Multi-Objective Distribution System Planning Considering Non-Utility-Owned Distributed Generation and CO2Emissions Costs
| dc.contributor.author | Mejia, Mario A. [UNESP] | |
| dc.contributor.author | Franco, John F. [UNESP] | |
| dc.contributor.author | Macedo, Leonardo H. [UNESP] | |
| dc.contributor.author | Muñoz-Delgado, Gregorio | |
| dc.contributor.author | Contreras, Javier | |
| dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
| dc.contributor.institution | Escuela Técnica Superior de Ingeniería Industrial | |
| dc.date.accessioned | 2025-04-29T20:05:47Z | |
| dc.date.issued | 2023-01-01 | |
| dc.description.abstract | Distribution systems planning (DSP) has become increasingly challenging due to the growing adoption of renewable distributed generation (DG) aimed at reducing CO2 emissions, particularly when the utility does not own these units. Therefore, this paper proposes a multi-objective stochastic strategy for DSP that considers non-utility-owned renewable DG. Under this approach, the utility makes investment decisions for assets such as conductors and voltage control equipment. Furthermore, the utilization of a multi-objective approach enables a sensitivity analysis, which assists both the utility and DG owner in reaching a consensus on the type, size, and location of renewable DG units. The strategy proposes minimizing the net present value of the investment and operational costs for both parties, with the additional goal of reducing the cost of CO2 emissions from the network. A scenario-based stochastic programming framework is used to characterize the behavior of uncertain parameters. The model is written in the AMPL language and solved using the CPLEX solver. Tests are conducted using a 69-node system, revealing that the total costs for both parties vary depending on the size and location of the DG as well as the cost of energy sold from the DG to the network. | en |
| dc.description.affiliation | São Paulo State University Department of Electrical Engineering | |
| dc.description.affiliation | São Paulo State University Department of Engineering | |
| dc.description.affiliation | Universidad de Castilla-La Mancha Escuela Técnica Superior de Ingeniería Industrial | |
| dc.description.affiliationUnesp | São Paulo State University Department of Electrical Engineering | |
| dc.description.affiliationUnesp | São Paulo State University Department of Engineering | |
| dc.identifier | http://dx.doi.org/10.1109/FES57669.2023.10183038 | |
| dc.identifier.citation | 2023 International Conference on Future Energy Solutions, FES 2023. | |
| dc.identifier.doi | 10.1109/FES57669.2023.10183038 | |
| dc.identifier.scopus | 2-s2.0-85166956974 | |
| dc.identifier.uri | https://hdl.handle.net/11449/306267 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | 2023 International Conference on Future Energy Solutions, FES 2023 | |
| dc.source | Scopus | |
| dc.subject | Distribution system planning | |
| dc.subject | mixed-integer linear programming | |
| dc.subject | multi-objective programming | |
| dc.subject | non-utility-owned distributed generation | |
| dc.subject | stochastic programming | |
| dc.title | Multi-Objective Distribution System Planning Considering Non-Utility-Owned Distributed Generation and CO2Emissions Costs | en |
| dc.type | Trabalho apresentado em evento | pt |
| dspace.entity.type | Publication |
