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Optimum allocation of distributed generation in multi-feeder systems using long term evaluation and assuming voltage-dependent loads
Guerra Sánchez, Luis Gerardo; Martínez Velasco, Juan Antonio
Universitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica
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.© 2015 Elsevier Ltd.
Àrees temàtiques de la UPC::Energies::Energia elèctrica
Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica
Monte Carlo method
Numerical analysis
Distributed generation
Distribution system
Long term evaluation
Loss minimization
Monte Carlo method
Parallel computing
Monte Carlo, Mètode de
Enginyeria elèctrica
Classificació AMS::60 Probability theory and stochastic processes
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/submittedVersion
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