The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A major ongoing effort by utilities is to improve their emergency preparedness process for weather events, in order to: 1) reduce outage time 2) reduce repair and restoration costs and 3) improve customer satisfaction. This paper proposes a method for forecasting the number of damages of different types that will result from a weather event, up to 3 days before the event actually occurs. The proposed...
Ever increasing penetration of wind power generation along with the integration of energy storage systems (ESSs) makes the successive states of the power system interdependent and more stochastic. Appropriate stochastic modeling of wind power is required to deal with the existence of uncertainty either in observations of the data (spatial) or in the characteristics that drive the evolution of the...
This paper describes a method for trip-purpose based modeling Plug-in Electric Vehicle (PEV) travel profiles to be used in estimating charging load times and durations. The method uses concepts from Activity-Based Travel Demand modeling to schedule PEV driver activities resulting in driving times and durations, from which the PEV charging profile may be determined (including when the PEV is available...
Accurate information about dynamic states is important for efficient control and operation of a power system. This paper compares the performance of four Bayesian-based filtering approaches in estimating dynamic states of a synchronous machine using PMU data. The four methods are Extended Kalman Filter, Unscented Kalman Filter, Ensemble Kalman Filter, and Particle Filter. The statistical performance...
Design of voltage source converters (VSC) for high-voltage direct current (HVdc) systems requires extensive simulation tools that are accurate and reliable. Before the installation of VSC-HVdc links, different simulation-based studies need to be performed by different parties and using different electromagnetic transient (EMT) simulation platforms. Previous work shows that even with a pedantic re-implementation...
Due to the variability of wind power, it is imperative to accurately and timely forecast wind generation to enhance the flexibility and reliability of the operation and control of real-time power systems. Special events such as ramps and spikes are hard to predict with traditional methods using solely recently measured data. In this paper, a new Gaussian Process model with hybrid training data taken...
Demand Response (DR) is a promising solution to deal with supply/demand imbalances in the power systems. To appreciate the availability of DR, it is important to include end user behavior in the analysis. In this paper, a model that can generate representative occupancy profiles in single office rooms is presented. The used method is non-homogeneous Markov chain modeling, along with exploratory data...
The paper considers stochastic optimization of the electricity procurement in the day-ahead power market. The novelty is in addressing the random errors of time series forecasting of electrical power loads and prices in the procurement. This problem is currently important because of the increased random variability in the power grid that is caused by growing integration of renewable generation. This...
This paper presents a novel detrending algorithm that allows long-term natural gas demand signals to be used effectively to generate high quality short-term natural gas demand forecasting models. Short data sets in natural gas forecasting inadequately represent the range of consumption patterns necessary for accurate short-term forecasting. In contrast, longer data sets present a wide range of customer...
In power systems forced oscillations occur, and identification of these oscillations is important for the proper operation of the system. Two of the parameters of interest in analyzing and addressing forced oscillations are the starting and ending points. To obtain estimates of these parameters, this paper proposes a time-localization algorithm based on the geometric analysis of the sample cross-correlation...
Load modelling is a crucial part in modelling a power system. The complex, nonlinear and stochastic characteristics of power load increase the difficulty of modelling. In this paper, a new approach of ambient signal based load model parameter identification method is proposed to solve this problem. With the proposed method, load model parameter can be identified in any time regardless of the existence...
Due to the growth in the number of residential photo voltaic (PV) adoptions in the past five years, there is a need in the electricity industry for a widely-accessible model that predicts the adoption of PV based on different business and policy decisions. We analyze historical adoption patterns and find that monetary savings is the most important factor in the adoption of PV, superseding all socioeconomic...
In this paper, an approach is proposed to improve linear models adopted in small-signal stability studies using information extracted from measured outputs of real system, as small disturbance data recorded by phasor measurement units (PMU). With this aim, a trajectory sensitivity technique is applied on the mismatch between the output of the simulated model and the response of the real system. Using...
Sustained oscillations are one of major stability concerns of a power system operator. In order to take effective remedial reactions, it is preferred to detect sustained oscillations at their early stage. Previously, self-coherence spectra were used to detect sustained oscillations using phasor measurement unit (PMU) data. This paper proposes a hypothesis test using a bootstrap method to set up a...
Nonlinearity of power flow equations is one of the major underlying factors in a power systems operation complexity. The need for a robust and less complex models rises in a volatile, dynamic and real time scenario. This paper introduces new empirical models using multivariate linear regression (MLR) methods with least squares for both real and reactive branch flows. The models do not make prior assumptions...
System Protection Schemes (SPS) being widely used in smart grid often involve multiple geographically distributed devices that cooperate in a timely manner which relies highly on the wide area communication. Due to this functional nature, SPSs are extremely vulnerable when cyber-attacks take place and significant impacts and losses might follow. Under such circumstances, risk assessment for SPS has...
This paper presents a dynamic simulation tool for examining the future impact of plug-in electric vehicles (PEVs) on residential sector power demand. First, the modeling approach used during the development of this tool is described. Markov chain based occupant behavior models developed using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS) are used in conjunction with...
To handle significant variability in loads, renewable energy generation, as well as various contingencies, (two-stage) robust optimization method has been adopted to construct unit commitment models and to ensure reliable solutions. In this paper, we further explore and extend the modeling capacity of two-stage robust optimization and present two new robust unit commitment variants: the expanded robust...
Wind power ramp events (WPREs) have received increasing attention in recent years due to their significant impact on the reliability of power grid operations. In this paper, a novel WPRE forecasting method is proposed which is able to estimate the probability distributions of three important properties of the WPREs. To do so, a neural network (NN) is first proposed to model the wind power generation...
In this paper the interactions between component failures are quantified and the interaction matrix and interaction network are obtained. The quantified interactions can capture the general propagation patterns of the cascades from utilities or simulation, thus helping to better understand how cascading failures propagate and to identify key links and key components that are crucial for cascading...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.