Synthesis of Solar Production and Energy Demand Profiles Using Markov Chains for Microgrid Design

Hugo Radet, Bruno Sareni () and Xavier Roboam
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Hugo Radet: LAPLACE, Université de Toulouse, CNRS, INPT, UPS, 2 rue Camichel, 31 071 Toulouse, France
Bruno Sareni: LAPLACE, Université de Toulouse, CNRS, INPT, UPS, 2 rue Camichel, 31 071 Toulouse, France
Xavier Roboam: LAPLACE, Université de Toulouse, CNRS, INPT, UPS, 2 rue Camichel, 31 071 Toulouse, France

Energies, 2023, vol. 16, issue 23, 1-12

Abstract: Uncertainties related to the energy produced and consumed in smart grids, especially in microgrids, are among the major issues for both their design and optimal management. In that context, it is essential to have representative probabilistic scenarios of these environmental uncertainties. The intensive development and massive installation of smart meters will help to better characterize local energy consumption and production in the following years. However, models representing these variables over large timescales are essential for microgrid design. In this paper, we explore a simple method based on Markov chains capable of generating a large number of probabilistic production or consumption profiles from available historical measurements. We show that the developed approach can capture the main characteristics and statistical variability of real data on both short-term and long-term scales. Moreover, the correlation between both production and demand is conserved in generated profiles with respect to historical measurements.

Keywords: microgrids; uncertainties; integrated design; stochastic modeling; Markov chains; energy demand; solar production (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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