Forecast on 2030 Vietnam Electricity Consumption

Nguyen, Vanthuan; Nguyen, Ka; Vo, Cuong Viet; Phan, Binh

doi:10.48084/etasr.2037

Cited by 9 publications

(3 citation statements)

References 6 publications

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“…Thus, it is important to conduct a forecast of electricity consumption as it is significant for economic development as well as policy improvement. 5,6 As a reliable and an important tool for making decisions, there are several forecasting techniques that can be used. In fact, the accuracy of forecasting can be observed to obtain significant results in the projection of electricity consumption.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, the accuracy of forecasting can be observed to obtain significant results in the projection of electricity consumption. 5 In this study, three different exponential smoothing models were utilised to forecast electricity consumption: simple, Holt, and Brown's exponential smoothing. This aim of this research was to conduct a study in order to forecast electricity consumption in Malaysia until the year 2032.…”

Section: Introductionmentioning

confidence: 99%

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Forecasting electricity consumption of Malaysia’s residential sector: Evidence from an exponential smoothing model

2022

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Background: In Malaysia, residential electricity consumption has shown a steady upward trend year by year. Due to this increase in energy consumption, it is important to forecast the value of electricity consumption until the year 2032 to accommodate the electricity demand. Methods: Three exponential smoothing models were compared to identify the most appropriate model in forecasting electricity consumption. The three exponential smoothing models are Simple, Holt, and Brown exponential smoothing. To identify the most appropriate model, a mean absolute percentage (MAPE) was chosen. Results: The results show that Holt’s exponential smoothing has the best performance with the lowest MAPE score of 2.299. Conclusions: Consequently, it was found that electricity consumption would substantially increase from 2647 ktoe (kilotonne of oil equivalent) to 3873 ktoe within the period of 2019 to 2032.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Forecasting electricity consumption of Malaysia’s residential sector: Evidence from an exponential smoothing model

2022

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“…Forecasting has to have a high degree of reliability to avoid false alarms. Traditional popular forecasting techniques such as linear regression and multiple regression are used to examine the relationship between independent variable(s) and a dependent variable [3][4][5][6]. Their usefulness is considerably acceptable for simple forecasting requirements.…”

Section: Introductionmentioning

confidence: 99%

A System Dynamics Modeling and Computer-based Simulation in Forecasting Long-term Sufficiency: A Philippine Chicken Meat Sector Case Study

Espino

Bellotindos

2020

Eng. Technol. Appl. Sci. Res.

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As the human population continues to grow, the global growth of the livestock sector will continue to rise as well. In the Philippines, the demand for chicken meat is projected to triple by 2050. In this study, the increasing consumption and long-term sufficiency were evaluated with the use of the system dynamics concept. With system modeling and computer-based simulation techniques, the available data on chicken meat supply chain were processed considering that factors behave dynamically. The simulated model facilitated the forecasting of key variables which may drop sufficiency from 87% in 2015 to 60% by 2050 if no proper actions take place in the areas of production and consumption. As a whole, this study developed and demonstrated preliminary system dynamics-based and computer based-approaches in order to understand the chicken meat sector. This showed that a dynamic systems-based paradigm shift in food and agricultural systems analysis can help address operational and strategic issues regarding food security.

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Tool-based renewable energy system planning using survey data: A case study in rural Vietnam

Hart¹,

Eckhoff²,

Breitner³

2023

Environ Dev Sustain

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Renewable energies provide effective sustainable development by raising living standards, accelerating economic growth, and mitigating pollution. However, specifically in developing countries, the lack of information, data, and local expertise challenges the design process and long-term success of renewable energy systems. Following the call for inter-disciplinary, solution-oriented research, this work uses a design science research-approach to facilitate multi-energy planning. The decision support system NESSI4D is developed, which considers site-specific economic, environmental, technological, and social factors and is tuned for stakeholder needs in developing countries. Following a step-by-step process model manual, the artifact’s applicability is demonstrated in a use case for a rural community in Thua Thien-Hue, Vietnam. Missing load data are synthesized from the TVSEP with the software RAMP. The results show that the implementation of renewable energy technologies only enables affordable, low-emission electrification with governmental financial incentives. Several sensitivity tests illustrate the impact of changing assumptions and highlight the importance of detailed analyses with highly specialized tools. The demonstrating use case validates the method’s relevance for research and practice towards the goals of effective sustainable development.

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Forecast on 2030 Vietnam Electricity Consumption

Cited by 9 publications

References 6 publications

Forecasting electricity consumption of Malaysia’s residential sector: Evidence from an exponential smoothing model

Forecasting electricity consumption of Malaysia’s residential sector: Evidence from an exponential smoothing model

A System Dynamics Modeling and Computer-based Simulation in Forecasting Long-term Sufficiency: A Philippine Chicken Meat Sector Case Study

Tool-based renewable energy system planning using survey data: A case study in rural Vietnam

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