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

Autor(es)

de Lima, Tayenne Dias ^[1] ; Tabares, Alejandra ^[1] ; Arias, Nataly Banol ^[2] ; Franco, John F. ^[3]

Afiliação do(s) autor(es)

^[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

• Tipo de documento: Artigo Científico
• Fonte: INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS; v. 131, OCT 2021.
• Citações Web of Science: 0

Resumo

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)

• Processo FAPESP: 18/20990-9 - Novos modelos de otimização aplicados ao problema de planejamento de sistemas de distribuição no contexto de redes ativas
• Beneficiário: Alejandra Tabares Pozos
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 18/23617-7 - Operação ótima de sistemas modernos de distribuição de energia elétrica através da participação ativa de veículos elétricos e baterias estacionárias
• Beneficiário: Maria Nataly Banol Arias
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 15/21972-6 - Otimização do planejamento e da operação de sistemas de transmissão e de distribuição de energia elétrica
• Beneficiário: Rubén Augusto Romero Lázaro
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 17/02831-8 - Aplicação de métodos de otimização no planejamento do sistema de distribuição de energia elétrica
• Beneficiário: John Fredy Franco Baquero
• Modalidade de apoio: Auxílio à Pesquisa - Regular