This paper proposes a distributed model predictive control based load frequency control (MPC-LFC) scheme to improve control performances in the frequency regulation of power system. In order to reduce the computational burden in the rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are utilized to approximate the predicted control trajectory. The closed-loop stability of the proposed MPC scheme is achieved by adding a terminal equality constraint to the online quadratic optimization and taking the cost function as the Lyapunov function. Furthermore, the treatments of some typical constraints in load frequency control have been studied based on the specific Laguerre-based formulations. Simulations have been conducted in two different interconnected power systems to validate the effectiveness of the proposed distributed MPC-LFC as well as its superiority over the comparative methods.

A distributed model predictive control based load frequency control scheme for multi-area interconnected power system using discrete-time Laguerre functions.

Robust multivariable predictive based load frequency control considering generation rate constraint

Reliable load frequency control (LFC) is very important for a modern power system with multi-source power generation and has been the primary focus of studies on advanced control theory and applications. In the LFC of a power system, the generation rate constraints (GRC) and position limit of the governor valve present major challenges to the control scheme because they significantly affect the dynamic responses of the system, resulting in larger overshoot and longer settling time. Model predictive control (MPC) is an attractive control strategy that systematically considers the constraints on the process inputs, states, and outputs. It is employed in LFC to cope with the GRC problem. This study proposes a distributed MPC (DMPC) for a four-area hydro–thermal interconnected power system. In the proposed scheme, the limit position of the governor valve is modelled by a fuzzy model and the local predictive controllers are incorporated into the non-linear control system. The effectiveness of the proposed non-linear constraint DMPC was demonstrated by simulations.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-cta.2015.1021

Distributed model predictive control for load frequency control with dynamic fuzzy valve position modelling for hydro–thermal power system

Aluminum production relies on the smelting process which consumes huge amounts of electrical energy One possible solution to reduce the fossil fuel consumption by aluminum production is the integration of wind power Based on this background, this paper studies an isolated power system for aluminum smelting production with a high penetration of wind power A dynamic model of the aluminum smelter load (ASL) is introduced in this paper using the field experiment data Based on this model, the dynamic model of the isolated system considering demand side participation is proposed The MPC-based frequency controller is proposed to keep the frequency deviation within a proper range ( $\pm$ 01 Hz) under wind power fluctuation as well as to recover the system frequency after a large disturbance (such as one generator trip) Finally, simulation results demonstrate the effectiveness of the proposed MPC based frequency controller

MPC-Based Frequency Control With Demand-Side Participation: A Case Study in an Isolated Wind-Aluminum Power System

SUMMARY

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 disturbance. Copyright © 2013 John Wiley & Sons, Ltd.

A functional model predictive control approach for power system load frequency control considering generation rate constraint

Constrained generalized predictive algorithm is employed to load frequency control in this paper. Generation rate constraint (GRC) has been considered. Using the linearization modeling technique, this paper deals with load frequency control by multivariable generalized predictive control method to build Controlled Auto-Regressive Integrated Moving Average model (CARIMA) and obtain generalized predictive control algorithm for load frequency control of the two-area reheat power system. Results demonstrate the effectiveness of the proposed generalized predictive control algorithm.

Xiaolei Zhan

Papers

Load frequency control considering generation rate constraints