Pawel Regulski

Wide-Area Monitoring, Protection, and Control of Future Electric Power Networks

Wide-area monitoring, protection, and control (WAMPAC) involves the use of system-wide information and the communication of selected local information to a remote location to counteract the propagation of large disturbances. Synchronized measurement technology (SMT) is an important element and enabler of WAMPAC. It is expected that WAMPAC systems will in the future reduce the number of catastrophic blackouts and generally improve the reliability and security of energy production, transmission, and distribution, particularly in power networks with a high level of operational uncertainties. In this paper, the technological and application issues are addressed. Several key monitoring, protection, and control applications are described and discussed. A strategy for developing a WAMPAC system in the United Kingdom is given as well.

Optimal Electric Network Design for a Large Offshore Wind Farm Based on a Modified Genetic Algorithm Approach

The increasing development of large-scale offshore wind farms around the world has caused many new technical and economic challenges to emerge. The capital cost of the electrical network that supports a large offshore wind farm constitutes a significant proportion of the total cost of the wind farm. Thus, finding the optimal design of this electrical network is an important task, a task that is addressed in this paper. A cost model has been developed that includes a more realistic treatment of the cost of transformers, transformer substations, and cables. These improvements make this cost model more detailed than others that are currently in use. A novel solution algorithm is used. This algorithm is based on an improved genetic algorithm and includes a specific algorithm that considers different cable cross sections when designing the radial arrays. The proposed approach is tested with a large offshore wind farm; this testing has shown that the proposed algorithm produces valid optimal electrical network designs.

Estimation of Composite Load Model Parameters Using an Improved Particle Swarm Optimization Method

Power system loads are one of the crucial elements of modern power systems and, as such, must be properly modelled in stability studies. However, the static and dynamic characteristics of a load are commonly unknown, extremely nonlinear, and are usually time varying. Consequently, a measurement-based approach for determining the load characteristics would offer a significant advantage since it could update the parameters of load models directly from the available system measurements. For this purpose and in order to accurately determine load model parameters, a suitable parameter estimation method must be applied. The conventional approach to this problem favors the use of standard nonlinear estimators or artificial intelligence (AI)-based methods. In this paper, a new solution for determining the unknown load model parameters is proposed-an improved particle swarm optimization (IPSO) method. The proposed method is an AI-type technique similar to the commonly used genetic algorithms (GAs) and is shown to provide a promising alternative. This paper presents a performance comparison of IPSO and GA using computer simulations and measured data obtained from realistic laboratory experiments.

Estimation of Frequency and Fundamental Power Components Using an Unscented Kalman Filter

In this paper, a new method for the simultaneous estimation of power components and frequency is presented. The method is based on the application of the unscented Kalman filter (UKF), which is an estimator capable of estimating the unknown model parameters during severe dynamic changes in the system. A particular advantage of using the UKF is the straightforward estimation procedure, which does not require linearization of the nonlinear signal model. This is an important feature as it improves the accuracy of the method during network transients. The nonlinear state-space parameter model for instantaneous power, taking into account the fundamental components of the system voltages and currents, is used as a starting point for the estimation of the power components and frequency. In the instantaneous power parameter model, the system frequency is considered to be an unknown model parameter, and it is estimated simultaneously with the other unknown model parameters: active and apparent power and the power angle. This resulted in an efficient numerical algorithm for the estimation of power components, which is not sensitive to variations of system frequency. The new estimator has been tested through computer simulations and by using data records obtained under laboratory conditions.

Wide Area Inter-Area Oscillation Monitoring Using Fast Nonlinear Estimation Algorithm

This paper presents the results of the development of Smart Grid transmission network applications in the Great Britain (GB) power system. A new Wide Area Monitoring System (WAMS) application for monitoring inter-area oscillations is developed. The core of this novel application is a fast nonlinear algorithm for the real-time estimation of the dominant inter-area oscillation mode, which processes GPS synchronized information obtained from Phasor Measurement Units (PMUs) installed in the power system. It is based on the Newton-Type Algorithm (NTA), an efficient parameter estimator. The paper focuses on the practical application of the new WAMS application: two data sets were tested, one based on computer simulations and the other based on real-life data records. The computer simulated oscillatory signals were obtained through dynamic simulations of the full GB power system model consisting of over 200 generators. The real-life data records used information collected by the FlexNet Wide Area Monitoring System (FlexNET-WAMS) installed in the GB network. Based on these data records, the features of inter-area oscillations in the GB network are drawn.

FlexNet wide area monitoring system

This paper presents the results of collaborative research from the SUPERGEN FlexNet Consortium into Wide Area Monitoring, Protection and Control (WAMPAC). The focus of the research addresses the design and development of an optimal WAMPAC architecture, communication infrastructure and real-time WAMPAC applications which will play an important role in future GB power network operation and understanding. The article concludes with an assessment of inter-area oscillations based on data records captured by the wide area monitoring system (WAMS) established as part of the FlexNet project.

On the Use of Dynamic Thermal-Line Ratings for Improving Operational Tripping Schemes

The increasing volume of renewable and intermittent generation that is being connected to power systems means that system operators need more advanced dynamic control tools to manage the increase in congestion and the resulting pressure on system constraints. The dynamic thermal-line rating (DTLR) is the thermal rating of a transmission line that is calculated in real time based on online measurements of the loading of the asset and local weather conditions. This dynamic rating will usually be greater than the static rating that is currently used, as the static rating is defined for the worst case scenario. Therefore, using the dynamic rating allows the thermal constraint on a line to be relaxed and the maximum loading increased. An operational tripping scheme (OTS) is a type of system integrity protection scheme that is used to relieve overloads on transmission lines during stressed system conditions by tripping preselected generation assets that are connected to the protected lines. An OTS is used to increase power flow on overhead lines, without building new assets or compromising security, but doing so results in potential generation constraints and higher system risk. This paper presents the novel integration of DTLRs into an existing OTS in order to improve its performance by reducing the likelihood of unnecessary generation tripping due to overly conservative line ratings. This novel OTS affords the system economic benefits, by avoiding unnecessary tripping, and improves system security by limiting the propagation of disturbed conditions and avoiding unnecessary tripping actions that could initiate dangerous cascading events that might lead to system blackouts. The new scheme is an example of a wide area monitoring, protection and control application.

Assessment of Frequency and Harmonic Distortions During Wind Farm Rejection Test

This paper proposes a new application of the self-tuning least squares (STLS) estimation algorithm for understanding transient processes during a rejection experiment at a wind farm site in Denmark. The problems of simultaneous estimation of frequency and harmonic distortion in a wind farm are investigated. An adaptive and robust application of the STLS algorithm is proposed to estimate the unknown parameters during the dynamic changes due to forced islanding conditions. Equipped with a self-tuning procedure, the algorithm is resistant to noise which significantly improves its accuracy. The system frequency is considered as an unknown model parameter and estimated simultaneously with fundamental and harmonic components. The outcome is an estimation method which is not sensitive to variations of system frequency. To demonstrate the efficiency of the proposed algorithm, a number of computer simulated tests are also presented. Several interesting results can be observed during the rejection experiment: the large deviations of three phase voltages and currents, the changes of total harmonic distortion, and variations of power system frequency.

Unscented Kalman Filter for frequency and amplitude estimation

This paper introduces a new digital signal processing algorithm for frequency and amplitude estimation based on Unscented Kalman Filter (UKF). The results of computer simulated and realistic synthetic data tests are presented. The initial parameters used during the tests were chosen carefully using an established parameter estimation method, the Self Tuning Least Square (STLS). It is concluded that the proposed algorithm is simple, efficient and has low computational demands compare to STLS which makes the UKF a very promising method in next generation of power quality monitoring devices.

Development of a flexible laboratory testing platform for assessing steady-state and transient performance of WAMS

This paper analyzes the development of an experimental setup for the steady state and transient analysis of Wide Area Measurement Systems (WAMS). The flexibility of the generated input signals for which the PMU performance is assessed represents a novel contribution of the designed setup. Transient disturbances modeled by mathematical functions or extracted from simulated networks within DigSILENT PowerFactory software are converted to COMTRADE files and uploaded into two signal generators in order to build relevant analogue waveforms for analyzing Phasor Measurement Units (PMUs) steady state and transient behavior. A novel characteristic of the design consists of the automated generating, acquisition and analysis procedure capable of processing the large quantity of results on which the steady state and transient performance assessment of WAMS is based. The assessment has revealed some equipment introduced phase shift errors, but their cause has been identified and overcome through the comparison of qualitative parameters of the input and output signals.