A review of tools, models and techniques for long-term assessment of distribution systems using OpenDSS and parallel computing
Many distribution system studies require long-term evaluations (e.g. for one year or more): Energy loss minimization, reliability assessment, or optimal rating of distributed energy resources should be based on long-term simulations of the distribution system. This paper summarizes the work carried...
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| Format: | Article |
| Language: | English |
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AIMS Press
2018-09-01
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| Series: | AIMS Energy |
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| Online Access: | http://www.aimspress.com/energy/article/3099/fulltext.html |
| _version_ | 1811343539527745536 |
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| author | Gerardo Guerra Juan A. Martinez-Velasco |
| author_facet | Gerardo Guerra Juan A. Martinez-Velasco |
| author_sort | Gerardo Guerra |
| collection | DOAJ |
| description | Many distribution system studies require long-term evaluations (e.g. for one year or more): Energy loss minimization, reliability assessment, or optimal rating of distributed energy resources should be based on long-term simulations of the distribution system. This paper summarizes the work carried out by the authors to perform long-term studies of large distribution systems using an OpenDSS-MATLAB environment and parallel computing. The paper details the tools, models, and procedures used by the authors in optimal allocation of distributed resources, reliability assessment of distribution systems with and without distributed generation, optimal rating of energy storage systems, or impact analysis of the solid state transformer. Since in most cases, the developed procedures were implemented for application in a multicore installation, a summary of capabilities required for parallel computing applications is also included. The approaches chosen for carrying out those studies used the traditional Monte Carlo method, clustering techniques or genetic algorithms. Custom-made models for application with OpenDSS were required in some studies: A summary of the characteristics of those models and their implementation are also included. |
| first_indexed | 2024-04-13T19:30:44Z |
| format | Article |
| id | doaj.art-15764aefbf49446483f81a1febbaccb7 |
| institution | Directory Open Access Journal |
| issn | 2333-8334 |
| language | English |
| last_indexed | 2024-04-13T19:30:44Z |
| publishDate | 2018-09-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Energy |
| spelling | doaj.art-15764aefbf49446483f81a1febbaccb72022-12-22T02:33:11ZengAIMS PressAIMS Energy2333-83342018-09-016576480010.3934/energy.2018.5.764energy-06-05-764A review of tools, models and techniques for long-term assessment of distribution systems using OpenDSS and parallel computingGerardo Guerra0Juan A. Martinez-Velasco1Departament d’Enginyeria Electrica, Universitat Politecnica de Catalunya, Barcelona, SpainDepartament d’Enginyeria Electrica, Universitat Politecnica de Catalunya, Barcelona, SpainMany distribution system studies require long-term evaluations (e.g. for one year or more): Energy loss minimization, reliability assessment, or optimal rating of distributed energy resources should be based on long-term simulations of the distribution system. This paper summarizes the work carried out by the authors to perform long-term studies of large distribution systems using an OpenDSS-MATLAB environment and parallel computing. The paper details the tools, models, and procedures used by the authors in optimal allocation of distributed resources, reliability assessment of distribution systems with and without distributed generation, optimal rating of energy storage systems, or impact analysis of the solid state transformer. Since in most cases, the developed procedures were implemented for application in a multicore installation, a summary of capabilities required for parallel computing applications is also included. The approaches chosen for carrying out those studies used the traditional Monte Carlo method, clustering techniques or genetic algorithms. Custom-made models for application with OpenDSS were required in some studies: A summary of the characteristics of those models and their implementation are also included.http://www.aimspress.com/energy/article/3099/fulltext.htmlclustering techniquedistributed energy resourcedistribution systemgenetic algorithm, ModelingMonte Carlo methodoptimizationparallel computationreliability |
| spellingShingle | Gerardo Guerra Juan A. Martinez-Velasco A review of tools, models and techniques for long-term assessment of distribution systems using OpenDSS and parallel computing AIMS Energy clustering technique distributed energy resource distribution system genetic algorithm, Modeling Monte Carlo method optimization parallel computation reliability |
| title | A review of tools, models and techniques for long-term assessment of distribution systems using OpenDSS and parallel computing |
| title_full | A review of tools, models and techniques for long-term assessment of distribution systems using OpenDSS and parallel computing |
| title_fullStr | A review of tools, models and techniques for long-term assessment of distribution systems using OpenDSS and parallel computing |
| title_full_unstemmed | A review of tools, models and techniques for long-term assessment of distribution systems using OpenDSS and parallel computing |
| title_short | A review of tools, models and techniques for long-term assessment of distribution systems using OpenDSS and parallel computing |
| title_sort | review of tools models and techniques for long term assessment of distribution systems using opendss and parallel computing |
| topic | clustering technique distributed energy resource distribution system genetic algorithm, Modeling Monte Carlo method optimization parallel computation reliability |
| url | http://www.aimspress.com/energy/article/3099/fulltext.html |
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