An Optimal Distributed MPC Scheme for Automatic Generation Control Under Network Constraints

Patel, R, Meegahapola, L, McGrath, B, Yu, X and Wang, L 2018, 'An Optimal Distributed MPC Scheme for Automatic Generation Control Under Network Constraints', in Proceedings of the IEEE 27th International Symposium on Industrial Electronics (ISIE 2018), Cairns, Australia, 13-15 June 2018, pp. 1121-1126.


Document type: Conference Paper
Collection: Conference Papers

Title An Optimal Distributed MPC Scheme for Automatic Generation Control Under Network Constraints
Author(s) Patel, R
Meegahapola, L
McGrath, B
Yu, X
Wang, L
Year 2018
Conference name ISIE 2018
Conference location Cairns, Australia
Conference dates 13-15 June 2018
Proceedings title Proceedings of the IEEE 27th International Symposium on Industrial Electronics (ISIE 2018)
Publisher IEEE
Place of publication United States
Start page 1121
End page 1126
Total pages 6
Abstract Traditional Automatic Generation Control (AGC) regulates an area control error (ACE) signal to control deviations in both the tie-line flows and system frequency. This approach can be suboptimal when the generation mix incorporates a high penetration of Renewable Energy Sources (RESs), and can lead to a biased control response under large supply and/or demand disturbance events. This paper proposes an alternative distributed Model Predictive Control (MPC) scheme which regulates the frequency deviations, and enforces thermal limit constraints on the tie-line flow deviations. The proposed State Constraint Distributed Model Predictive Control (SCDMPC) scheme achieves bias-free control and operation at the economically optimal operating point. The methodology is developed by considering system dynamics accounting for the primary generation sources and the tie-line power flow constraints. The new SCDMPC methodology reduces the regulating reserve requirement, enables a self-smoothing response to the supply/demand fluctuations between control areas, and improves the economics of AGC under high RESs penetration conditions.
Subjects Power and Energy Systems Engineering (excl. Renewable Power)
Keyword(s) Automatic generation control (AGC)
optimization
model predictive control (MPC)
distributed control
tielines
frequency regulation
DOI - identifier 10.1109/ISIE.2018.8433743
Copyright notice © 2018 IEEE
Versions
Version Filter Type
Citation counts: Scopus Citation Count Cited 0 times in Scopus Article
Altmetric details:
Access Statistics: 16 Abstract Views  -  Detailed Statistics
Created: Thu, 23 May 2019, 08:44:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us