Open AccessFlexibility of controllable power transformers for managing wind uncertainty using robust adjustable linearised optimal power flow
Author(s) -
Nikoobakht Ahmad,
Aghaei Jamshid,
Farahmand Hossein,
Lakshmanan Venkatachalam,
Korpås Magnus
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2018.5136
Subject(s) - electric power system , wind power , flexible ac transmission system , transformer , computer science , integer programming , renewable energy , grid , linear programming , voltage , power flow , mathematical optimization , reliability engineering , ac power , control theory (sociology) , control engineering , engineering , power (physics) , electrical engineering , mathematics , algorithm , physics , geometry , control (management) , quantum mechanics , artificial intelligence
As renewable energy sources (RESs) penetration increases in the power system, the transmission system operators face new challenges to ensure system reliability and flexibility while ensuring high utilisation of uncertain RES generation. Controllable transformers with on‐load tap changers and phase shifting capability are the promising flexibility tools to keep the system acceptable security and flexibility levels by controlling the voltage levels and energy flow. The AC optimal power flow (AC OPF) with detailed modelling considerations such as the bus voltage magnitude by including these devices is challenging. This study develops the AC OPF model to propose a robust flexibility optimisation framework for daily scheduling problem with uncertain wind energy sources. Nevertheless, the proposed formulation representation is an intractable mixed integer nonlinear programming (MINLP) while it includes AC grid constraints and the augmented modelling of the mentioned transformers. Accordingly, the proposed MINLP problem has been converted into a mixed‐integer linear program where a certain level of solution accuracy can be achieved for the available time budget. The effectiveness of the proposed method is demonstrated using a modified 6‐bus and IEEE 118‐bus test systems.