Decentralized model predictive based load frequency control in an interconnected power system

Abstract

This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

Introduction

In LFC problem, area load change and abnormal conditions lead to mismatches in frequency and scheduled power interchanges between areas. These mismatches have to be corrected by the LFC system. LFC objectives, i.e. frequency regulation and tracking the load demands, maintaining the tie-line power interchanges to specified values in the presence of modeling uncertainties, system nonlinearities and area load disturbances, determine the LFC synthesis as a multi-objective optimization problem [1], [2].

The fixed parameters controller, like an integral controller or a PI controller, is widely employed in the LFC application. Fixed parameters controllers are designed at nominal operating points and may no longer be suitable in all operating conditions. For this reason, adaptive gain scheduling approaches have been proposed for LFC synthesis [3], [4].

This method could to overcome the disadvantages of the conventional PID controller like. The need of adaptation of controller parameters, but actually, it faces some difficulties, like the instability of transient response as a result of abruptness in the system parameters, in additionally, Impossibility of obtaining accurate linear time invariant models at variable operating points [3].

Recently, the model predictive control (MPC) appears to be an efficient strategy to control many applications in industry; it has many advantages such as very fast response, robustness against load disturbance and parameters uncertainty. Its straightforward design procedure is considered as a major advantage of the MPC. Given a model of the system, only an objective function incorporating the control objectives needs to be set up. Additional physical constraints can be easily dealt with by adding them as inequality constraints, whereas soft constraints can be accounted for in the objective function using large penalties. Moreover, MPC adapts well to different physical setups and allows for a unified approach [5], [6].

Recently, some papers have reported the application of MPC technique on the load frequency control issue [7], [8], [9]. In [7], fast response and robustness against parameter uncertainties and load changes can be obtained using MPC controller, but, only for single area load frequency control application. In [8] the usage of MPC in multi-area power system is discussed, but, only by economic viewpoint, it presented a new model predictive load frequency control including economy logic for LFC cost reduction. In [9], Feasible Cooperation-Based MPC (FC-MPC) method is used in distributed LFC instead of Centralized MPC which is impractical for control of large-scale, geographically expansive systems, such as power systems, In spit of the good effort done in [9], the paper did not deal with the problem of system’s parameters mismatch, it only discussed the effect of load change, in addition, the range of load change used in the cases of study is very large and inappropriate in load frequency control issue.

This paper sheds the light on the impacts of parametric uncertainties beside the load change effect in an interconnected power system with decentralized model predictive based load frequency control. In this paper, each local area controller can be designed independently. The MPC technique law produces its optimal output derived from a quadratic cost function minimization based on the dynamic model of the specified area. The technique calculates the optimal control signal while respecting the given constraints over the output frequency deviation and the load change. The effects of the physical constraints such as generation rate constraint (GRC) and speed governor dead band [1] are considered. The power system with the proposed MPC technique has been tested through the effect of uncertainties due to governors and turbines parameters variation and load disturbances using computer simulation. A comparison has been made between the MPC and the traditional integral controller, which is widely used in practical industries, confirming the superiority of the proposed MPC technique. The simulation results proved that the proposed controller guarantees the robust performance in the presence of uncertainties due to governors and turbines parameters variation and loads disturbances.

The rest of the paper is organized as follows: the description of the dynamics of the interconnected power system is given in Section 2. A general consideration about MPC and its cost function are presented in Section 3. The proposed methodology is applied to two and three-area power system as a cases study, in Section 4. Finally, the paper is concluded in Section 5.