Determining Optimal Arrangement of Distributed Generations in Microgrids to Supply Electrical and Thermal Demands using Improved Shuffled Frog Leaping Algorithm

Global warming and prices of energy carriers within political conflicts between different nations, are some of the problems for traditional energy production and economic dispatch. In traditional generation systems, about 25 percentage of energy is wasted, and the presence of Distributed Energy Resources (DERs) such as Photovoltaic, Wind Turbine and wind farms, Fuel Cell, and the Combined Heat and Power can reduce fuel consumption, pollution, transmission losses, and increase the microgrid productivity. In this paper, a complete energy management framework in a microgrid is proposed by considering the load distribution constraints using Improved Shuffled Frog Leaping Algorithm (ISFLA) algorithm, in which it determines the exact share of energy production or consumption for different units. The proposed scheme is used to select the best arrangement of DERs in the power grid, which the output of which is to determine the number and optimal location of DERs in the several bus-bars of the grid. Then, the Independent System Operator (ISO) determines the quantity of energy exchange and consumption by considering the load distribution constraints. Boilers and CHPs have also been used to maintain the balance between the production of thermal power by energy sources and thermal demands. In addition, the Demand Response Program has been used with the aim of smoothing the load curve and reducing the operating costs. Finally, the proposed method is implemented and simulated on the IEEE 69 and 118 bus systems using MATLAB, which comparing the output results with existing algorithms, shows the superiority of the proposed method.

Determining Optimal Arrangement of Distributed Generations in Microgrids to Supply Electrical and Thermal Demands using Improved Shuffled Frog Leaping Algorithm Keywords:

Demand Response , Energy market , Optimization , Distributed Energy Resources , Improved Shuffled Frog Leaping Algorithm