Accurate estimation of the dynamic states a synchronous machine (e.g., rotor's angle and speed) is essential in monitoring controlling transient stability power system. It well known that covariance matrixes process noise (Q) measurement (R) have significant impact on Kalman filter's performance estimating states. The conventional ad-hoc approaches for are not adequate achieving best filtering performance. To address this problem, paper proposes an adaptive approach to adaptively estimate Q...

Accurate information about dynamic states is important for efficient control and operation of a power system. This paper compares the performance four Bayesian-based filtering approaches in estimating synchronous machine using phasor measurement unit data. The methods are extended Kalman filter, unscented ensemble particle filter. statistical each algorithm compared Monte Carlo two-area-four-machine test Under framework, robustness against noise process noise, sensitivity to sampling...

This paper proposes a regularized robust recursive least squares (R3LS) method for online estimation of power-system electromechanical modes based on synchronized phasor measurement unit (PMU) data. The proposed utilizes an autoregressive moving average exogenous (ARMAX) model to account typical data, which includes low-level pseudo-random probing, ambient, and ringdown A objective function is utilized reduce the negative influence from nontypical include outliers missing dynamic...

This paper proposes a robust recursive least square (RRLS) algorithm for online identification of power system modes based on measurement data. The data can be either ambient or ringdown. Also, the mode estimation is provided in real-time. validity proposed RRLS demonstrated with both simulation from 17-machine model and field wide area (WAMS). Comparison conventional (RLS) mean (LMS) algorithms shows that identify combined ringdown signals outliers missing real-time without noticeable...

In this paper, an extended particle filter (PF) is proposed to estimate the dynamic states of a synchronous machine using phasor measurement unit (PMU) data. A PF propagates mean and covariance via Monte Carlo simulation, easy implement, can be directly applied nonlinear system with non-Gaussian noise. The improves robustness basic through iterative sampling inflation dispersion. Using simulations practical noise model uncertainty considerations, PF's performance evaluated compared PF,...

Prony analysis has been applied to estimate inter-area oscillation modes using phasor measurement unit (PMU) measurements. To suppress noise and signal offset effects, a high-order model usually is used over-fit the data. As such, some trivial are intentionally added improve estimation accuracy of dominant modes. Therefore, reduce rate false alarms, it important distinguish between that reflect dynamic features power system artificially introduced accuracy. In this paper, stepwise-regression...

As renewable distributed energy resources (DERs) penetrate the power grid at an accelerating speed, it is essential for operators to have accurate solar photovoltaic (PV) forecasting efficient operations and planning. Generally, observed weather data are applied in PV generation model while practice based on forecasted data. A study uncertainty most commonly used variables presented. The 6 days ahead compared with results of analysis quantified by statistical metrics. In addition,...

This paper develops a self-coherence method for detecting sustained oscillations using phasor measurement unit (PMU) data. Sustained decrease system performance and introduce potential reliability issues. Timely detection of the at an early stage provides opportunity taking remedial reaction. Using high-speed time-synchronized PMU data, this details oscillation, even when oscillation amplitude is lower than ambient noise. Simulation field data are used to evaluate proposed method's...

In interconnected power systems, dynamic model reduction can be applied to generators outside the area of interest (i.e., study area) reduce computational cost associated with transient stability studies. This paper presents a method deriving reduced external based on response measurements. The consists three steps, namely dynamic-feature extraction, attribution, and reconstruction (DEAR). this method, feature extraction technique, such as singular value decomposition (SVD), is measured...

Accurate estimation of dynamic states (such as synchronous machine rotor angle and speed) is critical for monitoring controlling transient stability. Extended Kalman filter (EKF)-based approaches have been developed estimating states. In order to improve the EKF's performance in a machine, this paper proposes multi-step adaptive interpolation (MSAI) approach achieve balance between accuracy computational time. This consists three major steps. First, two indexes are calculated quantify...

Accurate forecasting of solar photovoltaic (PV) power for the next day plays an important role in unit commitment, economic dispatch, and storage system management. However, PV high temporal resolution such as five-minute is challenging because most models can only achieve same their predictors(i.e., weather variables), whose usually low (i.e., hourly). To address this challenge, similarity-based (SBFMs) are advocated paper to forecast using variables. effectively generalize model different...

Renewable energy sources (RESs) are increasingly used to meet the world's growing electrical needs, especially for economic benefits and environmental problems associated with fossil fuel use. Small-scale renewable sources, controllable loads, storage devices, other nonrenewable effectively integrated form a virtual power plant (VPP). Uncertainty in forecasting generation due intermittent nature of is one biggest challenges VPPs. Power by RESs changes day week, season, location, climate,...

Previously, variations of the Yule-Walker techniques have been applied successfully to give point estimates electromechanical modes a power system based on measured ambient data. This paper introduces bootstrap method confidence interval for modes. Simulation results from 19-machine model show validation and its consistence Monte Carlo methods. Actual measurement data taken western North American Power Grid in 2000 are processed using interarea mode damping ratios. The use multiple outputs...

This paper investigates the design of effective input signals for low-level probing power systems. In 2005, 2006, and 2008 Western Electricity Coordinating Council (WECC) conducted four large-scale system-wide tests western interconnected system where were injected by modulating control signal at Celilo end Pacific DC intertie. A major objective these is accurate estimation inter-area electromechanical modes. key aspect any such test an that leads to measured outputs rich in information...

Small signal stability problems are one of the major threats to grid and reliability. Prony analysis has been successfully applied on ringdown data monitor electromechanical modes a power system using phasor measurement unit (PMU) data. To facilitate an on-line application mode estimation, this paper develops recursive algorithm for implementing propose oscillation detection method detect in real time. By automatically detecting data, proposed helps guarantee that is properly timely Thus,...

This paper presents a general approach for coherency detection in bulk power systems using the projection pursuit (PP) theory. Supported by concept of center inertia (COI) systems, PP theory is employed to model wide-area as an optimization problem. In proposed method, optimal direction high dimensional orthogonal space explored order detect coherent groups via data from synchronous phasor measurement units (PMUs). Two quantitative indices constructed with assessment index (PI), objective...

The steady-state security region of the integrated energy system (IES) is a useful tool for rapid assessment and evaluation system. A complete characterization IES derived. derivation under nonlinear non-convex AC power flow model, gas uncertainty renewable without any linear simplification. Then novel robust computation scheme to compute proposed shown eliminate estimation errors existing methods. It that composed several disjoint components. Numerical studies are conducted show regions...

Power system mode shapes are a key indication of how dynamic components participate in low-frequency oscillations. Traditionally, calculated from linearized model. For large-scale power systems, obtaining accurate models is very difficult. Therefore, measurement-based shape estimation methods have certain advantages, especially for the application real-time small signal stability monitoring. In this paper, identification method proposed. The general relationship between transfer function...

ModeMeter techniques for real-time small-signal stability monitoring continue to mature, and more phasor measurements are available in power systems. It has come the stage bring modal information into system operation. This paper proposes establish a procedure Modal Analysis Grid Operations (MANGO). Complementary PSS other traditional modulation-based control, MANGO aims provide suggestions such as redispatching generation operators mitigate low-frequency oscillations. Load would normally...

Stochastic subspace identification (SSI) methods have been widely employed for oscillatory mode on probing and ambient data are reported to good performances. This work proposes a novel SSI-based approach identifying dominant from measurement extends the application of SSI ringdown condition. The proposed first constructs an initial cluster eigenvalues with repetitive calculations then utilises hierarchical clustering method extract modes cluster. within performed through varying model order...

A robust model for power system load forecasting covering different horizons of time from short-term to long-term is an indispensable tool have a better management the system. However, as horizon in increases, it will be more challenging accurate forecast. Machine learning methods got attention efficient dealing with stochastic pattern and resulting forecasting. In this study, problem case study New England Network studied using several commonly used machine such feedforward artificial...

Oscillations threaten the stability of a power system. Timely detecting oscillations can improve operators' situational awareness system and enable remedial reactions. To detect during their early stages, this paper proposes cross-coherence method using multiple-channel phasor measurement unit (PMU) data. are related to peaks in coherence spectra be detected by visual inspection setting up threshold. Using simulation data, it is shown that proposed even under low signal-to-noise ratios....

This paper proposes a new objective function and quantile regression (QR) algorithm for load forecasting (LF). In LF, the positive errors often have different economic impact from negative errors. Considering this difference, is proposed to put prices on QR used find optimal solution of function. Using normalized net energy New England network, method compared with time series method, artificial neural network support vector machine method. The simulation results show that more effective in...