Bulk power systems are usually composed of interconnected balancing areas (BAs) to minimize the operation cost from arbitrage trading and to increase the system reliability by importing electric power. In this case, each BA has its own automatic generation control (AGC) scheme in an energy management system (EMS), which is responsible for maintaining a nominal frequency and stabilizing inadvertent tie-line flows to scheduled flows. AGC signals are traditionally developed to minimize area control errors (ACEs), which represent the discrepancy between generation supply and total megawatt (MW) obligation in each BA [

1]. Given that the benefits of interconnection among BAs depend highly on the dynamic performance in maintaining frequency and tie-line flows, designing an AGC process to minimize ACEs has attracted continued interest while power systems are growing in size.

Recently, the model predictive control (MPC)-based designing process in AGC was studied extensively because of its two major advantages [

2]. First, this approach provides satisfactory control performance under dynamic constraints, such as load reference ramp constraints. Second, it allows systematic design of multi-input-multi-output (MIMO) systems. The conventional proportional integral derivative-based approach in AGC presents intractable subjects for admissible load reference control in real-time operation. In contrast, the MPC-based approach does not suffer from these problems because the actual control objectives and operating constraints can be represented explicitly in a single multi-horizon optimization.

Several MPC-based studies and formulations are available in the literature, and these approaches can be classified into three main categories, namely, centralized, distributed, and decentralized control structures. Mohamed [

3] investigated robust load frequency control (LFC) against parameter uncertainties and load changes but only dealt with LFC control application in a single-area power system. Kong [

4] proposed state contractive constraint-based MPC algorithms to guarantee the stability of the control scheme. Yousef [

5] utilized the MPC technique to investigate the design of the LFC system and thus improve power system dynamic performance over a wide range of operating conditions. However, centralized MPC-based AGC [

3,

4,

5] among independent bulk BAs is stated to be an impractical approach [

6,

7] because each BA should have its own AGC scheme, and optimizing AGC signals in a large-scale power system model consumes considerable computational time to obtain an admissible solution. Camponogara [

6] introduced the coordination of optimization computations using iterative exchange of information among distributed BAs. Venkat [

7] proposed a new object function that measures the system-wide effect of local control actions to build a reliable MPC-based controller. Nong [

8] provided a distributed MPC with fuzzy modeling to deal with the valve limit on the governor. Ma [

9] provided an MPC-based AGC that considers generation rate constraint and load reference ramp constraint. However, these distributed studies [

6,

7,

8,

9] assumed that the dynamic model in each area is modeled as a single-input-single-output (SISO) model, even when each BA has various local frequencies and multiple generators as the MIMO system [

1]. Control signals in each BA should also be periodically updated because EMS is a discretized controller [

10]. A few of the decentralized approaches are introduced or briefly mentioned in literature [

7,

11]. However, these control schemes are necessary to build a highly reliable and real-time communication system because each entity should communicate with other entities in real time to minimize the system-wide effects of local control actions and maximize its profits.

In this study, we develop a constrained MPC-based AGC in centralized and distributed control structures. In centralized MPC-based AGC, we develop a novel scheme to maintain designated line flows to strengthen its unique advantages. As loop flows and arrangements for parallel path compensation become increasingly important, this developed control scheme supports system operators by reducing the increase in power losses or the overloading of network elements. In distributed MPC-based AGC, the pseudo-frequency signal computed from ACEs is proposed. On the basis of this proposed signal, we develop individual and unsynchronized controllers to consider the system-wide effect of local control actions in each BA. In both control structures, the proposed MPC-based controllers provide the discretized AGC signals derived by minimizing a constrained quadratic programming (QP) based on the generator dynamic models in each BA. Moreover, we also consider computation burden because the real-time MPC-based controller in a bulk system can suffer from the computation capacity limits caused by dimensional complexity. According to the number of participating generators in AGC, computation time in the MPC-based approach is compared, and we develop a bulk-area partitioning scheme in accordance with the results to reduce computation time and ensure dynamic performance.

The remainder of this paper is divided into five sections:

Section 2 introduces the coupling model of electric generator and power network.

Section 3 develops MPC schemes in consideration of the generator dynamic model in power network.

Section 4 describes a case study of the proposed control model and discusses the MPC-based approach for implementation in AGC. Finally,

Section 5 gives the conclusions.