scholarly journals Econometric Model for Forecasting Electricity Demand of Industry and Construction Sectors in Vietnam to 2030

2020 ◽  
Vol 3 (1) ◽  
pp. First
Author(s):  
Viết Cường Võ ◽  
Phuong Hoang Nguyen ◽  
Luan Le Duy Nguyen ◽  
Van-Hung Pham
Keyword(s):  
Power System ◽  
Econometric Model ◽  
Electricity Consumption ◽  
Electricity Demand ◽  
Master Plan ◽  
Base Scenario ◽  
Leading Position ◽  
Long Term Forecasting ◽  
High Scenario

An accurate forecasting for long-term electricity demand makes a major role in the planning of the power system in any country. Vietnam is one of the most economically developing countries in the world, and its electricity demand has been increased dramatically high of about 15%/y for the last three decades. Contribution of industry and construction sectors in GDP has been increasing year by year, and are currently holding the leading position of largest consumers with more than 50% sharing in national electricity consumption proportion. How to estimate the electricity consumption of these sectors correctly makes a crucial contribution to the planning of the power system. This paper applies an econometric model with Cobb Douglas production function - a top-down method to forecast electricity demand of the industry and construction sectors in Vietnam to 2030. Four variables used are the value of the sectors in GDP, income per person, the proportion of electricity consumption of the sectors in total, and electric price. Forecasted results show that the proposed method has a quite low MAPE of 7.66% for long-term forecasting. Variable of electric price does not affect the demand. This is a very critical result of the study for authority governors in Vietnam. In the base scenario of the GDP and the income per person, the forecasted electricity demands of the sectors are 112,853 GWh, 172,691 GWh, and 242,027 GWh in 2020, 2025, 2030, respectively. In high scenario one, the demands are 115,947 GWh, 181,591 GWh, and 257,272 GWh, respectively. The above values in the high scenario are less than from 9.0% to 15.8 % of that of the based on in the Revised version of master plan N0. VII.

The impact of climate change on electricity demand in Australia

2018 ◽  
Vol 29 (7) ◽  
pp. 1263-1297 ◽  
Author(s):  
Nnaemeka Vincent Emodi ◽  
Taha Chaiechi ◽  
ABM Rabiul Alam Beg
Keyword(s):  
Climate Change ◽  
Peak Load ◽  
Electricity Consumption ◽  
Electricity Demand ◽  
Policy Uncertainty ◽  
Intergovernmental Panel ◽  
Distributed Lag ◽  
Potential Benefits ◽  
The Impact

This study estimates the short- and long-term impacts of climate change on electricity demand in Australia. We used an autoregressive distributed lag (ARDL) model with monthly data from 1999 to 2014 for six Australian states and one territory. The results reveal significant variations in electricity demand. We then used long-term coefficients for climatic response to simulate future electricity demand using four scenarios based on the representative concentration pathways (RCPs) of the Intergovernmental Panel on Climate Change (IPCC). Our results show a gradual increase in electricity consumption due to warmer temperatures with the possibility of peak demand in winter; however, demand tends to decrease in the middle of the twenty-first century across the RCPs, while the summer peak load increases by the end of the century. Finally, we simulated the impact of policy uncertainty through sensitivity analysis and confirmed the potential benefits of climate change adaptation and mitigation.

scholarly journals Forecast on 2030 Vietnam Electricity Consumption

2018 ◽  
Vol 8 (3) ◽  
pp. 2869-2874 ◽  
Author(s):  
V. H. M. Nguyen ◽  
K. T. P. Nguyen ◽  
C. V. Vo ◽  
B. T. T. Phan
Keyword(s):  
Developing Countries ◽  
Econometric Model ◽  
Electricity Consumption ◽  
System Planning ◽  
Electricity System ◽  
Term Forecast ◽  
Significant Step ◽  
Per Capita ◽  
Douglas Production Function

The first but very significant step in electricity system planning is to make an accurate long-term forecast on electricity consumption. This article aims to forecast the consumption for the Vietnam electricity system (GWH) up to 2030. An econometric model with the Cobb Douglas production function is used. The five variables proposed in the forecasting function are GDP, income, population, proportion of industry and service in GDP, and number of households. The forecasting equation is tested in terms of stationary and co-integration to choose meaningful variables and to eliminate the minor ones which account for none or small impacts on the forecast. The results show that: (1) the qualified forecasting equation only includes 3 major variables: the per capita income, the population, and the number of households, (2) with the medium income scenario, the forecasting consumptions in 2020, 2025, 2030 are 230,195 GWH, 349,949 GWH, 511,268 GWH respectively. (3) The GDP and the proportion of industry and service in GDP do not make major impacts on this forecasting in Vietnam. The method and the result of this article are likely a typical example of forecasting electricity consumption in developing countries which have a transforming economy similar to that in Vietnam.

scholarly journals Bottom-up Long-term Forecasting of Brazilian Commercial Class Electricity Consumption: First Results

2015 ◽  
Vol 55 ◽  
pp. 388-394 ◽  
Author(s):  
Bruno Q. Bastos ◽  
Reinaldo C. Souza ◽  
Fernando L. Cyrino Oliveira
Keyword(s):  
Electricity Consumption ◽  
Bottom Up ◽  
First Results ◽  
Long Term Forecasting

scholarly journals Application of LEAP model on long-term electricity demand forecasting in Indonesia, period 2010-2025

2018 ◽  
Vol 49 ◽  
pp. 02007 ◽  
Author(s):  
Jaka Windarta ◽  
Bambang Purwanggono ◽  
Fuad Hidayanto
Keyword(s):  
Demand Forecasting ◽  
Electricity Consumption ◽  
Electricity Demand ◽  
Planning System ◽  
Large Country ◽  
Electricity Demand Forecasting ◽  
Electricity Planning ◽  
Business As Usual

Electricity demand forecasting is an important part in energy management especially in electricity planning. Indonesia is a large country with a pattern of electricity consumption which continues to increase, therefor need to forecasting electricity demand in order to avoid unbalance demand and supply or deficit energy. LEAP (Long-range Energy Alternative Planning System) as a tool energy model and Indonesia as a case study. Basically, electricity demand is influenced by population, economy and electricity intensity. The purpose of this study is to provide understanding and application of electricity demand forecasting by using LEAP. The base year is 2010 and end year projection is 2025. The scenarios of simulated model consist of two scenarios. They are Business as Usual (BAU) and Government policy scenario. Results of both scenarios indicate that end year electricity demand forecasting in Indonesia increased more than two fold compared to base year.

Electricity Demand Forecasting

2014 ◽  
Vol 2 (1) ◽  
pp. 1-19
Author(s):  
Fawwaz Elkarmi ◽  
Nazih Abu Shikhah
Keyword(s):  
Power System ◽  
Planning Process ◽  
Demand Forecasting ◽  
Energy Forecasting ◽  
Forecasting Models ◽  
Forecasting Methods ◽  
Long Term Forecasting ◽  
Time Frames ◽  
And Control

Forecasting is the backbone of any planning process in all fields of interest. It has a great impact on future decisions. It is also of great importance to the operation and control of business, which is reflected as profits or losses to the entity. This paper aims to provide the planner with sufficient knowledge and background of the different scopes of forecasting methods, in general, and when applied to power system field, in particular. Various load and energy forecasting models, and theoretical techniques are discussed from different perspectives, time frames, and levels. The paper presents the attributes and importance of forecasting through several cases of research conducted by the author for the Jordanian power system. In all cases the methodologies selected cover short, medium and long term forecasting periods and the results are accurate.

scholarly journals The Effects of Social Distancing on Electricity Demand Considering Temperature Dependency

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 473
Author(s):  
Mohannad Alkhraijah ◽  
Maad Alowaifeer ◽  
Mansour Alsaleh ◽  
Anas Alfaris ◽  
Daniel K. Molzahn
Keyword(s):  
Power System ◽  
Social Activity ◽  
Electricity Consumption ◽  
Electricity Demand ◽  
Electric Grid ◽  
Temperature Changes ◽  
Social Distancing ◽  
Novel Coronavirus ◽  
Time Required

To mitigate the spread of the Novel Coronavirus (COVID-19), governments around the world have imposed social distancing policies ranging from minor social activity suspensions to full curfews. These social distancing policies have altered electricity consumption behaviors in numerous countries. Many governments imposed strict social distancing policies during a temperature transition season where the impacts of temperature variations are particularly important for the operation of the electric grid. This paper studies how strict social distancing policies affect the relationship between electricity demand and ambient temperature. We first review the expected short- and long-term impacts of social distancing on the electricity demand. We then present a case study on the electricity demand of the Kingdom of Saudi Arabia during strict social distancing policies. The results of this case study suggest that strict social distancing policies result in a stronger correlation between temperature and electricity demand compared to previous years. Additionally, we observe a reduction in the time required for the electricity demand to respond to temperature changes. Power system regulators can use the results in this paper to better design energy policies. The results can also be used by power system operators to more accurately forecast electricity demands and avoid inefficient and insecure operation of the electric grid.

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