The goal of this effort was to assess the effect of high penetration solar deployment on the small signal stability of the western North American power system (wNAPS). Small signal stability is concerned with the system response to small disturbances, where the system is operating in a linear region. The study area consisted of the region governed by the Western Electricity Coordinating Council (WECC). General Electric's Positive Sequence Load Flow software (PSLF®) was employed to simulate the power system. A resistive brake insertion was employed to stimulate the system. The data was then analyzed in MATLAB® using subspace methods (Eigensystem Realization Algorithm). Two different WECC base cases were analyzed: 2022 light spring and 2016 heavy summer. Each base case was also modified to increase the percentage of wind and solar. In order to keep power flows the same, the modified cases replaced conventional generation with renewable generation. The replacements were performed on a regional basis so that solar and wind were placed in suitable locations. The main finding was that increased renewable penetration increases the frequency of inter-area modes, with minimal impact on damping. The slight increase in mode frequency was consistent with the loss of inertia as conventional generation is replaced with wind and solar. Then, distributed control of renewable generation was assessed as a potential mitigation, along with an analysis of the impact of communications latency on the distributed control algorithms.
A central control algorithm was developed to utilize photovoltaic system advanced inverter functions, specifically fixed power factor and constant reactive power, to provide distribution system voltage regulation and to mitigate voltage regulator tap operations by using voltage measurements at the regulator. As with any centralized control strategy, the capabilities of the control require a reliable and fast communication infrastructure. These communication requirements were evaluated by varying the interval at which the controller sends dispatch commands and evaluating the effectiveness to mitigate tap operations. The control strategy was demonstrated to perform well for communication intervals faster than the delay on the voltage regulator (30 seconds). The communication reliability, latency, and bandwidth requirements were also evaluated.
FERC order 755 and FERC order 784 provide pay-for-performance requirements and direct utilities and independent system operators to consider speed and accuracy when purchasing frequency regulation. Independent System Operators (ISOs) have differing implementations of pay-for-performance. This paper focuses on the PJM implementation. PJM is a regional transmission organization in the northeastern United States that serves 13 states and the District of Columbia. PJM's implementation employs a two part payment based on the Regulation Market Capability Clearing price (RMCCP) and the Regulation Market Performance Clearing Price (RMPCP). The performance credit includes a mileage ratio. Both the RMCCP and RMPCP employ an actual performance score. Using the PJM remuneration model, this paper outlines the calculations required to estimate the maximum potential revenue from participation in arbitrage and regulation in day-ahead markets using linear programming. Historical PJM data from 2014 and 2015 was then used to evaluate the maximum potential revenue from a 5 MWh, 20 MW system based on the Beacon Power Hazle Township flywheel plant. Finally, a heuristic trading algorithm that does not require perfect foresight was evaluated against the results of the optimization algorithm.
This paper describes a control scheme to mitigate inter-area oscillations through active damping. The control system uses real-time phasor measurement unit (PMU) feedback to construct a commanded power signal to modulate the flow of real power over the Pacific DC Intertie (PDCI) located in the western North American Power System (wNAPS). A hardware prototype was constructed to implement the control scheme. To ensure safe and reliable performance, the project integrates a supervisory system to ensure the controller is operating as expected at all times. A suite of supervisory functions are implemented across three hardware platforms. If any controller mal-function is detected, the supervisory system promptly disables the controller through a bumpless transfer method. This paper presents a detailed description of the control scheme, simulation results, the bumpless transfer method, and a redundancy and diversity method in the selection of PMU signals for feedback. This paper also describes in detail the supervisory system implemented to ensure safe and reliable damping performance of the real-time wide area damping controller.
This paper presents a control design methodology that begins to address high penetration of renewable energy sources into networked AC microgrid systems. To bring about high performing microgrid systems that contain large amounts of stochastic sources and loads is a major goal for the future of electric power systems. Alternative methods for controlling and analyzing AC microgrid systems will provide understanding into tradeoffs that can be made during the design phase. This paper utilizes a control design methodology, based on Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) [1] that regulates renewable energy sources, loads and identifies energy storage requirements for an AC microgrid system. Both static and dynamic stability conditions are derived for the AC microgrid system. Numerical simulations are performed to demonstrate stability and performance. Two scenarios are considered; i) simple random stochastic renewable source and load AC Microgrid example and ii) a random variable pulse load application for Navy ship AC microgrid systems.
With increasing renewable penetrations and advancements in power electronics associated with smart grid technologies, distributed control of the power grid is quickly becoming a necessity. Once communications are introduced into a control system, the impacts of latency and unreliable communications quickly become a priority. Vector Lyapunov techniques are well suited for the analysis of control systems with structured perturbations. These perturbations can be employed to model uncertainty in communications as well as parameter uncertainty. In this paper, we present results for small signal stability of a simplified two area power system model for several scenarios: bandwidth limited local communications and tie line uncertainty; local communications and bandwidth limited global communications combined with tie line uncertainty; and uncertainty in global communications. These results are intended to be a starting point for the analysis of the impact of communications uncertainty on the stability of power systems.
The goal of this effort was to apply four potential control analysis/design approaches to the design of distributed grid control systems to address the impact of latency and communications uncertainty with high penetrations of photovoltaic (PV) generation. The four techniques considered were: optimal fixed structure control; Nyquist stability criterion; vector Lyapunov analysis; and Hamiltonian design methods. A reduced order model of the Western Electricity Coordinating Council (WECC) developed for the Matlab Power Systems Toolbox (PST) was employed for the study, as well as representative smaller systems (e.g., a two-area, three-area, and four-area power system). Excellent results were obtained with the optimal fixed structure approach, and the methodology we developed was published in a journal article. This approach is promising because it offers a method for designing optimal control systems with the feedback signals available from Phasor Measurement Unit (PMU) data as opposed to full state feedback or the design of an observer. The Nyquist approach inherently handles time delay and incorporates performance guarantees (e.g., gain and phase margin). We developed a technique that works for moderate sized systems, but the approach does not scale well to extremely large system because of computational complexity. The vector Lyapunov approach was applied to a two area model to demonstrate the utility for modeling communications uncertainty. Application to large power systems requires a method to automatically expand/contract the state space and partition the system so that communications uncertainty can be considered. The Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) design methodology was selected to investigate grid systems for energy storage requirements to support high penetration of variable or stochastic generation (such as wind and PV) and loads. This method was applied to several small system models.
This paper outlines the calculations required to estimate the maximum potential revenue from participation in arbitrage and regulation in day-ahead markets using linear programming. Then, we use historical Electricity Reliability Council of Texas (ERCOT) data from 2011-2013 to evaluate the maximum potential revenue from a hypothetical 32 MWh, 8 MW system. We investigate the maximum potential revenue from two different scenarios: arbitrage only and arbitrage combined with regulation. This analysis was performed for each load zone over the same period to show the impact of location and to identify trends in the opportunities for energy storage. Our analysis shows that, with perfect foresight, participation in the regulation market would have produced more than twice the revenue compared to arbitrage in the ERCOT market in 2011-2013. Over the last three years, there has been a significant decrease in the potential revenue for an energy storage system. We also quantify the impact of location on potential revenue.
Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase significantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, blob tracking is the norm. For higher resolution data, additional information may be employed in the detection and classification steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment. The algorithms considered are: random sample consensus (RANSAC), Markov chain Monte Carlo data association (MCMCDA), tracklet inference from factor graphs, and a proximity tracker. Each algorithm was tested on a combination of real and simulated data and evaluated against a common set of metrics.
Low signal-to-noise data processing algorithms for improved detection, tracking, discrimination and situational threat assessment are a key research challenge. As sensor technologies progress, the number of pixels will increase signi cantly. This will result in increased resolution, which could improve object discrimination, but unfortunately, will also result in a significant increase in the number of potential targets to track. Many tracking techniques, like multi-hypothesis trackers, suffer from a combinatorial explosion as the number of potential targets increase. As the resolution increases, the phenomenology applied towards detection algorithms also changes. For low resolution sensors, "blob" tracking is the norm. For higher resolution data, additional information may be employed in the detection and classfication steps. The most challenging scenarios are those where the targets cannot be fully resolved, yet must be tracked and distinguished for neighboring closely spaced objects. Tracking vehicles in an urban environment is an example of such a challenging scenario. This report evaluates several potential tracking algorithms for large-scale tracking in an urban environment.
Electromechanical oscillations often limit transmission capacity in the western North American Power System (termed the wNAPS). Recent research and development has focused on employing large-scale damping controls via wide-area feedback. Such an approach is made possible by the recent installation of a wide-area real-time measurement system based upon Phasor Measurement Unit (PMU) technology. One potential large-scale damping approach is based on energy storage devices. Such an approach has considerable promise for damping oscillations. This paper considers the placement of such devices within the wNAPS system. We explore combining energy storage devices with HVDC modulation of the Pacific DC Intertie (PDCI). We include eigenanalysis of a reduced-order wNAPS system, detailed analysis of a basic two-area dynamic system, and full-order transient simulations. We conclude that the optimal energy storage location is in the area with the lower inertia.