GARCHSK Based Risk Assessment in Electric Power Industry

Rui Qing Wang; Zi Qian Xiao

doi:10.4028/www.scientific.net/AMM.345.368

Paper Titles

Numerical Simulation of Filling Process in Casting Based on a Hybrid Lattice Boltzmann and Particle Level Set Model
p.349

Study on Electronic Industry with an Application of Rectilinear Embedding in VLSI Placement
p.355

Research on Photovoltaic Industry with the MPPT Algorithm in PV System
p.359

Research and Design of Temperature Monitoring System in Industry Applications Based on PLC
p.364

GARCHSK Based Risk Assessment in Electric Power Industry
p.368

Simulation Analysis on Industrial Wastewater Adjust Pool Stench in Collecting Hood with Properties of Environmental Materials
p.372

Research on Petrochemical Industry with Analysis of Floating Roof Tanks under the Planar Inclined Foundation
p.376

Study on the Sustainable Development Evaluation of Logistics Enterprise for Industry Manufacturing Based on Data Envelopment Analysis
p.380

Study on the Model of Quantitative Evaluation of Circular Economy Development for Industry Manufacturing Based on WIOA
p.384

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 345GARCHSK Based Risk Assessment in Electric Power...

GARCHSK Based Risk Assessment in Electric Power Industry

Abstract:

The restructuring/deregulation in electric power industry has heightened the importance of risk assessment. A model to estimate value-at-risk via GARCHSK specification is proposed, in which the seasonalities, heteroscedasticities, skewnesses, kurtosises and relationship to system loads are jointly addressed. The impacts of probability distribution assumption for innovations on value-at-risk estimate validation are analyzed for three distributions: normal, student-t and Gram-Charlier series expansion of the normal density function. The numerical example shows that the proposed model performs better in predicting one-period-ahead VaR.