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Two-Stage Stochastic Optimization Model for Multi-Microgrid Planning

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Author(s):
Vera, Enrique Gabriel ; Canizares, Claudio A. ; Pirnia, Mehrdad ; Guedes, Tatiana Pontual ; Trujillo, Joel David Melo
Total Authors: 5
Document type: Journal article
Source: IEEE TRANSACTIONS ON SMART GRID; v. 14, n. 3, p. 13-pg., 2023-05-01.
Abstract

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)

FAPESP's process: 19/00466-6 - Spatial microgrid planning with renewable energy and electric vehicles
Grantee:Joel David Melo Trujillo
Support Opportunities: Regular Research Grants
FAPESP's process: 21/08832-1 - Optimized allocation of intelligent concentrators in low voltage networks with distributed energy resources
Grantee:Joel David Melo Trujillo
Support Opportunities: Regular Research Grants