This paper develops a systematic framework for analyzing how low frequency forced oscillations propagate in electric power systems. Using this framework, the paper shows how to mathematically justify the so-called Dissipating Energy Flow (DEF) forced oscillation source-location technique, and the DEF’s specific deficiencies are pinpointed. Leveraging incremental passivity enforcement, a set of simple inference problems are introduced whose solutions can be used in conjunction with the proposed propagation framework in order to enhance the effectiveness of the DEF method. The proposed techniques are illustrated on the IEEE 39-bus New England test system.
In this paper, a Bayesian framework, via a two-stage Maximum A Posteriori optimization routine, is employed in order to locate the most probable source of a forced oscillation given an uncertain prior model. The approach leverages an equivalent circuit representation of the system in the frequency domain and employs a numerical procedure which makes the problem suitable for real time application. The derived framework lends itself to successful performance in the presence of PMU measurement noise, high generator parameter uncertainty, and multiple forced oscillations occurring simultaneously. The approach is tested on a 4-bus system with a single forced oscillation source and on the WECC 179-bus system with multiple oscillation sources.
Despite wide-scale deployment of phasor measurement unit technology, locating the sources of low frequency forced oscillations in power systems is still an open research topic. The dissipating energy flow method is one source location technique which has performed remarkably well in both simulation and real time application at ISO New England. The method has several deficiencies, though, which are still poorly understood. This paper borrows the concepts of passivity and positive realness from the controls literature in order to interpret the dissipating energy flow method, pinpoint the reasons for its deficiencies, and set up a framework for improving the method. The theorems presented in this paper are then tested via simulation on a simple infinite bus power system model.
This paper presents a method that gauges and improves the voltage stability of a system using the statistics present in PMU data streams. Leveraging an analytical solver to determine a range of “critical” bus voltage variances, the presented methods monitor raw statistical data in an observable load pocket to determine when control actions are needed to mitigate the risk of voltage collapse. A simple reactive power controller is then implemented, which acts dynamically to maintain an acceptable voltage stability margin within the system. Time domain simulations on 3-bus and 39-bus test cases demonstrate that the resulting statistical controller can outperform more conventional feedback control systems by maintaining voltage stability margins while loads simultaneously increase and fluctuate.
(Primary author: Petr Vorobev) – Frequency control by energy storage units has been extensively promoted during the last years due to development in energy storage and power electronics technologies. The outstanding ramping capabilities of storage units makes them attractive for fast response services. However, performance metrics of such services are not always obvious and the true benefit of using storage is hard to assess. In the present manuscript we have developed an easy-to-use method for performance assessment and control design for energy storage, participating in frequency control under stochastic load perturbations. As a demonstration of our method, we perform a control design for single area system with energy storage and show that even storage with a very modest power capacity is sufficient to completely take over the primary frequency control duty. Since our method does not require explicit dynamic simulations over stochastic model, it is easily generalizable on more complex systems.
(Primary author: Petr Vorobev) – Stability certification of microgrids can be challenging due to the lack of information on exact values of system parameters. Moreover, full-scale direct stability analysis for every system configuration can be economically and technically unjustified. There exist a demand for simple conditions imposed on system components that guarantee the whole system stability under arbitrary interconnections. Most of existing methods are relying on the so-called passivity property which can be difficult to realize by all the system components simultaneously. In the present manuscript we develop an approach for certifying the system stability by separately considering its properties in different regions of frequency domain. We illustrate our method on the case of droop-controlled inverters and show that while these inverters can never be made passive, reasonable stability certificates can be formulated by careful consideration of their input admittance for different frequency regions. We discuss the generalization of the method for different types of microgrid components
This paper proposes a systematic method for locating the source of a forced oscillation by considering a generator’s response to fluctuations of its terminal voltages and currents. It is shown that a generator can be represented as an effective admittance matrix with respect to low-frequency oscillations, and an explicit form for this matrix, for various generator models, is derived. Furthermore, it is shown that a source generator, in addition to its effective admittance, is characterized by the presence of an effective current source, thus giving a natural qualitative distinction between source and nonsource generators.
Spectral decomposition of the reduced power flow Jacobian is used to pinpoint buses with poor voltage support. This analysis is combined with online PMU processing to mitigate the effects of voltage instability. The ideas of this paper are interesting (static spectral analysis + online dynamic data processing), but the mechanisms are underdeveloped.
This behemoth represents my MS thesis work. Its primary accomplishment is the development of a reactive power controller which actively responds to bus voltage variance. Voltage variance can be a more useful control input signal than voltage mean in certain circumstances. To watch my thesis defense (8/9/2016) on YouTube, please watch part 1 , part 2 , part 3 , and part 4 sequentially.
As an undergraduate RA, I worked on a federally funded study which sought to answer the following question: what sort of pricing structure will most effectively encourage residential electricity customers to participate in demand response? I helped analyze and sort smart meter data from several thousand Rutland, Vermont study participants. I am listed as a technical assistant in the final report.
This document derives the AC power flow equations, develops system and load noise models, and then shows how the state and algebraic variable covariance matrices may be computed. Many of these ideas are based on work done by Dr. Goodarz Ghanavati.
We use a mass-spring damper system to intuitively show how a forced mechanical oscillation propagates through a system.
This document goes into painstaking detail to explain how synchronous generators may be simulated in a transmission network while preserving all network dynamics (phasors are not used to compute active & reactive power flows).
How does one convert the distributed parameters of a transmission line into lumped parameters? This derivation will answer all of your lingering questions.
Causes and consequences of the power system failure in Tokyo in 1987.
Causes and consequences of the power system failure in the Northeastern US in 2003.
In this (unpolished) academic paper, I present a useful framework (using random variable analysis) for quantifying the strength of the load noise associated with a load bus. Next, I present a method for calculating a critical bus voltage variance which should not be exceeded. This will occur if the system is approaching “static” voltage collapse.
My senior design team built a device which measures 1) forces applied to cross country ski poles and 2) the acceleration of the athlete. It provided real-time audio feedback for performance enhancement and data aggregation for post workout analysis. The final product was somewhat successful, but we would need to put in additional work to bring it out of the prototype stage.
How much money will a college student save by foregoing a University meal plan and shopping for him/herself? I tracked every nickle I spent on food for two semesters during my junior year at UVM.