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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Investment & generation costs vs CO2 emissions in the distribution system expansion planning: A multi-objective stochastic programming approach

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Author(s):
de Lima, Tayenne Dias [1] ; Tabares, Alejandra [1] ; Arias, Nataly Banol [2] ; Franco, John F. [3]
Total Authors: 4
Affiliation:
[1] Sao Paulo Univ UNESP, Dept Elect Engn, Ilha Solteira, SP - Brazil
[2] Univ Estadual Campinas, Dept Energy Syst, Sao Paulo - Brazil
[3] UNESP, Sch Energy Engn, Rosana, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS; v. 131, OCT 2021.
Web of Science Citations: 0
Abstract

Currently there is a great concern about climate change and its mitigation is one of the main reasons to encourage the development of more sustainable energy systems. Advanced methods are needed to support the planning process in which not just economic criteria are considered but also environmental issues such CO2 emissions related to energy generation. Hence, renewable distributed generation (DG) has been increasing in the last years to provide sustainable energy with low environmental impacts. Nevertheless, renewable DG introduces new challenges in the distribution system expansion planning problem (DSEP) due to its uncertain nature. To deal with those issues, this paper proposes a multi-objective approach based on Stochastic Programming for the DSEP, which addresses the minimization of two conflicting objectives: investment \& generation costs and CO2 emissions. The uncertainties related to wind, irradiation, and demand are modeled through representative scenarios under a mixed-integer linear programming formulation. Multi-period investments on substations, circuits, and DG allocation are considered to maintain the feasible operation. The multi-objective formulation is solved using off-the-shelf commercial software and the well-established epsilon-constraint method. Tests in a 54-node distribution system show that robust expansion plans considering CO2 emissions result in larger penetration of renewable resources; the found set of Pareto solutions represents the trade-off between cost and emission objectives that can be used by the expansion-planner to accomplish specific needs (e.g., budget limitations, emissions reduction target, or environmental constraints). (AU)

FAPESP's process: 18/20990-9 - New optimization models to solve the distribution system planning problem in the context of active networks
Grantee:Alejandra Tabares Pozos
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 18/23617-7 - Optimization of modern distribution system operation via Electric Vehicles' flexibility and stationary batteries integrated into three-phase unbalanced networks
Grantee:Maria Nataly Banol Arias
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 15/21972-6 - Optimization of the operation and planning in transmission and distribution systems
Grantee:Rubén Augusto Romero Lázaro
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 17/02831-8 - Application of optimization methods to the planning of electrical distribution systems
Grantee:John Fredy Franco Baquero
Support Opportunities: Regular Research Grants