SMART GRID COST OPTIMIZATION USING GENETIC ALGORITHM

Formerly, energy had been inexpensive and management of energy was efficient and was limited to elementary considerations. In the current scenario, due to a rapid increase in demand, complexity of the electrical network, probability of contingency and electricity cost have equally increased. In the recent past, Smart Grids are proven to be the best way to minimize these problems in an easier and smart way. Smart grid is defined as an electric network which has information technology fused to it. This paper proposes a way to reduce the total electricity cost in a smart grid using Genetic Algorithm. The system considered has renewable energy and battery banks apart from the grid to meet the demand. Short term time averaged electricity cost is formulated as an objective for optimization by GA with discharge of battery, energy from the grid to charge battery and meet load etc. as decision variables. The optimization problem is run for a 24 hours data of renewable input, real-time electricity price and load using MATLAB software; and the obtained results are furnished