Adaptive Robust Short-Term Planning of Electrical Distribution Systems Considering Siting and Sizing of Renewable Energy Based DG Units

Autor(es)

Melgar-Dominguez, Ozy Daniel ^[1] ; Pourakbari-Kasmaei, Mahdi ^[2] ; Sanches Mantovani, Jose Roberto ^[1]

Afiliação do(s) autor(es)

^[1] Sao Paulo State Univ, Dept Elect Engn, BR-15385000 Ilha Solteira - Brazil

^[2] Aalto Univ, Dept Elect Engn & Automat, Espoo 02150 - Finland

• Tipo de documento: Artigo Científico
• Fonte: IEEE TRANSACTIONS ON SUSTAINABLE ENERGY; v. 10, n. 1, p. 158-169, JAN 2019.
• Citações Web of Science: 13

Resumo

Short-term planning is a decision-making process that aims at ensuring proper performance of electrical distribution systems (EDSs) within a short period of time. In recent years, this process has faced a significant challenge due to the integration of renewable energy based technologies. To handle such complicated planning problem most suitably, sophisticated algorithms are required. This paper proposes a mixed-integer linear programming model to find the optimal short-term plan of EDSs considering siting and sizing of capacitor banks and renewable energy sources, conductor replacement of overloaded circuits, and voltage regulators allocation. Besides considering the economic aspects, the environmental issues are also considered to promote a low carbon emission system. To address the uncertainties of electricity consumption and renewable energy output power, a two-stage robust optimization model is used, and to handle this model more efficiently, the column and constraint generation algorithm is applied. A 135-node distribution system is studied under different conditions to assess the performance of the proposed approach. Results show that the planning actions, for each case study, improve the efficiency of EDS and mitigate the pollutant emissions at the distribution level. (AU)

• 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