Automatic Generation Control

About: Automatic Generation Control is a research topic. Over the lifetime, 2896 publications have been published within this topic receiving 68558 citations.

Grid Integration of Large DFIG-Based Wind Farms Using VSC Transmission

Abstract: This paper describes the use of voltage source converter (VSC)-based HVDC transmission system (VSC transmission) technology for connecting large doubly fed induction generator (DFIG)-based wind farms over long distance. The operation principles of the proposed system are described, and new control strategies for normal and grid fault conditions are proposed. To obtain smooth operation, the wind farm side VSC (WFVSC) is controlled as an infinite voltage source that automatically absorbs power generated by the wind farm and maintains a stable local ac network. Fault ride through of the system during grid ac faults is achieved by ensuring automatic power balancing through frequency modulation using WFVSC and frequency control using DFIG. PSCAD/EMTDC simulations are presented to demonstrate robust performance during wind speed and power variations and to validate the fault ride through capability of the proposed system.

Model-Based Attack Detection and Mitigation for Automatic Generation Control

Abstract: Cyber systems play a critical role in improving the efficiency and reliability of power system operation and ensuring the system remains within safe operating margins. An adversary can inflict severe damage to the underlying physical system by compromising the control and monitoring applications facilitated by the cyber layer. Protection of critical assets from electronic threats has traditionally been done through conventional cyber security measures that involve host-based and network-based security technologies. However, it has been recognized that highly skilled attacks can bypass these security mechanisms to disrupt the smooth operation of control systems. There is a growing need for cyber-attack-resilient control techniques that look beyond traditional cyber defense mechanisms to detect highly skilled attacks. In this paper, we make the following contributions. We first demonstrate the impact of data integrity attacks on Automatic Generation Control (AGC) on power system frequency and electricity market operation. We propose a general framework to the application of attack resilient control to power systems as a composition of smart attack detection and mitigation. Finally, we develop a model-based anomaly detection and attack mitigation algorithm for AGC. We evaluate the detection capability of the proposed anomaly detection algorithm through simulation studies. Our results show that the algorithm is capable of detecting scaling and ramp attacks with low false positive and negative rates. The proposed model-based mitigation algorithm is also efficient in maintaining system frequency within acceptable limits during the attack period.

Maiden Application of Bacterial Foraging-Based Optimization Technique in Multiarea Automatic Generation Control

Abstract: A maiden attempt is made to examine and highlight the effective application of bacterial foraging (BF) to optimize several important parameters in automatic generation control (AGC) of interconnected three unequal area thermal systems, such as integral controller gains (KIi) for the secondary control, governor speed regulation parameters (Ri) for the primary control and frequency bias parameters (Bi), and compare its performance to establish its superiority over genetic algorithm (GA) and classical methods. Comparison of convergence characteristics of BF, GA, and classical approach reveals that the BF algorithm is quite faster in optimization, leading to reduction in computational burden and giving rise to minimal computer resource utilization. Simultaneous optimization of KIi, Ri, and Bi parameters which surprisingly has never been attempted in the past, provides not only best dynamic response for the system but also allows use of much higher values of Ri (than used in practice), that will appeal to the power industries for easier and cheaper realization of governor. Sensitivity analysis is carried out which demonstrates the robustness of the optimized KIi, Ri, and Bi to wide changes in inertia constant (H), reheat time constant (Tr), reheat coefficient (Kr), system loading condition, and size and position of step load perturbation.

Automatic generation control of a wind farm with variable speed wind turbines

Abstract: Wind farms are considered to be negative loads from the point of view of a utility manager. Modern variable-speed wind turbines offer the possibility for controlling active and reactive power separately. This paper presents a new integrated control system of a wind farm according to the utility manager's requirements. This control system is based on two control levels: a supervisory system controls active and reactive power of the whole wind farm by sending out set points to all wind turbines, and a machine control system ensures that set points at the wind turbine level are reached. The system has been validated by numerical simulation using data from a wind farm with 37 variable-speed wind turbine situated in the North of Spain. An automatic generation control of these characteristics promises improved performance of the system and a better grid integration of the wind energy without significant extra costs.