Solution of hybrid energy based dynamic economic emission dispatch problems using chaos assisted arithmetic optimization algorithm

With the substantial environmental depletion, one of the most important steps toward minimizing the carbon footprints is the integration of the renewable source of energy, for instance, wind or solar to the existing conventional generators. In this proposed work, the existing problems of conventional thermal scheduling like excessive generation cost and additional emissive components of fuel are minimized by incorporating renewable energy sources with the conventional thermal generating units. This paper proposes a thermal-solar-wind-battery (TSWB) integrated system model for 24 hourly hybrid dynamic economic emission dispatch (HDEED) generation scheduling. Here, fruitful performance of minimum cost-emission oriented TSWB system has been inspected by using chaos based arithmetic optimization algorithm (AOA) (CAOA). Chaos has been used in order to improve the exploration capability, large-scale complex problem handling and to deal with highly volatile nature of HDEED. Four test systems of different scales having six, thirty, forty and eighty thermal generators in the TSWB integrated system are used to test the proposed approach. Tested result shows that both the operating costs and pollutant emissions drop down up to 9% and 31%, respectively. Obtained results are compared with particle swarm optimization algorithm, backtracking search algorithm and Squirrel search algorithm which establishes the superiority of the CAOA.