hong: hong

In cugliari/enercast: Electrical energy forecast tools

Description

Fit Hong Vanilla Benchmark multiple regression model for electricity load forecasting

Usage

hong(data)

Arguments

data	Data frame with columns: year year (...2012, 2013, 2014...) month month (01, 02, ..., 12) wday day of the week (Mon Thu Wed Tue Fri Sat Sun) instant (01, 02, ..., 24) for hourly data or (01, 02, ..., 48) or half hourly data temp temperature load electricity loads

Details

The Hong Vanilla Model:

E(Load) = β_0 + β_1 Trend +β_2 Day \times Hour + β_3 Month + β_4 Month \times Temp + β_5 Month \times Temp^2 +β_6 Month \times Temp^3 + β_7 Hour \times Temp + β_8 Hour \times Temp^2 + β_9 Hour \times Temp^3

Value

An object of class lm

Author(s)

Jairo Cugliari, Andres Castrillejo, Fernando Massa, Ignacio Ramirez

References

Hong, T. and Wang, P. and Lee Willis, H. (2011) A naive multiple linear regression benchmark for short term load forecasting. In Power and Energy Society General Meeting, 2011 IEEE, 1–6.

Hong, T. and Pinson, P.and Fan, S. (2014) Global energy forecasting competition 2012. International Journal of Forecasting, 30(2):357–363

Examples

 1

cugliari/enercast documentation built on Sept. 15, 2019, 10:13 a.m.