Bi-level fuzzy stochastic-robust model for flexibility valorizing of renewable networked microgrids
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Journal Title
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Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2022-09
Major/Subject
Mcode
Degree programme
Language
en
Pages
15
Series
Sustainable Energy, Grids and Networks, Volume 31
Abstract
This paper presents a new bi-level multi-objective model to valorize the microgrid (MG) flexibility based on flexible power management system. It considers the presence of renewable and flexibility resources including demand response program (DRP), energy storage system and integrated unit of electric spring with electric vehicles (EVs) parking (IUEE). The proposed bi-level model in the upper-level maximizes expected flexibility resources profit subject to flexibility constraints. Also, in the lower level, minimizing MG energy cost and voltage deviation function based on the Pareto optimization technique is considered as the objective functions; it is bounded by the linearized AC optimal power flow constraints, renewable and flexibility resources limits, and the MG flexibility restrictions. In the following, the proposed bi-level model using Karush–Kuhn–Tucker (KKT) technique is converted to a single-level counterpart, and the fuzzy decision-making method is employed to achieve the best compromise solution. Further, hybrid stochastic-robust programming models uncertain parameters of the proposed model, so that stochastic programming models uncertainties associated with demand, energy price, and the maximum renewables active generation. Also, to capture the flexible potential capabilities of the IUEE, robust optimization models the EVs’ parameters uncertainty. Finally, numerical results confirm the proposed model could jointly improve operation, economic and flexibility conditions of the MG and turned it to a flexi-optimized-renewable MG.Description
Publisher Copyright: © 2022 The Author(s)
Keywords
Flexibility valorizing, Fuzzy decision-making, Hybrid stochastic-robust programming, Microgrid flexibility, Renewable networked microgrids
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Citation
Norouzi, M, Aghaei, J, Niknam, T, Pirouzi, S & Lehtonen, M 2022, ' Bi-level fuzzy stochastic-robust model for flexibility valorizing of renewable networked microgrids ', Sustainable Energy, Grids and Networks, vol. 31, 100684 . https://doi.org/10.1016/j.segan.2022.100684
