Browsing by Author "Debbarma, Sophia"

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    Day ahead Demand Side Management using Firefly Algorithm
    (Department of Electrical Engineering, NITS, 2019) Debbarma, Sophia
    With the increase in the number of electrical gadgets and appliances, the demand for electricity has also increased, it is now very important to emphasize in the concept of demand side management to meet the required demand of electricity. DSM assures efficient use of available energy resources. DSM along with smart grid allows the consumer to have details of power consumption information and allows the suppliers to lower the overall load demand during the peak period and modify the load curve. Necessary data of the energy consumption and price have been taken from different papers. In this research work, the primary aim is to mainly lower the overall load demand and thus the operational cost and utility bills. The work is done in different areas – residential, commercial and industrial. To get the optimized result, Meta-heuristic algorithm was developed to minimize the problem. Because of the flexibility, gradient free mechanisms and local optima avoidance of the algorithms, meta-heuristic techniques is gaining popular. Calculation of derivative of search space is not required in meta-heuristic technique making it highly flexible for solving a diverse range of problem. The evolutionary algorithms used to solve the demand side management problem is Particle Swarm Optimization, Firefly Algorithm and Salp Swarm Algorithm. The three algorithms is used to obtain the objective of the project work in three different area- residential, commercial and residential area. Firefly algorithm is found out to provide the best cost as compared to other two algorithm PSO and SSA. Firefly Algorithm is able to provide better accuracy.