Razin Ahmed, Victor Sreeram, Yateendra Mishra, Muammer Din Arif
Integration of photovoltaics into power grids is difficult as solar energy is highly dependent on climate and geography; often fluctuating erratically. This causes penetrations and voltage surges, system instability, inefficient utilities planning and financial loss. Forecast models can help; howeve...
Shafiul Hasan Rafi, Nahid‐Al Masood, Shohana Rahman Deeba, Eklas Hossain
In this study, a new technique is proposed to forecast short-term electrical load. Load forecasting is an integral part of power system planning and operation. Precise forecasting of load is essential for unit commitment, capacity planning, network augmentation and demand side management. Load forec...
Abdullah Al Mamun, Md. Sohel, Naeem Mohammad, Md Samiul Haque Sunny et al.
Load forecasting is a pivotal part of the power utility companies. To provide load-shedding free and uninterrupted power to the consumer, decision-makers in the utility sector must forecast the future demand for electricity with a minimum error percentage. Load prediction with less percentage of err...
Md. Arif Istiake Sunny, Mirza Mohd Shahriar Maswood, Abdullah G. Alharbi
In the financial world, the forecasting of stock price gains significant attraction. For the growth of shareholders in a company's stock, stock price prediction has a great consideration to increase the interest of speculators for investing money to the company. The successful prediction of a stock'...
Md. Mijanur Rahman, Mohammad Shakeri, Sieh Kiong Tiong, Fatema Khatun et al.
This paper presents a comprehensive review of machine learning (ML) based approaches, especially artificial neural networks (ANNs) in time series data prediction problems. According to literature, around 80% of the world’s total energy demand is supplied either through fuel-based sources such as oil...
Md. Alamgir Hossain, Ripon K. Chakrabortty, Sondoss Elsawah, Michael J. Ryan
Accurate forecasting of wind power generation plays a key role in improving the operation and management of a power system network and thereby its reliability and security. However, predicting wind power is complex due to the existence of high non-linearity in wind speed that eventually relies on pr...
Ahmad Hasan Nury, Khairul Hasan, Md. Jahir Bin Alam
Time-series analyses of temperature data are important for investigating temperature variation and predicting temperature change. Here, Mann–Kendall (M–K) analyses of temperature time-series data in northeastern Bangladesh indicated increasing trends (Sen’s slope of maximum and minimum yearly temper...
Faiaz Ahsan, Nazia Hasan Dana, Subrata K. Sarker, Li Li et al.
Abstract Meteorological changes urge engineering communities to look for sustainable and clean energy technologies to keep the environment safe by reducing CO 2 emissions. The structure of these technologies relies on the deep integration of advanced data-driven techniques which can ensure efficient...
Jayanthi Devaraj, Rajvikram Madurai Elavarasan, GM Shafiullah, Taskin Jamal et al.
With the growth of forecasting models, energy forecasting is used for better planning, operation, and management in the electric grid. It is important to improve the accuracy of forecasting for a faster decision-making process. Big data can handle large scale of datasets and extract the patterns fed...
Mohammad Zoynul Abedin, Mahmudul Hasan Moon, M. Kabir Hassan, Petr Hájek
This study proposes an ensemble deep learning approach that integrates Bagging Ridge (BR) regression with Bi-directional Long Short-Term Memory (Bi-LSTM) neural networks used as base regressors to become a Bi-LSTM BR approach. Bi-LSTM BR was used to predict the exchange rates of 21 currencies agains...
Mst. Noorunnahar, Arman Hossain Chowdhury, Farhana Arefeen Mila
In this study, we attempt to anticipate annual rice production in Bangladesh (1961-2020) using both the Autoregressive Integrated Moving Average (ARIMA) and the eXtreme Gradient Boosting (XGBoost) methods and compare their respective performances. On the basis of the lowest Corrected Akaike Informat...
Abrar Faisal, Afikur Rahman, Mohammad Tanvir Mahmud Habib, Abdul Hasib Siddique et al.
Solar radiation is the energy or radiation we get from the sun, time-varying data. Solar radiation plays a vital role in various sectors. With better prediction, performances in these sectors can be enhanced. In this work, we proposed a system to forecast solar radiation using Neural Networks. Meteo...
Guoqiang Chen, Tianyu Long, Jiangong Xiong, Yun Bai
Abdallah Abdellatif, Hamza Mubarak, Shameem Ahmad, Tofael Ahmed et al.
Nowadays, photovoltaics (PV) has gained popularity among other renewable energy sources because of its excellent features. However, the instability of the system’s output has become a critical problem due to the high PV penetration into the existing distribution system. Hence, it is essential to hav...
A.K. Azad, M.G. Rasul, M. M. Alam, S. M. Ameer Uddin et al.
In this study, the wind speed data has been statistically analyzed using Weibull distribution to find out wind energy conversion characteristics of Hatiya Island in Bangladesh. Two important parameters like Weibull shape factor “k” and Weibull scale factor “c” have been calculated by four methods. T...