation. The RPD problem is analyzed implementing the proposed approach with series-shunt compensation in a competitive electricity market for secured operation and the proposed Iterative type-CCOA4 reduces the total operating cost by 3.3450 × 103$ with respect to initial operating cost.