Use of Synchronized Phasor Measurements for Model Validation in ERCOT

Use of Synchronized Phasor Measurements for Model Validation in ERCOT NDR Sarma, Jian Chen, Prakash Shrestha, Shun-Hsien Huang, John Adams, Diran Obadina, Tim Mortensen and Bill Blevins Electricity Reliability Council of Texas, USA Email Contact: snuthalapati@ercot.com Abstract This paper discusses experiences in the use of synchronized phasor measurement technology in Electric Reliability Council of Texas (ERCOT) interconnection, USA. Implementation of synchronized phasor measurement technology in the region is a collaborative effort involving ERCOT, ONCOR, AEP, SHARYLAND, EPG, CCET and UT-Arlington. As several phasor measurement units (PMU) have been installed in ERCOT grid in recent years, phasor data with the resolution of 30 samples per second is being used to monitor power system status and record system events. Post-event analyses using recorded phasor data have successfully verified ERCOT dynamic stability simulation studies. Real time monitoring software RTDMS enables ERCOT to analyze small signal stability conditions by monitoring the phase angles and oscillations. The recorded phasor data enables ERCOT to validate the existing dynamic models of conventional and/or wind generator. Keywords- Synchronized phasor measurement data, phasor measurement units, dynamic stability, post-event analysis, model validation, ERCOT T I. INTRODUCTION HE Electric Reliability Council of Texas Inc. (ERCOT) serves as the independent system operator for most of Texas region, and manages the flow of electric power to 23 million Texas customers representing 85 percent of the state s electric load and 75 percent of the Texas land area. ERCOT schedules power on an electric grid that connects 40,500 miles of transmission lines and more than 550 generation units. ERCOT also manages financial settlement for the competitive wholesale bulk-power market and administers customer switching for 6.5 million Texans in competitive choice areas. The total installed generation capacity of ERCOT is 84,400MW and its recorded peak load is 68,379 MW. There is total of 9,528 MW of wind generating capacity installed and operating in the ERCOT market, which makes Texas the largest renewable energy producer in US. The ERCOT bulk transmission system is built around 345kV and 38kV lines, which extend from far north-west of Texas to the border of Mexico. Most power is consumed in industrial and urban load centers in east and south Texas, while most wind energy is installed in the north-west part of Texas because of abundant wind resource there. This separation between resources and load centers create some unique challenges in how to best integrate renewable resources to meet increasing demand while also effectively ensuring the reliability of the ERCOT grid. Since synchronized phasor measurement units (PMUs) were first introduced in early 980s, they have been recognized as the new tools to modernize power system monitoring and control. Especially in recent years, PMUs are becoming popular in power systems due to their versatile utilization [3,4]. Applications of phasor measurements have been extended to power system monitoring [5,6,7], protection [8] and control [9]. Recognizing potential benefits of synchronized phasor technology, ERCOT started a collaborative effort in 2008 to implement this technology into its power system operations and planning studies. Besides ERCOT, this effort has engaged various other entities, including ERCOT transmission service providers (TSPs) Oncor, American Electric Power (AEP) and Sharyland, Electric Power Group (EPG) as the software application vendor, the Center for the Commercialization of Electric Technology (CCET) as coordinator, University of Texas at Arlington (UT-Arlington) as research collaborator. While the PMUs have been installed across ERCOT grid, several real-time and off-line tools have been installed for ERCOT engineers to monitor and study the incoming phasor data. Analyses using phasor data have indicated that synchronized phasor measurements can greatly improve both ERCOT operations and planning. Reference [0] gives the details of some of the applications of PMU data in ERCOT. This paper focuses on application of PMU data for model validation. This paper is organized as follows. Section II describes the existing PMU installation condition, including the locations of PMUs and the structure of communication network. Section III presents the application of phasor measurements in ERCOT for parameter validation. Section IV summarizes the conclusions about ERCOT s experience to date in the use of phasor measurements and also discusses the future plans. II. PMU LOCATIONS AND NETWORK IN ERCOT In this section, the locations of PMUs and their effects on different applications are discussed. The current communication network of PMUs and Phasor Data Concentrators (PDCs) is also presented. A. PMU Locations in ERCOT grid In principal, PMUs should be installed across the ERCOT transmission grid, to provide the good observation for entire network. Currently, PMUs are only installed in the networks

of participating transmission companies. The geographical locations of the existing and planned PMUs are shown in Fig.. At the time of writing this paper, there are total of 2 PMUs installed and connected to ERCOT phasor network. It is expected that at least 7 more PMUs will be installed in the next two years. The data presented in this paper was obtained from the installed PMUs as shown in Fig.. Note that not all PMU data sources were always available for the recorded events due to the communication constraints or outages. Although more PMUs will provide a clearer overall picture of entire grid with resolution of 30 samples per second, even the limited number of PMUs in current ERCOT grid have shown that they can be valuable in post-event dynamic analysis, realtime small signal stability monitoring and generator model validation. PMUs installed in the west and north areas allow ERCOT to monitor the stability conditions on West to North interface. And as most of wind generation is installed in West Texas, the data from PMUs located close to wind power plants can also help ERCOT validate dynamic wind generation models. B. Phasor Data and Communication Network A communication network has been built to transfer the phasor data from the individual PMUs to the ERCOT control center, where the incoming data is streamed to real-time applications and archived for off-line studies. As shown in Fig.2, currently the phasor data is sent from three ERCOT TSPs AEP, Sharyland and Oncor. Oncor and AEP have setup their own PDC and local data storage, so their data is sent to ERCOT through their PDCs. The Sharyland PMUs connect directly to the ERCOT PDC. The ERCOT PDC synchronizes this data using the attached time stamp, and outputs the data stream to data storage and to real time applications in ERCOT s Taylor control center. All data communications between ERCOT and the participated TSPs are based on ERCOT secured private wide area network (WAN). For data management, the phasor data is archived both in the TSP s local PDC level and ERCOT s control center. Stream phasor data is saved in ERCOT s server up to 2 years, and selected event data will be kept and archived for a longer time frame. A real time application installed in the ERCOT control center monitors the incoming stream phasor data and automatically selects for archiving event files when a disturbance is detected. III. Fig. PMU locations in ERCOT grid Fig. 2 Phasor data communication network APPLICATIONS OF PMU DATA FOR MODEL VALIDATION In addition to post-event analysis and real-time system monitoring, the Phasor measurement data has been used in ERCOT system for generator model validation. A well-recognized benefit of synchronized phasor data is that it can provide precise snapshots of the system states from multiple locations simultaneously. Because of its high resolution of the recoded data, it can reveal dynamic transients during a system event. Also because of its synchronization capability through GPS, the phasor data can provide a system wide view of the grid, compared to the conventional digital fault recorder (DFR) which can only visualize the local bus. Therefore, for the first time, the installation of PMUs allowed ERCOT to observe system wide transient condition changing before, during and after event disturbances. PMUs provide high resolution information regarding measured frequency, voltage angle and magnitude, current angle and magnitude. Using the phasor measurement data to provide an overview of the system in real time, it can allow operators to monitor the health of system and make informed decision. For this purpose, the Real Time Dynamic Monitoring System (RTDMS ) application has been installed 2

in the ERCOT control center. Developed by EPG, this synchrophasor software application can provide real time, wide area situational awareness to system operators, as well as the capability to monitor and analyze the real time dynamics of the power system []. Fig.3 shows the RTDMS dashboard screen for ERCOT. This display maps the available PMUs in the ERCOT grid and the phase angle separation between key substations in the system. The panel on the right also provides the important metrics regarding system security, including frequency, voltage magnitude and angles, power flows and damping index. The colors on the arrows and traffic lights provide a user-friendly interface to indicate the possible violation of the user-defined metric thresholds. Besides the main dashboard, RTDMS also provides other useful displays to track the changes of those above variables, such as separate displays for system frequency, voltage magnitude, voltage angles, and MW/MVAR values measured by the selected PMUs (Fig 4). Among them, the display of oscillation damping is specially designed to monitor existing inter-area oscillations in real time. In ERCOT, both operations and planning engineers rely on dynamic simulation tools to study the behavior of the power system and identify the stability issues in the grid. Therefore, the accuracy of the dynamic models is the key to achieve correct and reliable study results. Although field test is still a good method to directly identify the parameters of generator models, newly deployed Intelligent Electric Device (IED) such as DFRs and PMUs can provide dynamic information with high resolution, which makes online dynamic parameter identification become another valid option. A hybrid method combining particle swarm optimization (PSO) and sensitivity analysis (SA) has been developed by UT Arlington and ERCOT for dynamic parameter identification. This two-step method provides a feasible approach using recorded phasor data to verify and correct the conventional generator dynamic models. [2] Furthermore, the phasor data also has been used to study and verify the dynamic models for wind generation. As an example, a wind power plant (WPP) related event is presented below, where the recorded phasor data was used to validate and tune the wind dynamic model. A detail description of this post-event analysis is available in reference [2]. A simplified network topology of the WPP connected to the ERCOT grid is shown in Fig.5. Under operating condition, the WPP is connected to the ERCOT grid through two 69kV transmission lines. One phasor measurement unit (PMU) was installed on one of the 69kV lines (Bus5-Bus7). Fig. 3 Dashboard display for ERCOT system Fig. 4 Display of tracking oscillation mode Fig.5 Simplified network topology of the WPP The event happened when one of the 69kV lines (Bus5- Bus6) was in scheduled outage, then the WPP started to experience a poorly-damped voltage oscillation. When the output from WPP kept increasing, the voltage oscillation became further un-damped, as shown in Fig. 6. As stated in reference [3], the primary cause for these oscillations is the weak grid condition with low short circuit ratio. Before the post-event analysis of such an oscillation event, it is important to ensure that the wind dynamic model and associated modeling parameters are accurate. Therefore, the tuning of the wind dynamic model to accommodate the weak grid condition was made to have the simulation response match the PMU record data. Fig.7 shows the results between the simulation and PMU data at low wind output with poorly 3

.03.37.70 2.03 2.37 2.70 3.37 4.04 4.37 4.70.03.37.70 2.03 2.37 2.70 3.37 4.04 4.37 4.70 0.03 0.77.50 2.23 2.97 4.43 5.7 5.90 6.63 7.37 8.0 8.83 0.00 0.43 0.87.30.73 2.7 2.60 3.47 3.90 4.34 4.77 damped voltage response. The result in Fig.7 provides a wind dynamic model validation benchmark. And just by increasing the wind output in the study case with the same wind dynamic model, the un-damped oscillation as observed in the PMU data was also successfully re-created, as shown in Fig.8. Based on the findings in the off-line studies and the tuning of the wind dynamic model to re-create the PMU recorded oscillatory response in the real events, the voltage regulator of the WPP was identified as the key cause for the oscillations. The key causes for the oscillatory response captured by PMU are the combination of weak grid condition and aggressive voltage control of WPP. As a result, the potential solutions to mitigate these oscillations include the improvement of system strength and tuning of the wind voltage controller. This WPP related event is part of our experience to use phasor data to review our existing dynamic model. Considering the complexity of the WPP controls and quick changing of network topology, it is difficult to foresee all potential issues before the energization of the WPP. PMUs, as high speed measurement devices, can detect abnormal behaviors around their location. On the other side, the recorded data from PMUs can be easily extracted by ERCOT engineers for tuning the parameters to improve existing models, and further identify the actual cause of problems. IV. CONCLUSIONS PMUs have been installed in ERCOT grid in recent years, and a secure communication network has been set up to transfer phasor data from the PMUs or TSP s PDCs to ERCOT s PDC. Although currently the number of PMUs is limited when comparing to other interconnections, their benefits have already been recognized by both ERCOT operations and planning, in the areas of real-time small signal stability monitoring, system post-event analysis, and dynamic model verification. In the near future, more PMUs are expected to be installed to cover the rest part of grid. Redundant PDCs and communication network are also in consideration to improve phasor data quality. Future applications of PMU data include its use in real time state estimator to improve observability and measurement redundancy. ACKNOWLEDGMENT The authors would like to express our appreciation for the helps from all team members for our ERCOT phasor project...05 0.95..08.06.04.02 0.98 0.96 (a) Poorly-damped oscillation at low output (b) Un-damped oscillations at high output Fig.6 Recorded voltage oscillations at the WPP s point of interconnection (POI)..05 0.95.2. 0.9 0.8 PMU Simu Fig.7 Voltage responses at WPP s POI Fig. 8 Voltage response at WPP s POI at high wind output 4

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