z-logo
open-access-imgOpen Access
Photovoltaic-grid control method based on self-gain system compensation
Author(s) -
Junci Tang,
Tie Li,
Junbo Pi,
Dai Cui
Publication year - 2021
Publication title -
international journal of low-carbon technologies
Language(s) - English
Resource type - Journals
eISSN - 1748-1325
pISSN - 1748-1317
DOI - 10.1093/ijlct/ctab090
Subject(s) - photovoltaic system , maximum power point tracking , control theory (sociology) , compensation (psychology) , electric power system , renewable energy , grid , computer science , grid connected photovoltaic power system , electricity generation , power (physics) , control engineering , engineering , control (management) , electrical engineering , mathematics , voltage , psychology , physics , geometry , quantum mechanics , inverter , artificial intelligence , psychoanalysis
The presence of decentralized production in modern electrical systems precludes traditional automatic generation control (AGC) strategies. Renewable energy production is highly dependent on the environment; for example, photovoltaic (PV) system, but its power generation is very unstable, which makes power grids containing PV systems face greater challenges. In this paper, we propose a PV-grid control method based on self-gain system compensation to reduce the negative effects of large fluctuations and uncertainties in solar energy production. First, the performance characteristics of solar modules are discussed and a multi-region model with a system with high penetration of solar systems is built. The AGC power is then displayed with different power variations according to different maximum power point tracking methods to analyze the uncertainty and variation of the PV output power and its effects on the AGC. We have also developed and implemented a compensation unit to eliminate the negative effects of PV power on AGC. Finally, the proposed method was demonstrated using the load from the example step as a disturbance variable to obtain a dynamic model of a dual-zone switched grid AGC with two PV systems based on a DMPC-distributed model. As a result of the simulation, the proposed method in this paper can guarantee the excellent properties of the dynamic behavior of the AGC system with large variations and high uncertainty of the PV system, and the validity of the proposed method have also been confirmed.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom