Open AccessPower control strategy for photovoltaic system based on the Newton quadratic interpolation
Author(s) -
Liu Yun,
Xin Huanhai,
Wang Zhen,
Yang Taicheng
Publication year - 2014
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.2013.0067
Subject(s) - maximum power point tracking , photovoltaic system , control theory (sociology) , microgrid , convergence (economics) , quadratic function , computer science , quadratic equation , maximum power principle , rate of convergence , fault (geology) , mode (computer interface) , electric power system , power (physics) , voltage , engineering , mathematics , control (management) , electrical engineering , artificial intelligence , geometry , quantum mechanics , physics , channel (broadcasting) , inverter , economic growth , computer network , operating system , seismology , economics , geology
To maximise the economic benefit, photovoltaic (PV) systems in general operate in the so‐called maximum power point tracking (MPPT) mode. However, in certain occasions (e.g. in a microgrid or in a weak system), it is beneficial for a PV system not to always operate in the MPPT mode, but occasionally in the power dispatch mode, because of the top priority of maintaining system stability. To this end, a Newton quadratic interpolation‐based power control strategy for PV system is proposed to iteratively obtain the required terminal voltage of PV system by approximating the power–voltage characteristic curve with a quadratic curve. With this control strategy, PV systems can operate in the power dispatch mode to flexibly adjust the active power output in a wide range, or adaptively switch to the MPPT mode if necessary. Details on the convergence rate and the way to achieve the fault ride‐through capability are also discussed. Simulation is performed based on a detailed PV dynamical model, illustrating that the proposed method has fast convergence rate and robust performance compared with a revised perturb and observe method which can attain the same function.