Open AccessStochastic constrained linear quadratic control in a network of smart microgrids
Author(s) -
Bersani Chiara,
Dagdougui Hanane,
Ouammi Ahmed,
Sacile Roberto
Publication year - 2020
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2019.0992
Subject(s) - smart grid , context (archaeology) , computer science , mathematical optimization , energy management , quadratic equation , power balance , power (physics) , electric power , grid , electric power system , control theory (sociology) , control (management) , energy (signal processing) , engineering , mathematics , electrical engineering , paleontology , statistics , physics , geometry , quantum mechanics , artificial intelligence , biology
Challenges of microgrids (MGs) energy management have gained more relevance with the presence of uncertainties in power generation and local loads. These problems significantly increase when related to network of smart MGs (NSMG). To address these challenges, this study presents a stochastic constrained control problem for the optimal management of a cooperative NSMG with interconnections allowing power exchanges. In this model, each MG can exchange power locally among each other as well as with the main electric grid. The proposed control approach is based on a linear‐quadratic Gaussian problem definition for the optimal control of power flows under quadratic constraints limiting the variability of the power exchange as well as of the stored energy in each MG. The developed framework is applied to a cooperative network of four smart MGs to test and validate its effectiveness and performance. The network is connected to the main electric grid allowing power exchanges. The results demonstrate that the role of energy storage systems is undoubtedly becoming more and more relevant in the context of reacting to the stochastic behaviour of the balance between produced and consumed powers in MGs.