Next Article in Journal
Numerical Investigation of Harvesting Solar Energy and Anti-Icing Road Surfaces Using a Hydronic Heating Pavement and Borehole Thermal Energy Storage
Next Article in Special Issue
Impacts of Load Profiles on the Optimization of Power Management of a Green Building Employing Fuel Cells
Previous Article in Journal
Oscillation Suppression Method by Two Notch Filters for Parallel Inverters under Weak Grid Conditions
Previous Article in Special Issue
Deep Learning Based on Multi-Decomposition for Short-Term Load Forecasting

Short-Term Forecasting of Total Energy Consumption for India-A Black Box Based Approach

Institute for Energy Studies, Anna University, Chennai 600025, India
Department of Education, Gandhigram Rural Institute, Dindigul 624302, India
Author to whom correspondence should be addressed.
Energies 2018, 11(12), 3442;
Received: 31 October 2018 / Revised: 29 November 2018 / Accepted: 29 November 2018 / Published: 9 December 2018
(This article belongs to the Special Issue Short-Term Load Forecasting by Artificial Intelligent Technologies)
Continual energy availability is one of the prime inputs requisite for the persistent growth of any country. This becomes even more important for a country like India, which is one of the rapidly developing economies. Therefore electrical energy’s short-term demand forecasting is an essential step in the process of energy planning. The intent of this article is to predict the Total Electricity Consumption (TEC) in industry, agriculture, domestic, commercial, traction railways and other sectors of India for 2030. The methodology includes the familiar black-box approaches for forecasting namely multiple linear regression (MLR), simple regression model (SRM) along with correlation, exponential smoothing, Holt’s, Brown’s and expert model with the input variables population, GDP and GDP per capita using the software used are IBM SPSS Statistics 20 and Microsoft Excel 1997–2003 Worksheet. The input factors namely GDP, population and GDP per capita were taken into consideration. Analyses were also carried out to find the important variables influencing the energy consumption pattern. Several models such as Brown’s model, Holt’s model, Expert model and damped trend model were analysed. The TEC for the years 2019, 2024 and 2030 were forecasted to be 1,162,453 MW, 1,442,410 MW and 1,778,358 MW respectively. When compared with Population, GDP per capita, it is concluded that GDP foresees TEC better. The forecasting of total electricity consumption for the year 2030–2031 for India is found to be 1834349 MW. Therefore energy planning of a country relies heavily upon precise proper demand forecasting. Precise forecasting is one of the major challenges to manage in the energy sector of any nation. Moreover forecasts are important for the effective formulation of energy laws and policies in order to conserve the natural resources, protect the ecosystem, promote the nation’s economy and protect the health and safety of the society. View Full-Text
Keywords: India; TEC; short-term; forecasting; black box India; TEC; short-term; forecasting; black box
Show Figures

Figure 1

MDPI and ACS Style

Rahman, H.; Selvarasan, I.; Begum A, J. Short-Term Forecasting of Total Energy Consumption for India-A Black Box Based Approach. Energies 2018, 11, 3442.

AMA Style

Rahman H, Selvarasan I, Begum A J. Short-Term Forecasting of Total Energy Consumption for India-A Black Box Based Approach. Energies. 2018; 11(12):3442.

Chicago/Turabian Style

Rahman, Habeebur, Iniyan Selvarasan, and Jahitha Begum A. 2018. "Short-Term Forecasting of Total Energy Consumption for India-A Black Box Based Approach" Energies 11, no. 12: 3442.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop