Multi Objective Economic Dispatch Problem of Micro Grid with Integrated Vehicle to Grid (T-0430) (MFN 6207)

Abstract

The Power Economic Dispatch (PED) is the most important factor for the efficient operation and control of the power system. The PED is a problem related to the proper allocation of the available electrical power generating sources in order to meet the power demand at a minimized cost. Different conventional techniques are used to solve the PED problem by considering it as a conventional problem. The different conventional techniques used are Particle Linear Programming (LP), Lambda Iteration Method (LIM) and Dynamic Programming (DP) etc. The conventional techniques are not efficient enough to solve the complex PED problems. Different Artificial Intelligence (DAI) algorithms like particle Swarm Optimization (PSO), Artificial Neural Networks (ANN) and Fuzzy Logic etc. are also used to solve the non-convex PED problems. The complexity of the PED is also increased with the increased number of sources available for power generation in the power system. The addition of the Electric Vehicles (EVs) also increases the complexity of PED problem. Most of the optimization techniques used for PED does not consider the emission constraints of the available sources while solving the PED problem. The Multi Objective Economic Dispatch Problem (MOEDP) of a Micro-Grid (MG) is established in the proposed research in which the emission constraints of the power generating sources are also considered. The power generating sources included in the proposed MG are the Wind Turbines (WTs), Photovoltaic Cells (PVs), Diesel Engine (DE), Battery Storage (BS), Fuel Cells (FCs) and EVs. The micro-grid is connected to the main grid by the distribution lines and allowed bi-directional flow of power i.e. from main grid to MG and from MG to the main grid. The Artificial Algae Algorithm (AAA) using MATLAB is used to solve the PED problem in the proposed research and the results are compared with the other optimization techniques. The comparative analysis shows that the results of AAA are better in terms of economics, emissions and convergence rate.