Research Article
Comparisons of the Added Value of Dynamical Downscaling of ECMWF EPS and NCEP GEFS for Wind Forecast in the Complex Terrain of Sichuan and Yunnan in China
Zifen Han,
Bolin Zhang,
Jianmei Zhang,
Jie Long,
Xiaohui Zhong
Issue:
Volume 8, Issue 5, October 2023
Pages:
104-112
Received:
15 September 2023
Accepted:
24 October 2023
Published:
28 October 2023
Abstract: Numerical weather prediction (NWP) models are commonly used for wind power forecasts, but NWP forecasts are uncertain due to uncertainties in the initial conditions, approximate model physics, and the chaotic nature of the atmosphere. Ensemble prediction systems (EPS), which simulate multiple possible futures, thus provide valuable information about forecast uncertainties. However, the spatial resolution of global ensemble forecasts from the European Centre for Medium-range Weather Forecast (ECMWF) and the National Centers for Environmental Prediction (NCEP) is relatively coarse and insufficient for many wind power farms built in complex terrain. This work proposes using the Weather and Research Forecasting model (WRF) to downscale ECMWF EPS and NCEP global ensemble forecast system (GEFS) to determine and compare the added values of downscaling different global EPS forecasts for wind forecasts in the complex terrain of Sichuan and Yunnan in China. A total of 366 days of day-ahead forecasts (28 to 51 hours) for wind speed at 80 meters are evaluated. The results demonstrate that the ensemble average of the higher resolution WRF downscaled forecast is considerably better than that of the global EPS forecast, and downscaled forecast of ECMWF EPS achieves the best performance. Also, a selective ensemble average (SEA) method is proposed and applied for the ultra-short (10 to 13 hours) forecast. Verification results demonstrate that the SEA method outperforms the ensemble mean.
Abstract: Numerical weather prediction (NWP) models are commonly used for wind power forecasts, but NWP forecasts are uncertain due to uncertainties in the initial conditions, approximate model physics, and the chaotic nature of the atmosphere. Ensemble prediction systems (EPS), which simulate multiple possible futures, thus provide valuable information abou...
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Research Article
A Review of Power Prediction Methods Under the COVID-19 Pandemic
Youliang Dong,
Changshun Yan
Issue:
Volume 8, Issue 5, October 2023
Pages:
113-117
Received:
4 October 2023
Accepted:
6 November 2023
Published:
9 November 2023
Abstract: Load forecasting, Prediction Models, COVID-19, Time Series Analysis, Combined models, Electricity is the foundation of national construction, and accurate electricity load forecasting is an important guarantee for the normal operation of power systems. During the COVID-19 pandemic, the electricity demand of various countries has fluctuated significantly due to various factors, which has had a certain impact on national development. To assist the government in planning power supply rationally and formulating plans in advance based on electricity demand, it is necessary to accurately predict electricity demand. Therefore, this paper systematically analyzes and introduces the development history of electricity load forecasting technology, which helps to better cope with the impact of the COVID-19 pandemic on the power industry. This paper introduces the research status of electricity load forecasting technology, including time series methods, machine learning methods, deep learning methods, hybrid model methods, and analyzes the advantages and disadvantages of each forecasting method. Establishing a model through these methods can accurately and effectively predict electricity demand, providing technical guarantees and theoretical support for the stable development and long-term construction of the country. Finally, this paper summarizes the current problems in electricity forecasting and the trends of future improvement and development. Through reviewing and summarizing the article, it can provide researchers with ideas and technical routes to solve problems, and also help non-professionals interested in this issue to have a general understanding.
Abstract: Load forecasting, Prediction Models, COVID-19, Time Series Analysis, Combined models, Electricity is the foundation of national construction, and accurate electricity load forecasting is an important guarantee for the normal operation of power systems. During the COVID-19 pandemic, the electricity demand of various countries has fluctuated signific...
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Research Article
Macroeconomic Factors Determining CO2 Emission in Bangladesh: Through the Lens of VECM Approach
Md. Tanvir Ahmed*,
Refat Ferdous
Issue:
Volume 8, Issue 5, October 2023
Pages:
118-128
Received:
28 September 2023
Accepted:
31 October 2023
Published:
11 November 2023
Abstract: Never before has this planet encountered this kind of environmental crisis. Overall macroeconomic activities are inarguably linked to the worsening environmental quality. As a result, designing economic policies inevitably requires the knowledge of the factors that hurt the environment and lead to serious climatic conditions. Using secondary data from the year 1990 to 2021 and employing vector error correction model (VECM), this study attempts to determine the factors impacting carbon dioxide (CO2) emission in Bangladesh. The findings of this study show that GDP, total trade volume (TT) and energy consumption (EN) raise the level of CO2 emission in the short run and the effect of population (PO) is not statistically significant. The long-run model also substantiates that GDP, TT, EN and PO have positive impact on the CO2 emission. Though the use of renewable energy (RE) reduces emissions both in the short and long run, this effect is not statistically significant. These findings can help recognize the unintended losses incurred and formulate effectual policies for withstanding the pernicious effects of CO2 emission from a developing country perspective. Thus, this study significantly contributes to the appropriate policymaking activities that help developing nations around the world to sustainably achieve economic growth without hurting the environment.
Abstract: Never before has this planet encountered this kind of environmental crisis. Overall macroeconomic activities are inarguably linked to the worsening environmental quality. As a result, designing economic policies inevitably requires the knowledge of the factors that hurt the environment and lead to serious climatic conditions. Using secondary data f...
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