Multi-objective Optimization of Energy Consumption in Microgrids Considering CHPs and Renewables Using Improved Shuffled Frog Leaping Algorithm

In this paper, a consistent framework to optimize the energy consumption in microgrids (MGs) with the presence of Distributed Energy Resources (DERs) such as Wind Turbines, Photo-Voltaic arrays, Combined Heat and Power, Fuel Cell, Boiler and Batteries is presented, in which battery owners can use them both in battery to grid and grid to battery (G2V). Since the time of use electricity tariff is higher than charging rate pricing, the batteries are due to discharge their energy to the loads and otherwise, the DERs such will supply the batteries and the rest of demands. The load uncertainties and renewable energy probability of production modeled with different probability densities through Beta, Weibull distribution functions with suitable coefficients and information gap decision theory, are going to be modeled and solved using the Improved Shuffled Frog Leaping Algorithm (ISFLA). In this way, the best sets of distributed energy resources in MGs are chosen. The results comparison of the proposed method with the existing methods has verified the superiority of ISFLA method to solve this optimization problem in IEEE 33 and 69 bus test systems.