Open AccessRobust voltage control algorithm incorporating model uncertainty impacts
Author(s) -
Bakhshideh Zad Bashir,
Toubeau JeanFrançois,
Lobry Jacques,
Vallée François
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.6383
Subject(s) - robustness (evolution) , voltage , control theory (sociology) , monte carlo method , transformer , computer science , mathematical optimization , uncertainty quantification , robust control , control system , engineering , control (management) , mathematics , biochemistry , chemistry , statistics , artificial intelligence , machine learning , electrical engineering , gene
This study addresses the voltage control problem of the medium‐voltage distribution systems under uncertainty of the network model. A robust voltage control algorithm (RVCA) is developed in order to manage the voltage constraints considering uncertainties associated with the parameters of load, line, and transformer models. The RVCA determines a corrective solution that remains immunised against any realisation of uncertainty associated with the parameters of the network model. To this end, prior to formulating the voltage control problem, Monte Carlo (MC) simulations are used to characterise uncertain parameters of the network component models and load flow (LF) calculations are carried out to evaluate their impacts. The voltage constraints management under the uncertain environment is then formulated as a robust optimisation (RO) problem. The latter is constructed based on the results obtained through the MC simulations and LF calculations. Once the RO is solved, in order to check the robustness of the solution, system voltages are evaluated using the LF calculations considering the new set‐points of control variables and uncertainty of network parameters. The simulation results reveal that neglecting model uncertainty in the voltage control problem can lead to infeasible solutions while the proposed RVCA, at an extra cost, determines a corrective solution which remains protected against the studied uncertainties.