Solving Unit Commitment Problem with Wind Solar based Power System Network using SCA Algorithm

One of the most difficult problems in power system optimization research is the unit commitment (UC) issue. The current study effectively reduced emissions and generating costs in the UC problem by applying the Sine Cosine algorithm (SCA) technique. The traditional IEEE 30 bus network and its modified versions with the addition of renewable energy sources (RESs) (wind, PV) are the test systems under consideration. The proper probability density function is used to manage the uncertainty inherent in RESs (wind, PV).The results obtained by SCA are contrasted with those obtained using Particle Swarm Optimization (PSO) and Biogeography based optimization (BBO) technologies. It shows that using SCA has proven to be more effective than using BBO and PSO in achieving the goals. Statistical analysis such as the ANOVA test has been used to quantify the superiority of SCA. This study also shows quantitative proof of the clean air and economic advantages of RES deployment in conventional power networks.