A PSO-BPSO Technique for Hybrid Power Generation System Sizing
| Autor: | Nestor Proenza-Perez, Omar R. Llerena-Pizarro, Celso Eduardo Tuna, José Luz Silveira |
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| Přispěvatelé: | Universidade Estadual Paulista (Unesp), Universidad Politécnica Salesiana, Ederal Center of Technological Education Celso Suckow da Fonseca (CEFET/RJ) |
| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
General Computer Science Computer science 020209 energy Photovoltaic system PSO-BPSO Particle swarm optimization 02 engineering and technology 021001 nanoscience & nanotechnology Transfer function Sizing State of charge Robustness (computer science) Hybrid system 0202 electrical engineering electronic engineering information engineering Mathematical modeling Electrical and Electronic Engineering Hybrid power Optimal sizing 0210 nano-technology Hybrid generation energy systems |
| Zdroj: | Scopus Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP |
| ISSN: | 1548-0992 |
| DOI: | 10.1109/tla.2020.9111671 |
| Popis: | Made available in DSpace on 2020-12-12T02:11:05Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-08-01 The Particle Swarm Optimization (PSO) algorithm has been widely used in the field of optimization mainly due to its easy implementation, robustness, fast convergence, and low computational cost. However, due to its continuous nature, the PSO cannot be applied directly to real-life problems such as hybrid energy generating systems (HEGS) sizing, which contain continuous and discrete decision variables. In this context, the present work proposes the combination of the original version of the PSO with the binary version of the same algorithm (BPSO) for the sizing of HEGS. The transfer function is the main difference between these two algorithms. In this paper, an S-type transfer function is used to map the continuous space into a discrete space. All components of the HEGS are modeled and simulated during the optimization process. The net present value is defined as the unique objective function. The state of charge (SOC) of the batteries is the main constraint. The proposed PSO-BPSO is used for sizing hybrid power generating systems in the Galapagos Islands in Ecuador. Results show that the best configuration for the studied case is a hybrid system with solar panels, batteries, and diesel generators. Configurations that contain only photovoltaic panels and batteries imply a higher cost due to the oversizing of the battery bank. The proposed PSO-BPSO algorithm revealed to be a simple and powerful tool for efficient energy systems sizing. São Paulo State University UNESP College of Engineering of Guaratinguetá Department of Energy Laboratory of Optimization Energy Systems (LOSE) Institute of Bioenergy Research (IPBEN) GIDTEC - Mechanical Engineering Department Universidad Politécnica Salesiana Ederal Center of Technological Education Celso Suckow da Fonseca (CEFET/RJ) São Paulo State University UNESP College of Engineering of Guaratinguetá Department of Energy Laboratory of Optimization Energy Systems (LOSE) Institute of Bioenergy Research (IPBEN) |
| Databáze: | OpenAIRE |
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