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Coordinated Power System Load Frequency Control via MPC
, Ph.D. Dissertation Sharif University of Technology ; Ranjbar, Ali Mohammad (Supervisor)
Abstract
Load frequency control (LFC) is one of the important control problems in interconnected power system design and operation, and is becoming more significant today because of the increasing size, changing structure, emerging new uncertainties, environmental constraints and the omplexity of power systems. Therefore, load frequency function requires increased performance and flexibility to ensure that it is capable of maintaining a generation-load balance, following serious disturbances.Real power systems are often large-scale systems which are composed of many interacting subsystems. Therefore, it is difficult to control such systems due to the required inherent computational complexities and...
A functional model predictive control approach for power system load frequency control considering generation rate constraint
, Article International Transactions on Electrical Energy Systems ; Volume 23, Issue 2 , 2013 , Pages 214-229 ; 20507038 (ISSN) ; Ranjbar, A. M ; Amraee, T ; Sharif University of Technology
2013
Abstract
In this paper, a wide area measurement, centralized, load frequency control using model predictive control (MPC) is presented for multi-area power systems. A multivariable constrained MPC was used to calculate optimal control actions including generation rate constraints. To alleviate computational effort and to reduce numerical problems, particularly in large prediction horizon, an exponentially weighted functional MPC was employed. Time-based simulation studies were performed on a three-area power system, and the results were then compared with decentralized MPC and classical PI controller. The results show that the proposed MPC scheme offers significantly better performance against load...
Robust multivariable predictive based load frequency control considering generation rate constraint
, Article International Journal of Electrical Power and Energy Systems ; Volume 46, Issue 1 , March , 2013 , Pages 405-413 ; 01420615 (ISSN) ; Toulabi, M. R ; Ranjbar, A. M ; Sharif University of Technology
2013
Abstract
In this paper, a robust multivariable Model based Predictive Control (MPC) is proposed for the solution of load frequency control (LFC) in a multi-area power system. The proposed control scheme is designed to consider multivariable nature of LFC, system uncertainty and generation rate constraint, simultaneously. A constrained MPC is employed to calculate optimal control input including generation rate constraints. Economic allocation of generation is further ensured by modification of the predictive control objective function. To achieve robustness against system uncertainty and variation of parameters, a linear matrix inequality (LMI) based approach is employed. To validate the...
Supervisory predictive control of power system load frequency control
, Article International Journal of Electrical Power and Energy Systems ; Vol. 61, issue , October , 2014 , p. 70-80 ; Ranjbar, A. M ; Sharif University of Technology
Abstract
Objective: The objective of this paper is to develop a hierarchical two-level power system load frequency control. Design: At the button level, standard PI controllers are utilized to control area's frequency and tie-line power interchanges. At the higher layer, model predictive control (MPC) is employed as a supervisory controller to determine the optimal set-point for the PI controllers in the lower layer. The proposed supervisory predictive controller computes the optimal set-points such that to coordinate decentralized local controllers. Blocking and coincidence point technology is employed to alleviate the computational effort of the MPC. In order to achieve the best closed loop...
Load-frequency control of interconnected power system using emotional learning-based intelligent controller
, Article International Journal of Electrical Power and Energy Systems ; Volume 36, Issue 1 , March , 2012 , Pages 76-83 ; 01420615 (ISSN) ; Boroushaki, M ; Hosseini, S. H ; Sharif University of Technology
2012
Abstract
In this paper a novel approach based on the emotional learning is proposed for improving the load-frequency control (LFC) system of a two-area interconnected power system with the consideration of generation rate constraint (GRC). The controller includes a neuro-fuzzy system with power error and its derivative as inputs. A fuzzy critic evaluates the present situation, and provides the emotional signal (stress). The controller modifies its characteristics so that the critic's stress is reduced. The convergence and performance of the proposed controller, both in presence and absence of GRC, are compared with those of proportional integral (PI), fuzzy logic (FL), and hybrid neuro-fuzzy (HNF)...