Optimum allocation of distributed generation in multi-feeder systems using long term evaluation and assuming voltage-dependent loads

The analysis of actual distribution systems with penetration of distributed generation requires powerful tools with capabilities that until very recently were not available in distribution software tools; for instance, probabilistic and time mode simulations. This paper presents the work made by the authors to expand some procedures previously implemented for using OpenDSS, a freely available software tool for distribution system studies, when it is driven as a COM DLL from MATLAB using a parallel computing environment. The paper details the application of parallel computing to the allocation of distributed generation for optimum reduction of energy losses in a multi-feeder distribution system when the system is evaluated during a long period (e.g., the target is to minimize energy losses for periods longer than one year) and voltage-dependent load models are used. The long term evaluation is carried out by assuming that the connection of the generation units is sequential, and using a divide and conquer approach to speed up calculations. The main goals are to check the viability of a Monte Carlo method in some studies for which parallel computing can be advantageously applied and propose a procedure for quasi-optimum allocation of photovoltaic generation in a multi-feeder distribution system.