Modeling electricity loads in California: ARMA models with hyperbolic noise
نویسندگان
چکیده
In this paper we address the issue of modeling electricity loads. After analyzing properties of the deseasonalized loads from the California power market we fit an ARMA(1,6) model to the data. The obtained residuals seem to be independent but with tails heavier than Gaussian. It turns out that the hyperbolic distribution provides an excellent fit.
منابع مشابه
Evaluation of Time Series Patterns for Wind Speed Volatilities in Anzali Meteorological Station
Abstract. One of the major problems in using wind energy is that wind-generated electricity is more unstable than electricity generated by other sources, and therefore integrating wind energy use with traditional power generation systems can be a challenge. This problem can be effectively reduced by having accurate information about the mean and wind speed volatilities. Therefore, in this paper...
متن کاملAutoregressive moving average models of crown profiles for two California hardwood species
Time-series Autoregressive Moving Average (ARMA) models were employed to model tree crown profiles for two California hardwood species (blue oak and interior live oak). There are three major components of these models: a polynomial trend, an ARMA model, and unaccounted for variation. The polynomial trend was used to achieve a stationary series. For these crown profiles, the use of a quadratic t...
متن کاملIdentification of an Autonomous Underwater Vehicle Dynamic Using Extended Kalman Filter with ARMA Noise Model
In the procedure of designing an underwater vehicle or robot, its maneuverability and controllability must be simulated and tested, before the product is finalized for manufacturing. Since the hydrodynamic forces and moments highly affect the dynamic and maneuverability of the system, they must be estimated with a reasonable accuracy. In this study, hydrodynamic coefficients of an autonomous un...
متن کاملAuto Regressive Moving Average (ARMA) Modeling Method for Gyro Random Noise Using a Robust Kalman Filter
To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observatio...
متن کاملNonparametric Transfer Function Models.
In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between 'input' and 'output' time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modelin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Signal Processing
دوره 82 شماره
صفحات -
تاریخ انتشار 2002