A Hybrid Water Cycle Algorithm-Least Square based Framework for Robust Estimation of

Abstract

 

The power quality is becoming an extensively addressing aspect of power system because of sensitive operation of smart grid, awareness of power quality and modern power system equipment. This paper proposes a new hybrid framework of Water Cycle Algorithm-Least Square (WCA-LS) for estimation of harmonics present in time varying noisy power signals. Water Cycle Algorithm (WCA) is a population based algorithm which realizes the concepts of exploitation and exploration to find global optimal in search space under consideration. This algorithm exploits the concept of natural hydrologic cycle to perform heuristic optimization. In hydrologic cycle water flow in the form of streams, rivers and sea. When the rain falls from clouds and snow melts from glaciers, water flows downhill in the form of streams. When streams combine at one point they generate rivers which ultimately fall into the sea. Water from lakes is evaporated and the trees also transpire the water during photosynthesis process into atmosphere to generate clouds. These clouds release water back to the earth in the form of rains and precipitation to complete the cycle. The Proposed approach has been applied on test system from literature and results prove the effectiveness of technique in terms of precision and computational time. Results are further authenticated by estimating harmonics of real time voltage waveform of Axial Flux Parmanent Magnet Synchronous Generator (AFPMSG). The proposed WCA-LS delivers promising results compared to some of the state of art frameworks such as Genetic Algorithm (GA) and Particle Swarm Optimization with Passive Congregation based Least Square (PSOPC-LS).