A novel algorithm based on the combination of AC-OPF and GA for the optimal sizing and location of DERs into distribution networks
This article proposes an algorithm to obtain an optimal local solution for the network planning process related to the optimal integration of different renewable energy sources (RES) and different BatteryEnergy Storage Systems (BESS) into a distribution network (DN). The algorithm provides strategic...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/351022 |
| Acesso em linha: | https://hdl.handle.net/2117/351022 https://dx.doi.org/10.1016/j.segan.2021.100497 |
| Access Level: | acceso abierto |
| Palavra-chave: | Energy storage Electric power distribution Renewable energy sources Distributed generation Distribution networks Energy storage systems Power system planning Energia -- Emmagatzematge Energia elèctrica -- Distribució Energies renovables Àrees temàtiques de la UPC::Enginyeria elèctrica |
| Resumo: | This article proposes an algorithm to obtain an optimal local solution for the network planning process related to the optimal integration of different renewable energy sources (RES) and different BatteryEnergy Storage Systems (BESS) into a distribution network (DN). The algorithm provides strategicinformation related to investment and operation costs regarding the type of technology, location,and sizing. The mathematical formulation is based on an AC optimal power flow (OPF) to ensurethe network’s minimal stability conditions. Besides, through the use of linearization and a modifiedversion of a genetic algorithm (GA), the algorithm proposed breaks the 24 h wall, used until now inthe literature, and extend it to 8760 h, which represents a much more realistic scenario to define thestorage and power generation capacity of a DN in a planning context. The algorithm has been testedin a modified version of the IEEE 33-bus considering two cases of study: an off-grid case and grid-connected case, to measure the CapEx and OpEx variability, achieving to show that a grid-connectedsystem reduces the installed capacity of DG and BESS in 37.4% and the CapEx 22.8% |
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