Investigating the Effect of Grid Load Data on Optimal DG Placement and Capacity Determination

Abstract

Grid load data is an important factor in the placement and capacity of distributed generation (DG) in grid studies. Distribution networks are the largest part of electric networks and thus have the highest share of losses due to their low voltage and wide extent. Using power generation units near load centers can reduce grid losses considerably. For this purpose, the placement and capacity of DG units must be determined in order to maximize their potential. Usually, DG placement and capacity determination is done based on annual peak load data. This study shows that network load data such as peak load, average load, and hourly load strongly affect DG placement and capacity determination, and, therefore, will affect the annual network loss and the net present cost of DG installation during its useful life. In this study, different scenarios based on the type and number of network load input data, are considered and DG placement and capacity determination is performed for the IEEE 33 bus network. In order to do load flow studies, the Matpower program in the MATLAB environment is used and a genetic algorithm is used for optimization.