Intelligent Voltage Control Research Articles

Intelligent Voltage Control Method in Active Distribution Networks Based on Averaged Weighted Double Deep Q-network Algorithm

High penetration of distributed renewable energy sources and electric vehicles (EVs) makes future active distribution network (ADN) highly variable. These characteristics put great challenges to traditional voltage control methods. Voltage control based on the deep Q-network (DQN) algorithm offers a potential solution to this problem because it possesses human-level control performance. However, the traditional DQN methods may produce overestimation of action reward values, resulting in degradation of obtained solutions. In this paper, an intelligent voltage control method based on averaged weighted double deep Q-network (AWDDQN) algorithm is proposed to overcome the shortcomings of overestimation of action reward values in DQN algorithm and underestimation of action reward values in double deep Q-network (DDQN) algorithm. Using the proposed method, the voltage control objective is incorporated into the designed action reward values and normalized to form a Markov decision process (MDP) model which is solved by the AWDDQN algorithm. The designed AWDDQN-based intelligent voltage control agent is trained offline and used as online intelligent dynamic voltage regulator for the ADN. The proposed voltage control method is validated using the IEEE 33-bus and 123-bus systems containing renewable energy sources and EVs, and compared with the DQN and DDQN algorithms based methods, and traditional mixed-integer nonlinear program based methods. The simulation results show that the proposed method has better convergence and less voltage volatility than the other ones.

Development of an Intelligent Voltage Control System for Bulk Power Systems

As modern power systems become large and complicated, an automated voltage and reactive power control system is required in most developed countries due to the remarkable recent progress in computer networks and information technology. To date, voltage control has depended on human operators in the Korean power system. Accordingly, this paper proposes a universal intelligent voltage control system for bulk power systems based on sensitivity analysis and a main expert system. A detailed state space modeling technique is discussed, and an effective performance index is proposed to accelerate the searching performance of the expert system. As the searching strategy is an important factor for the speed of the expert system, the least-first search algorithm is applied using this performance index. The proposed system has been applied to the Korean power system, showing promising results.

The Dominant Influencer of Voltage Fluctuation (DIVF) for Power Distribution System

Variability in power generation at multiple consumer-owned renewable energy sources can cause random voltage fluctuations, which may result in voltage violations at multiple nodes in a power distribution system. Traditional methods of voltage control are ineffective to address fast voltage variations. New dynamic methods of voltage control using end-user devices can significantly benefit from the knowledge of the dominant influencer of voltage fluctuation (DIVF). This paper introduces information theoretic metrics to identify DIVF for every node in the power distribution system. A node can be DIVF due to its location in the distribution system and its capacity to generate and change its power. Use of traditional power flow algorithms to identify the DIVF is computationally complex, which limits their use in real-time applications. In this paper, information theoretic indicators of the DIVF are computed analytically in a computationally efficient manner, and their effectiveness to identify the DIVF is tested using the IEEE 69 node test system. From simulations, it is shown that differential entropy, Kullback–Leibler distance, and Frechet distance are effective indicators of the DIVF and can successfully identify the most influential nodes providing the foundation for intelligent voltage control.

Intelligent voltage control strategy for three-phase UPS inverters with output LC filter

This paper presents a supervisory fuzzy neural network control (SFNNC) method for a three-phase inverter of uninterruptible power supplies (UPSs). The proposed voltage controller is comprised of a fuzzy neural network control (FNNC) term and a supervisory control term. The FNNC term is deliberately employed to estimate the uncertain terms, and the supervisory control term is designed based on the sliding mode technique to stabilise the system dynamic errors. To improve the learning capability, the FNNC term incorporates an online parameter training methodology, using the gradient descent method and Lyapunov stability theory. Besides, a linear load current observer that estimates the load currents is used to exclude the load current sensors. The proposed SFNN controller and the observer are robust to the filter inductance variations, and their stability analyses are described in detail. The experimental results obtained on a prototype UPS test bed with a TMS320F28335 DSP are presented to validate the feasibility of the proposed scheme. Verification results demonstrate that the proposed control strategy can achieve smaller steady-state error and lower total harmonic distortion when subjected to nonlinear or unbalanced loads compared to the conventional sliding mode control method.

전력계통의 지능형 전압제어시스템에 관한 연구

As modern power systems become large and complicated, the automated voltage and reactive power control system is required in most developed countries due to the recent amazing progress of computer net works and information thechnology. So far the voltage control has been depend on human operator in korean power system. This paper presents an intelligent voltage control system based on sensitivity analysis and artificial intelligence technology. Detailed state space modeling technique is discussed and a new performance index is proposed to speed up the searching performance of the expert system. As the searching strategy is very important factor of the speed of expert system the least first search algorithm is applied using this performance index. The intelligent voltage control system is applied to the Jeju power system. As a result, case studies showed a promissing application of the intelligent voltage control system.

Development of an Intelligent Voltage Control System for Jeju Island in Korea

The reactive power, unlike frequency, has local characteristics and it has relied on the manual operation in a local reactive power control station so far. Since coordination or integrated control was possible due to the recent advances in computers and communication networks, the hierarchical voltage control system, consisting of primary, secondary, and tertiary, has been already applied to the real-life situations of several developed countries in Europe. Recently, the Korea power system has been operated more closely to stability limits because of rapid growth in load-demand as seen in Europe. For this reasons, KEPCO recognized the need of the voltage control system and developed the voltage control system. In this paper, we developed intelligent voltage control system for domestic system using numerical algorithm based on the sensitivity matrix and expert system, and dynamic response characteristics of the developed system investigated as a preliminary step for interfacing RTDS(Real Time Digital Simulator). In addition, the developed system performance was verified.