Zhenyu Huang

Comparative analysis between ROCOF and vector surge relays for distributed generation applications

This paper presents a comprehensive comparative analysis between rate-of-change-of-frequency (ROCOF) and vector-surge (VS) relays for distributed generation islanding detection. The analysis is based on the concepts of detection-time versus active power-imbalance curves and critical active power imbalance. Such curves are obtained through dynamic simulations. The performance of these devices considering different scenarios is determined and compared. Factors such as voltage-dependent loads, generator inertia constant, and multidistributed generator systems are analyzed. False operation of these relays due to faults in adjacent feeders is also addressed. Results show that ROCOF relays are more reliable to detect islanding than vector surge relays when the active power imbalance in the islanded system is small. However, ROCOF relays are more susceptible to false operation than VS relays.

A practical method for assessing the effectiveness of vector surge relays for distributed generation applications

This work presents a simple and reliable method for predicting the islanding detection performance of vector surge relays. The relay performance is characterized by a tripping-time versus power-imbalance curve. With the curve, one can determine the time taken by a vector surge relay to detect islanding for any generation-load mismatch level. The main contribution of this paper is the development of analytical formulas for directly determining the behavior of vector surge relays. As a result, efforts needed to asses the relay performance for a given distributed generation scheme can be simplified significantly. The accuracy of the formulas has been verified by extensive simulation study results.

Incorporating Uncertainty of Wind Power Generation Forecast Into Power System Operation, Dispatch, and Unit Commitment Procedures

An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, capable of incorporating multiple sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and startup failures). A new method called the “flying-brick” technique is developed to evaluate the look-ahead required generation performance envelope for the worst-case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an energy management system (EMS) is developed. Demonstration through EMS integration illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems in control rooms.

Current Status and Experience of WAMS Implementation in North America

The 15 years of successful implementation of wide-area measurement systems (WAMS) in the WECC power grid have shown significant value of WAMS data in system dynamic modeling and validation, FACTS control validation and pilot implementations of wide area protection schemes. The August 14 2003 blackout in the eastern interconnection of the North America revealed the urgent need for wide-area information acquisition for better power grid operations. The Eastern interconnection phasor project (EIPP) was launched in 2003 to deploy a WAMS system in the eastern interconnection. Development of IEEE C37.118, a standard for phasor data acquisition and transmission, will aid in deployment of phasor measurement systems for WAMS applications. Technologies of phasor measurement units (PMUs) with high precision time synchronization and phasor data concentrators (PDCs) for phasor data aggregation and event recording are key to the success of WAMS implementation. This paper reviews the WAMS development in the North America and presents current and potential WAMS applications including dynamic modeling and validation and wide-area control. Past experience shows a promising future of WAMS in improving power system planning, operation and control. However, there remain challenges to make phasor measurement consistent and to meet both slow and fast data application needs

Online voltage stability monitoring using VAr reserves

For many years, system operators have noticed that the VAr reserves of key generators can indicate the degree of controllability of key bus voltages in a system. This observation has led to the development of a few VAr reserve monitoring systems. In this paper, a rigorous investigation on the subject is conducted. Using the correlative relationship between generator VAr reserves and system voltage stability margins, a practical and systematic method for online voltage stability monitoring is proposed. The method has been thoroughly tested on two real-life power systems with promising results.

Harmonic resonance mode analysis

Harmonic resonance often manifests as high harmonic voltages in a power system. It was found that such resonance phenomenon is associated with the singularity of the network admittance matrix. The singularity, in turn, is due to the fact that one of the eigenvalues of the matrix approaches zero. By analyzing the characteristics of the eigenvalue, one can find useful information on the nature and extent of the resonance. The objective of this paper is to present our findings on this interesting subject. Based on the results, a technique called resonance mode analysis is proposed. Analytical and case study results have confirmed that the proposed method is a valuable tool for power system harmonic analysis.

Massive contingency analysis with high performance computing

Contingency analysis is a key function in the Energy Management System (EMS) to assess the impact of various combinations of power system component failures based on state estimates. Contingency analysis is also extensively used in power market operation for feasibility test of market solutions. Faster analysis of more cases is required to safely and reliably operate todays power grids which have a less margin and more intermittent renewable energy sources. Enabled by the latest development in the computer industry, high performance computing holds the promise of meet the need in the power industry. This paper investigates the potential of high performance computing for massive contingency analysis. The framework of “N-x” contingency analysis is established, and computational load balancing schemes are studied and implemented with high performance computers. Case studies of massive 300,000-contingency-case analysis using the Western Electricity Coordinating Council power grid model are presented to illustrate the application of high performance computing and demonstrate the performance of the framework and computational load balancing schemes.

Vulnerability assessment for cascading failures in electric power systems

Cascading failures present severe threats to power grid security, and thus vulnerability assessment of power grids is of significant importance. Focusing on analytic methods, this paper reviews the state of the art of vulnerability assessment methods in the context of cascading failures. These methods are based on steady-state power grid modeling or high-level probabilistic modeling. The impact of emerging technologies including phasor technology, high-performance computing techniques, and visualization techniques on the vulnerability assessment of cascading failures is then addressed, and future research directions are presented.

Generator dynamic model validation and parameter calibration using phasor measurements at the point of connection

Summary form only given. Power system model quality is key to safe and reliable electricity delivery. In this paper, a novel method using disturbance data recorded by phasor measurement units (PMUs) is proposed to improve the integrity of dynamic models, which consists of both model validation and model parameter identification. In the model validation step, event playback is applied to simulate the models response for a rigorous comparison with measured response captured by PMUs. A large mismatch indicates model deficiency. In the parameter identification step, an automatic calibration method using the extended Kalman filter (EKF) techniques and trajectory sensitivity analysis is formulated to save significant effort and time from manual tuning. Case studies are presented to demonstrate that the proposed method has adequate performance for model validation and parameter calibration in terms of accuracy, good convergence speed and robustness with respect to measurement noises. The proposed method is cost-effective and complements traditional equipment testing for improving dynamic model quality.

Simulating the dynamic coupling of market and physical system operations

As energy trading products cover shorter time periods and demand response programs move toward real-time pricing, financial market-based activity impacts ever more directly the physical operation of the system. To begin to understand the complex interactions between the market-driven operation signals, the engineered controlled schemes, and the laws of physics, new system modeling and simulation techniques must be explored. This discussion describes requirements for interactions and an approach to capture the dynamic coupling between energy markets and the physical operation of the power system appropriate for dispatcher reaction time frames.