The objective of this paper is to assess the chronological variations in the available transfer capability (ATC) caused by uncertainties associated with hourly load fluctuations and equipment unavailabilities. The system states resulting from these uncertainties are generated using the Monte Carlo method with sequential simulation (MCMSS). The ATC for each generated state is evaluated through a linear dc optimal power flow (OPF). The test results, with a modified version of the IEEE Reliability Test System, demonstrate that the time-dependent uncertainties have a significant impact on the ATC. These effects have been assessed through statistical indexes such as expected values, box plot, and percentiles.Index Terms-Available transfer capability (ATC), composite system, linear programming, Monte Carlo method (MCM), power system reliability.
Several papers have recognized the effect of uncertainties in voltage stability analysis through probabilistic methods. In these papers, the unstable states are generally identified by the unsolvability of the power flow equations or by violations in the voltage stability margin limit. However, voltage stability problems may also be associated with a loss in voltage controllability, when a voltage control action has an effect which is contrary to what is usually expected. The main aim of this paper is to include unstable states caused by unsolvability and voltage controllability loss in the voltage stability probabilistic assessment. This goal is achieved through the combination of three techniques: the Monte Carlo Simulation Method, the nonlinear optimal power flow and the D' matrix method. These three techniques permit the inclusion of a new issue in the computation of voltage instability risk: the unstable states stemming from controllability loss.
Index Terms-Composite systems, interior point method, MonteCarlo simulation, optimal power flow, probabilistic methods, sensitivity analysis, voltage stability.
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