Two-Stage Stochastic Optimization Model for Multi-Microgrid Planning

Autor(es)

Vera, Enrique Gabriel ; Canizares, Claudio A. ; Pirnia, Mehrdad ; Guedes, Tatiana Pontual ; Trujillo, Joel David Melo

• Tipo de documento: Artigo Científico
• Fonte: IEEE TRANSACTIONS ON SMART GRID; v. 14, n. 3, p. 13-pg., 2023-05-01.

Resumo

This paper presents a Two Stage stochastic Programming (TSSP) model for the planning of Multi-Microgrids (MMGs) in Active Distribution Networks (ADNs). The model aims to minimize the total costs while benefiting from interconnections of Microgrids (MGs), considering uncertainties associated with electricity demand and Renewable Energy Sources (RESs). The associated uncertainties are analyzed using Geometric Brownian Motion (GBM) and probability distribution functions (pdfs). The model includes long-term purchase decisions and short-term operational constraints, using Geographical information Systems (GIS) to realistically estimate rooftop solar limits. The planning model is used to study the feasibility of implementing an MMG system consisting of 4 individual Microgrids (MGs) at an ADN in a municipality in the state of Sao Paulo, Brazil. The results show that the TSSP model tends to be less conservative than the deterministic planning model, which is based on simple and pessimistic reserve constraints, while performing faster than a simple Stochastic Linear Programming (SLP) algorithm, with higher accuracy. (AU)

• Processo FAPESP: 19/00466-6 - Planejamento espacial de micro redes considerando energia renováveis e veículos elétrico
• Beneficiário: Joel David Melo Trujillo
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 21/08832-1 - Alocação otimizada de concentradores inteligentes em redes de baixa tensão com recursos energéticos distribuídos
• Beneficiário: Joel David Melo Trujillo
• Modalidade de apoio: Auxílio à Pesquisa - Regular