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Abstract
Voltage limit violation is a significant issue in power distribution networks, and it can result in many undesirable consequences, such as equipment damage and power outages. In this paper, we propose an innovative approach for intelligent communication-based reporting of voltage limit violations in power distribution networks utilizing the unscented Kalman filter (UKF). The proposed method utilizes real-time monitoring of the system's voltage and current measurements to estimate the power system's state parameters. By using the inferred state parameters, the proposed algorithm can detect and report voltage limit violations promptly. The proposed algorithm has been extensively tested against simulated data of an actual distribution system, demonstrating its ability to accurately detect and report voltage limit violations while mitigating issues such as noise and measurement errors.
Introduction
Currently, power distribution systems around the world are undergoing significant changes due to technological advancements and environmental concerns. One of the biggest challenges that the power distribution industry faces, however, is voltage limit violations. Voltage limit violations can lead to safety hazards, equipment damage, and power outages. Smart grids equipped with intelligent sensing and communication capabilities have enabled utilities to monitor real-time system information and improve the control and management of their power distribution networks. Intelligent communication-based reporting of voltage limit violations is an essential tool for detecting and preventing voltage limit violations in power distribution networks.
There are many existing methods for detecting voltage limit violations in power distribution networks, such as using phasor measurement units (PMUs) and state estimators. These methods can accurately detect voltage limit violations, but they typically require a significant amount of data, making them challenging to implement in real-time systems. In this paper, we propose a new method that can detect and report voltage limit violations in real-time in power distribution networks utilizing the UKF algorithm.
Unscented Kalman Filter
The UKF is a popular alternative to the traditional extended Kalman filter (EKF) for state estimation in nonlinear systems. The UKF is based on the principle of sigma-point scaling, which ensures that the equivalent number of points retains the mean and covariance of the prior distribution. The UKF can accept nonlinear measurement equations, making it well-suited to problems with nonlinear relationships. Compared to EKF, UKF takes into account the higher-order information in the measurement model, resulting in increased estimation accuracy.
Intelligent Communication-Based Reporting of Voltage Limit Violations
The proposed approach for intelligent communication-based reporting of voltage limit violations in power distribution networks utilizes the UKF algorithm. The proposed algorithm consists of three phases: 1) measurement of the system's voltage and current, 2) estimation of the state variables using the UKF algorithm, and 3) detection of voltage limit violations using the estimated state variables.
In the first phase, the proposed algorithm collects real-time measurements of the system's voltage and current using PMUs. PMUs are installed at key points in the system and enable high-speed, accurate measurements of critical system parameters, such as voltage and current.
In the second phase, the UKF algorithm uses the collected voltage and current measurements to estimate the state variables of the system, such as voltage magnitudes, phase angles, and real and reactive power. The estimated state variables are then used to detect voltage limit violations.
In the third phase, the proposed algorithm detects voltage limit violations by comparing the estimated voltage magnitudes with the predefined voltage threshold values. If the estimated voltage magnitudes exceed the threshold values, the algorithm reports the violation via a communication network to the control center.
Validation Results
The proposed method has been tested using simulated data of an actual distribution system, and the simulation results demonstrate its effectiveness in detecting and reporting voltage limit violations. The proposed algorithm performs well in noisy environments and can estimate the state variables accurately and promptly.
Conclusion
This paper proposes an innovative approach for intelligent communication-based reporting of voltage limit violations in power distribution networks using the UKF algorithm. The proposed approach can detect and report voltage limit violations promptly, mitigating issues such as noise and measurement errors. By using this algorithm, utilities can improve their management and control of power distribution networks and minimize the damages caused by voltage limit violations. Further research is needed to evaluate the algorithm's effectiveness in real-world scenarios.