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Voltage phase angle variation in relation to wind power
Abstract
Monitoring of some of the effects of wind power on the transmission grid is possible from 120 V wall outlet measurements. The penetration levels of wind power are reflected in synchronized phasor measurements taken by the independent synchrophasor network located at the University of Texas at Austin. The independent synchrophasor network is unique because it takes single-phase synchronized voltage phasor measurements from 120 V wall outlets. These measurements are shown to be suitable for observing some of the effects of wind power penetration on power system parameters such as the voltage phase angle. This is the beginning of research on the topic of quantifying the effects of wind power on the grid as seen in Texas Independent Synchrophasor Network measurements.
... In recent years, the growing demand for energy has resulted in the expansion of the power generation portfolio to include renewables such as solar and wind power. These Variable Energy Resource (VERs) inject uncertain amounts of power at time scales faster and generally dissimilar to that previously found in typical load profiles due to the unpredictable weather conditions [7]. Figure 1 shows the power spectra of power spectra of real power output from two wind farms and one solar PV array [8]. ...
... where η is the generator efficiency and it varies with the choice of generator [38]. The wind active power injection is then ultimately tied to the state vector via Equation 2. The effect of wind generation on the phase angle has been establish by Allen in Texas-EROCT synchrophasor network [7]. ...
For many decades, state estimation has been a critical technology in the energy management systems utilized by transmission system operators. Over time, it has become a mature technology that provides an accurate representation of system state under fairly stable and well understood system operation. The integration of variable energy resources such as wind and solar generation, however, introduce new dynamics and uncertainties into the system. Along with increase in variability which needs real time monitoring, state estimation will be extended to the distribution networks which increase the size of the problem. Conventional solutions to this problem result in large problem sets being solved at a faster rate thereby becoming computationally intensive. This work builds upon the recent contribution of event-triggering where the state estimator is only called in the case of considerable “novelty” in the evolution of the system state. Specifically, the concept of tracking saves significant computational effort at minimal expense of error by allowing for the update of system state between two consecutive triggered instances. The new event-triggered tracking state estimator (ETTSE) is demonstrated on the standard IEEE 14-bus system, and the results are observed for a specific bus.
... The calculation doesn't break down the whole hour of information without a moment's delay, yet rather investigates a window of PMU information, appointed to the variable yWindow. The subroutine examination on the window of information yWindow is applied for each moving window of information until the finish of the whole hour of the signal y [12]. ...
Smart grid is an advanced electrical supply system in which data is conveyed bi directionally utilizing computerized correspondence innovation. Observing, investigating, controlling and correspondence happens inside the inventory network accordingly improving proficiency, lessening vitality utilization and so on. A Phasor Measurement Unit (PMU) measures electrical signals in system. PMUs are utilized in the transmission side of the system. These are introduced at different places on the network and are time synchronized utilizing Global Positioning System (GPS). Thus real time synchronized continuous estimations are obtained from different estimation points on the network. PMU helps in automating the system. A system of PMUs called Wide Area Measurement System (WAMS) can be utilized for huge scale monitoring of the network. Power outages and load shedding in the system can avoided. PMUs can synchronously gauge voltage and current, phase angle, power, energy import & export, frequency, frequency deviations, etc. These parameters can be utilized to tell about the state of the system. The optimal placement of PMUs & Event detection techniques from the synchronized PMU data are determined using MATLAB software. Programming PMUs to detect the events in the system & placing it optimally can help diminish the huge expense and equipment intricacy.
For many decades, state estimation (SE) has been a critical technology for energy management systems utilized by power system operators. Over time, it has become a mature technology that provides an accurate representation of system state under fairly stable and well understood system operation. The integration of variable energy resources (VERs) such as wind and solar generation, however, introduces new fast frequency dynamics and uncertainties into the system. Furthermore, such renewable energy is often integrated into the distribution system thus requiring real-time monitoring all the way to the periphery of the power grid topology and not just the (central) transmission system. The conventional solution is two fold: solve the SE problem (1) at a faster rate in accordance with the newly added VER dynamics and (2) for the entire power grid topology including the transmission and distribution systems. Such an approach results in exponentially growing problem sets which need to be solver at faster rates. This work seeks to address these two simultaneous requirements and builds upon two recent SE methods which incorporate event-triggering such that the state estimator is only called in the case of considerable novelty in the evolution of the system state. The first method incorporates only event-triggering while the second adds the concept of tracking. Both SE methods are demonstrated on the standard IEEE 14-bus system and the results are observed for a specific bus for two difference scenarios: (1) a spike in the wind power injection and (2) ramp events with higher variability. Relative to traditional state estimation, the numerical case studies showed that the proposed methods can result in computational time reductions of 90%. These results were supported by a theoretical discussion of the computational complexity of three SE techniques. The work concludes that the proposed SE techniques demonstrate practical improvements to the computational complexity of classical state estimation. In such a way, state estimation can continue to support the necessary control actions to mitigate the imbalances resulting from the uncertainties in renewables.
This paper examines the synchrophasor data for 221 generating unit trips in ERCOT over the time period during September 2009 through June 2010. Specifically, the phase angle variation between West Texas (i.e., wind country) with regard to central ERCOT is studied. The results show no clear relationship between wind generation and damped resonant frequency (f) or normalized damping ratio (ζ).
Disturbances in power systems cause oscillations which can be observed in measured signals throughout the network. This paper examines the relationship between events in the system and the measured modal content of the oscillations. Identifying patterns or distinguishing characteristics from oscillation monitoring data is examined in the context of linear system theory and control theory. Our results show that with knowledge of the nominal modes of certain generators, it is often possible to distinguish an event at one of these generators.
Advances in synchrophasor technology have led to synchrophasor applications progressing from being simply visualization, data archiving, and postmortem analysis tools to real-time control systems. These new systems can produce, consume, time align, and process synchrophasor data. A significant advancement in this technology is that the results of synchrophasor processing translate into alarm or control actions that are issued in real time. With this powerful, new technology, former complex synchrophasor applications such as system integrity protection schemes (SIPS) and assessment of power system stability over large geographical areas are easier to implement, have fewer components, and are more reliable than traditional solutions. The paper discusses how to accomplish the following tasks: Detecting out-of-step conditions. Identifying inter-area power oscillations. Protecting multi-terminal substation busbars. Identifying current and voltage measurement errors.
The estimation of oscillation modes is important to the monitoring and damping of low frequency oscillation in power system. Ambient data caused by low level stochastic disturbances can be used to identify the low frequency oscillation properties. In this paper, the autoregressive moving averaging(ARMA) method is used to analyze the ambient data. As a key step in the ARMA method, the selection of model order is primarily studied. By comparing different model order selection criterions, Bayesian information criterion(BIC) is chosen to determine the model order, and ARMA (2n, 2n-1) modeling procedure is adopted to improve the calculation efficiency. The overall flowchart of the proposed low frequency oscillation analysis based on ambient data is also given, which is designed for the online application. The advantages of this approach are validated through simulations in 36-node benchmark system and practical ambient signals measured in China Southern power grid.
The importance of having phasor measurement units or PMUs in an electric grid is widely recognized. However, the number of PMUs on a large system is limited by cost and the placement of PMUs must be addressed. The main objective of this research is to create an algorithm to identify buses that are the best candidates for PMU placement based on certain requirements. The monitoring of certain grid events like transmission line failure or generator failure must be possible from the selected PMU locations. In addition, the PMUs must be distributed evenly so that critical parts of the grid are visible. At the same time, there should be no or little redundancy in the PMU readings unless it is intentional to provide additional data reliability. The algorithm, once developed, is then applied to the electric network directed and operated by the Electric Reliability Council of Texas (ERCOT). After analyzing the results, clusters or group of buses are identified in each operational area in the ERCOT gird, where the PMUs should be located. The PMU can be located at any of the bus in the cluster. In future it is desirable to expand the algorithm to consider the geographical divisions in the ERCOT grid along with the commercial divisions.
The North American Frequency Monitoring Network (FNET) is a wide-area measurement system that monitors the North American Interconnections at distribution voltage level. A situational awareness system has been implemented on the server located at Virginia Tech to detect and analyze power system disturbances in near-real time. This paper demonstrates the viability of monitoring bulk transmission systems at a very low voltage level by discussing several major disturbances in the Eastern Interconnection (EI) observed by FNET. Important parameters of power systems, such as frequency, voltage and phase angle, are examined to understand system behavior during disturbances. The recordings and analysis show that a great deal of valuable information about dynamics in transmission systems can be obtained at a lower voltage level. The disturbance location estimation is also analyzed as an application of the distribution-level measurements.
Increasing amounts of wind turbines are connected to electrical power systems. This affects many aspects of their operation and behaviour. In this paper, the impact of large scale wind power generation on power system oscillations is treated. The three main types of power system oscillations, namely oscillations of a group of generators against a strong system and intra- and inter-area oscillations are studied. To this end, test systems are used. The effect of wind power on the oscillations is investigated by gradually replacing the power generated by the synchronous generators in the system by power from either constant or variable speed wind turbines, while observing the movement of the eigenvalues through the complex plane. From the results, it is concluded that the effect of wind power on power system oscillations depends on the wind turbine concept (constant or variable speed) and on the wind power penetration. In most cases, an increase in frequency and damping of power system oscillations was observed. This observation is caused by a relative reduction in size of the synchronous generators that engage in power system oscillations, which is equivalent to strengthening their mutual coupling. Further, it was shown that constant speed wind turbines damp power system oscillations more than variable speed turbines. This is caused by the damping effect of the squirrel cage induction generator used in constant speed wind turbines.
With the growing implementation of synchrophasors or PMU's across the power grid, it is now possible to observe and analyze system wide dynamic phenomena in real-time. This paper presents the framework of an automatic real-time oscillation monitoring expert system for extracting the modal information and mode shape of electromagnetic oscillations while they are still emerging in the real power system. The algorithms use three signal processing engines, namely, Prony's method, matrix pencil method and Hankel total least squares (HTLS) method. Results from these engines are processed using a custom developed set of rules for handling the complexities of modal analysis from real-time PMU measurements. The results are illustrated on several actual PMU recordings from power systems in North America. A simple powerful control design is also explored to initiate a supplementary HVDC modulation scheme to damp out inter-area oscillations when the oscillation monitoring system detects poorly damped oscillations.
The impact of power fluctuations arising from fixed-speed wind turbines on the magnitude and frequency of inter-area oscillations was investigated. The authors used data acquisition equipment to record the power flow on the interconnector between the Northern Ireland and Republic of Ireland systems. By monitoring the interconnector oscillation using a fast Fourier transform, it was possible to determine the magnitude and frequency of the inter-area oscillation between the Northern Ireland electricity system and that of the electricity supply board. Analysis was preformed to determine the relationship (if any) between the inter-area oscillation and the observed wind power generation at the corresponding time. Subsequently, regression analysis was introduced to model this relationship between the FFT output and the wind power generation. The effect of conventional generators on the magnitude and frequency of the inter-area oscillation was also considered.
Phasor measurements were introduced as a specialized power system measurement in 1986. Following a paper published in 1983 describing the technique, Virginia Tech produced prototype phasor measurement units (PMU s) that were supplied to American Electric Power (AE P) and the Bonneville Power Administration (BPA). These units were tested and used by these utilities for several years before the first commercial unit, the Macrodyne 1690, was introduced in 1991. Using the original PMU s, AE P and BPA built phasor measurement systems that only provided recorded data for analysis with basic plotting tools. BPA redesigned the measurement system in 1997 into a true real-time, widearea measurement system (Figure 1) using commercial PMU s and a custom phasor data concentrator (PDC ). Since then, many phasor data systems have been developed and deployed throughout the world. Many more PMU models have become available with a range of options. Several variations of PDC units have been produced, and many applications are available for analysis of recorded phasor data as well as real-time display and alarming. This article examines the current phasor measurement systems in North America.
Monitoring of events in the power system provides a great deal of insight into the behavior of the system. Events with impact on the entire power system typically occur in or near the transmission network and are therefore best monitored at transmission system substations. This puts great demands on the equipment and in general restricts the use of the data since it becomes property of the transmission system operator. An alternative is to measure at lower voltage levels. This paper documents the close agreement between voltage and frequency at low and high voltage levels during a remote and a nearby fault in the transmission network. The very high quality of the data suggests that valuable information about the transmission system can be obtained at lower voltages.
Monitoring the Power Grid
- B Bhargava
- G Rodriguez
Texas Synchrophasor Network Observations
- W M Grady