Investigating Distributed Generation Systems Performance Using Monte Carlo Simulation

Abstract

A novel algorithm to evaluate the performance of electric distribution systems, including distributed generation (DG) is proposed. This algorithm addresses the deterministic and the stochastic natures of these electrical systems. Monte Carlo simulation is employed to solve the system operation randomness problem, taking into consideration the system operation constraints. The uncertainties in the locations, exported penetration level, and the states (on or off) of the DG units constitute the random parameters of the studied systems. The introduced algorithm incorporates these parameters with the traditional Newton-Raphson solution of the power flow equations. Monte Carlo simulation is implemented to perform the analysis of all the possible operation scenarios of the system under study and thus ensure the validity of the results. The proposed algorithm is employed to obtain the hourly power flow solution for a typical DG connected system. The system loading follows several typical load curves based on load bus types. Furthermore, new hourly steady-state operating system parameters are evaluated to describe the system behavior under the DG random operation. The results obtained are presented and discussed.