Publication
An analysis of energy storage system interaction in a multi objective model predictive control based energy management in DC microgrid
Conference Article
Conference
IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
Edition
24th
Pages
739-746
Doc link
https://doi.org/10.1109/ETFA.2019.8869474
File
Authors
Projects associated
INCITE: Innovative controls for renewable sources integration into smart energy systems
MICAPEM: Parameter estimation, diagnosis and control for the improvement of efficiency and durability of PEM fuel cells
REFER: Reducció energètica i flexibilitat en edificis en rehabilitació
MdM: Unit of Excellence María de Maeztu
Abstract
Non-deterministic generation from renewable sources have resulted in the incorporation energy storage systems in modern grids. Management of energy between different storage elements need to done optimally to ensure efficient operation of the grid. The intraday energy management problem is addressed in this work through an online model predictive control using multi objective optimisation. This work analyses the energy interaction among different storages when penalty weights in a multi objective optimisation problem is varied, in order to find an optimal scenario in terms of weight distribution. Different scenarios are identified and performance indices are proposed to achieve the same. The work also addresses implicitly the objective of minimising rate of degradation batteries. Simulation results are presented to aid in the analysis.
Categories
control theory, optimisation.
Author keywords
Model predictive control, energy management, energy storages system, degradation rate
Scientific reference
U. Raveendran Nair and R. Costa. An analysis of energy storage system interaction in a multi objective model predictive control based energy management in DC microgrid, 24th IEEE International Conference on Emerging Technologies and Factory Automation, 2019, Zaragoza, pp. 739-746.
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