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This paper addresses the problem of predicting a wind farm's power generation when no or few statistical data is available. The study is based on a time-series wind speed model and on a simple dynamic model of a DFIG wind turbine including cut-off and cut-in behaviours. The wind turbine is modeled as a stochastic hybrid system with three operation modes. Numerical results, obtained using Monte-Carlo...
The problem of choosing the optimal location and size for shunt capacitors in unbalanced distribution systems can be formulated as a mixed, non-linear, constrained optimization problem and is usually solved in deterministic scenarios. However, distribution systems are stochastic in nature, leading thus to inaccurate deterministic solutions. To take into account the unavoidable uncertainties which...
This work presents a procedure to validate sags monitoring results based on a stochastic assessment of voltage sag indices. The main practical use of this methodology is to analyze the accuracy of sag indices obtained from very short monitoring periods. Probabilistic models of several factors can be taken into account: lines and busbars fault rate, pre-fault voltage, fault type distribution, fault...
Hidden failures in protection schemes, the traditional N - 1 security criterion and the introduction of the electricity market are usually major causes in the recent wide area blackouts. In the present work, we address the reliability analysis of power systems using the Generalized Stochastic Petri Nets (GSPN). The proposed modeling approach considers not only the most common failures of power system...
This paper introduces the infeed modeling requirements for investigations on energy storage in power systems with complex spatial dependence structures between stochastic infeeds. It is shown that synthesizing multivariate time series, including correct modeling of persistence and spatial dependence, is crucial for obtaining statistically relevant results. A suited new multivariate time series model...
In power system planning and operation, accurate assessment of reliability worth is essential for making informed decisions. One common simplification when modeling power system reliability is assuming constant failure rates and non time-varying restoration times. However, historical outages show differently; failure rates and restoration times for especially overhead lines are dependent upon time-varying...
Up to now, to analyze and design the operational limits of transmission lines, many utilities still apply traditional deterministic approaches, which have long been recognized as excessively conservative. In this work, we propose a different overload protection scheme in order to increase the line ampacity. The main idea is to include the thermal model of overhead lines inside the protection and then...
Multi-stage decision making, a fundamental tenet of stochastic programming, resonates well with the practice of the electricity markets. The day-ahead market, used to commit the generators, bears uncertainty in the power demand and physical conditions of the generators and transmission lines. The situation becomes less uncertain in the real-time market, where the dispatch is decided. Although traditional...
Wind energy on a power system alters the unit commitment and dispatch problem, as it adds a stochastic element due to the uncertainty of wind power forecasts. By explicitly taking into account the stochastic nature of wind power, it is expected that better schedules should be produced, thereby reducing costs on the system. This paper compares a stochastically optimised unit commitment and dispatch...
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