Analyzing Multi-Objective Combined Heat and Power Integrated with Wind-Solar for Optimal Power Flow Problem

This study uses the chaotic oppositional driving training based optimization (CODTBO) algorithm to depict a new approach to combined heat power economic dispatch systems. Primarily concerned with reducing emissions. Chaotic oppositional based learning has been incorporated with DTBO to enhance the exploration and exploitation phenomenon of the proposed technique. This phenomenon helps to increase the searching ability of the proposed technique. Initially combined heat and power (CHP) has been incorporated with IEEE 57 bus for test system I. Furthermore wind and solar energy integrated with IEEE 57 bus system as a renewable energy source in this suggested test system II. In order to properly optimize the CHPED, solar and wind energy are already taken into consideration a lot. This indicates that the system is both cost-effective and environmentally beneficial. Future non-renewable resource scarcity is a very important issue. The process of generating electricity also pollutes our atmosphere. This project aims to lessen those issues. The viability and efficacy of comprehending the aforementioned scenario accurately were demonstrated by numerical data.