A Two-stage Stochastic Model for Coordinated Operation of Natural Gas and Microgrid Networks
| dc.contributor.author | Zandrazavi, Seyed Farhad [UNESP] | |
| dc.contributor.author | Tabares, Alejandra | |
| dc.contributor.author | Franco, John Fredy [UNESP] | |
| dc.contributor.author | Shafie-Khah, Miadreza | |
| dc.contributor.author | Soares, Joao | |
| dc.contributor.author | Vale, Zita | |
| dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
| dc.contributor.institution | Los Andes University | |
| dc.contributor.institution | University of Vaasa | |
| dc.contributor.institution | Polytechnic of Porto | |
| dc.date.accessioned | 2025-04-29T20:11:51Z | |
| dc.date.issued | 2023-01-01 | |
| dc.description.abstract | On the one hand, natural gas-fired dispatchable distributed generation (DG) units and batteries can be used in microgrids (MG) to cope with the intermittency of renewable energy resources such as wind turbines and photovoltaic units. On the other hand, the uncertainties in MG influence the gas system through the gas-fired DG units, making these systems' optimal operation interdependent. As a result, firstly, a novel mixed-integer nonlinear model for optimal integrated operation of gas and MG networks is proposed. Then, the model is linearized, guaranteeing the optimality of solutions and enhancing the model's tractability. Finally, a two-stage stochastic mode is proposed to include the uncertainties linked to electricity price, wind power speed, solar irradiation, and demand. In contrast, the value of the stochastic solution measurement is calculated to justify the use of the stochastic approach. The results indicate that the total cost of the integrated system decreased by 17.82% using the stochastic model compared to the deterministic approach. | en |
| dc.description.affiliation | São Paulo State University Department of Electrical Engineering | |
| dc.description.affiliation | Los Andes University Department of Industrial Engineering | |
| dc.description.affiliation | School of Technology and Innovations University of Vaasa | |
| dc.description.affiliation | GECAD School of Engineering (ISEP) Polytechnic of Porto | |
| dc.description.affiliationUnesp | São Paulo State University Department of Electrical Engineering | |
| dc.identifier | http://dx.doi.org/10.1109/PowerTech55446.2023.10202794 | |
| dc.identifier.citation | 2023 IEEE Belgrade PowerTech, PowerTech 2023. | |
| dc.identifier.doi | 10.1109/PowerTech55446.2023.10202794 | |
| dc.identifier.scopus | 2-s2.0-85169451970 | |
| dc.identifier.uri | https://hdl.handle.net/11449/308277 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | 2023 IEEE Belgrade PowerTech, PowerTech 2023 | |
| dc.source | Scopus | |
| dc.subject | energy management | |
| dc.subject | gas distribution network | |
| dc.subject | microgrid | |
| dc.subject | renewable energy | |
| dc.subject | stochastic programming | |
| dc.title | A Two-stage Stochastic Model for Coordinated Operation of Natural Gas and Microgrid Networks | en |
| dc.type | Trabalho apresentado em evento | pt |
| dspace.entity.type | Publication |

