Open AccessOptimal sizing method of vanadium redox flow battery to provide load frequency control in power systems with intermittent renewable generation
Author(s) -
Martínez Maximiliano,
Molina Marcelo Gustavo,
Mercado Pedro Enrique
Publication year - 2017
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.2016.0798
Subject(s) - sizing , flow battery , computer science , automatic frequency control , renewable energy , electric power system , battery (electricity) , mathematical optimization , optimal control , control theory (sociology) , power (physics) , control engineering , automotive engineering , engineering , control (management) , mathematics , electrical engineering , physics , artificial intelligence , art , telecommunications , quantum mechanics , visual arts
This study proposes a novel methodology for optimal sizing of a vanadium redox flow battery (VRFB) aiming at providing the load frequency control (LFC) of power system (PSs) with renewable generation, such as wind generation. This methodology utilises a new optimisation problem, where the optimal size of the VRFB is an endogenous result from the model of optimisation problem. To resolve the new optimisation problem, a hybrid optimisation model (HOM) is employed in order to calculate the optimal investment for the VRFB (optimal size) while taking into account both its impact on the PS costs and on the quality of the system frequency. Through stochastic optimisation, the HOM allows computing the variable operating costs and VRFB investment costs, considering the uncertainties associated to the PS. This stochastic optimisation utilises a new quasi‐stationary simulations of the PS operation, which demands lower computing effort. To this aim, this study proposes a novel modelling approach of both the VRFB and the PS operation. Moreover, statistical indexes are proposed as new factor used in sizing the LFC operating reserve. The results show that the developed methodology allows evaluating with precision the stochastic characteristics of the PS.