# Development of an Intelligent Voltage Control System for Bulk Power Systems
## 1 Introduction  
As power systems grow, many countries experience a number of widespread power outages due to voltage instability caused by the imbalance between reactive power supply and demand [1]. It is also expected that voltage instability will intensify in the near future as new renewable energy sources, such as wind power plants and small solar energy systems, are expanded [2]. Therefore, maintaining adequate voltage and reactive power is becoming an important issue in most countries.  
The voltage control methodology in bulk power systems can be classified into numerical methods and intelligent system approaches. The hierarchical-distributed architecture was first proposed by the French company Electricite de France [3]. This system consists of three layers of architecture: primary voltage control, secondary voltage control, and tertiary control [4]. Italy proposed a similar three-layer architecture, which consists of primary voltage regulation regional voltage regulators and tertiary voltage regulators [5]. Spain's voltage control system also consists of three layers of architecture [6]. Therefore, a hierarchical numerical control system is widely used in European countries. Of course, the detailed object function and operational strategy are different depending on the situation of each country. An interesting point in the secondary voltage control is the pilot node, which is most important to coordinate the regional voltage as it represents the center of the regional load. The pilot node concept may reduce the remote sensing cost and calculation burden. However, it may be hard to select pilot nodes in some tightly coupled power systems.  
For intelligent voltage control systems, the sensitivity tree-based real-time voltage and reactive power control method was proposed for the first time in Canada [7] in the 1980s. Inthe 1990s, SEGRE [8] and SETRE [9; 10] were proposed in Spain, which are basically hybrid systems using the sensitivity tree-based numerical computation and artificial intelligence method using operators' knowledge [11; 12]. However, the detailed numerical modeling and structure of the expert system, such as the knowledge-based, searching-space, and inference technique, have not been reported yet.  
In Korea, the voltages of load buses have been maintained by human operators based on their experience at regional locations. However, especially in metropolitan areas, it has been difficult to secure enough sites to install reactive power compensation equipment. In addition, voltage fluctuations frequently occur due to increased reactive power demands, such as underground cables. Therefore, a modern control system is required to maintain the entire system voltage.  
Recently, a secondary voltage control system [13; 14] has been proposed in Korea. This system has been tested in a test-bed system in Jeju Island. However, as the total power generation capacity has exceeded 125 GW in Korea, and Korea's main power system is very tightly coupled internally, a pilot node selection would be difficult for the mainland power system. Presently, it is clear that the supervisory control and data acquisition (SCADA) or remote sensing cost becomes increasingly cheaper. As Korea's mainland power system has a complex structure with heavy load density, an intelligent control approach would be more efficient than a conventional hierarchical three-layer approach. Therefore, an intelligent system has been proposed [15; 16; 17].  
This paper presents a state-of-the-art intelligent voltage control system for Korea's power system in detail. The proposed system consists of a numerical subsystem and a main expert system. The numerical subsystem consists of sensitivity matrices and power flow. The sensitivity tree space is generated by the sensitivity of various reactive power sources, such as the terminal voltage of each generator, shunt capacitors and shunt reactors, and transformer tap. The main expert system searches the sensitivity tree to find the best solution step-by-step and suggests the final control sequences.