Dynamic Performance Evaluation of Distributed Generation Units in the Micro Grid

This paper presents dynamic models of distributed generators (DG) and investigates dynamic behavior of the DG units in the micro grid system. The DG units include photovoltaic and fuel cell sources. The voltage source inverter is adopted since the electronic interface which can be equipped with its controller to keep stability of the micro grid during small signal dynamics. This paper also introduces power management strategies and implements the DG load sharing concept to keep the micro grid operation in gridconnected and islanding modes of operation. The results demonstrate the operation and performance of the photovoltaic and fuel cell as distributed generators in a micro grid. The entire control system in the micro grid is developed by combining the benefits of the power control and the voltage control strategies. Simulation results are all reported, confirming the validity of the proposed control technique.

Genetic Algorithm for Solving Non-Convex Economic Dispatch Problem

Economic dispatch (ED) is considered to be one of the key functions in electric power system operation. This paper presents a new hybrid approach based genetic algorithm (GA) to economic dispatch problems. GA is most commonly used optimizing algorithm predicated on principal of natural evolution. Utilization of chaotic queue with GA generates several neighborhoods of near optimal solutions to keep solution variation. It could avoid the search process from becoming pre-mature. For the objective of chaotic queue generation, utilization of tent equation as opposed to logistic equation results in improvement of iterative speed. The results of the proposed approach were compared in terms of fuel cost, with existing differential evolution and other methods in literature.