Optimal Integrated Energy Scheduling for Industrial Customers Based on a Bi-level Programming DOI Creative Commons
Qiang Li, Feng Zhao,

Weiping Song

и другие.

IEEE Access, Год журнала: 2024, Номер 12, С. 167778 - 167793

Опубликована: Янв. 1, 2024

Язык: Английский

Forecasting day-ahead electric power prices with functional data analysis DOI Creative Commons
Faheem Jan, Hasnain Iftikhar, Muhammad Junaid Tahir

и другие.

Frontiers in Energy Research, Год журнала: 2025, Номер 13

Опубликована: Март 28, 2025

Day-ahead electricity prices in today’s competitive electric power markets have complex features such as high frequency, volatility, non-linearity, non-stationarity, mean reversion, multiple periodicities, and calendar effects. These complicated make price forecasting difficult. To address this, this research examines the application of functional data analysis to day-ahead prices. Compared classical time series approaches, is more appealing since it anticipates daily profile, allowing for short-term projections. This technique uses a autoregressive ( F AR) with exogenous predictors id="m2">X ) model predict next-day In addition, standard time-series models, including (AR) id="m4">

Язык: Английский

Процитировано

0

A Two-layer Low-carbon Economic Planning Method for Park-level Integrated Energy Systems with Carbon-Energy Synergistic Hub DOI Creative Commons
Yunfei Mu, Haochen Guo,

Zhijun Wu

и другие.

Energy and AI, Год журнала: 2024, Номер 18, С. 100435 - 100435

Опубликована: Окт. 29, 2024

Язык: Английский

Процитировано

1

Optimal Integrated Energy Scheduling for Industrial Customers Based on a Bi-level Programming DOI Creative Commons
Qiang Li, Feng Zhao,

Weiping Song

и другие.

IEEE Access, Год журнала: 2024, Номер 12, С. 167778 - 167793

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0