Title :
Angular Instability “Day Ahead” Risk Forecasting ‑ Probabilistic Dependency on Load
Author :
Ríos, M.A. ; Arrieta, R. ; Torres, A.
Abstract :
This paper proposes a methodology in order to evaluate the probabilistic impact of load variations on angular stability of power systems, around 24 hours day ahead planned operation conditions. For each operation condition, the load is forecasted; however, at the operation moment the real load is different. So, a probabilistic small signal analysis around the operational condition allows the establishment of a probabilistic density function (pdf) related to the behaviour of critical eigenvalues of the dynamic lineal system. The hourly pdf is computed based on an hourly Monte Carlo simulation and, once the main statistical moments are computed, the angular instability is determined from the pdf. The method is tested using the New England 39-node system.
Keywords :
Covariance matrix; Demand forecasting; Load forecasting; Monte Carlo methods; Modal Analysis; Monte Carlo Simulation; Power System Stability; Risk Evaluation of Operation Planning; Small Signal Analysis;
Journal_Title :
Latin America Transactions, IEEE (Revista IEEE America Latina)
DOI :
10.1109/T-LA.2007.4445710