Muhammad Munsif^1,2, Fath U Min Ullah^1,2, Samee Ullah Khan^1,2, Noman Khan^1,2, Sung Wook Baik^1,2,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1751-1773, 2023, DOI:10.32604/csse.2023.038514

Abstract Photovoltaic (PV) systems are environmentally friendly, generate green energy, and receive support from policies and organizations. However, weather fluctuations make large-scale PV power integration and management challenging despite the economic benefits. Existing PV forecasting techniques (sequential and convolutional neural networks (CNN)) are sensitive to environmental conditions, reducing energy distribution system performance. To handle these issues, this article proposes an efficient, weather-resilient convolutional-transformer-based network (CT-NET) for accurate and efficient PV power forecasting. The network consists of three main modules. First, the acquired PV generation data are forwarded to the pre-processing module for data refinement. Next, to carry out data encoding, a… More >

Saurabh Awasthi^*, Gagan Singh, Nafees Ahamad

Energy Engineering, Vol.120, No.4, pp. 811-829, 2023, DOI:10.32604/ee.2023.026863

Abstract A distributed generation system (DG) has several benefits over a traditional centralized power system. However, the protection area in the case of the distributed generator requires special attention as it encounters stability loss, failure re-closure, fluctuations in voltage, etc. And thereby, it demands immediate attention in identifying the location & type of a fault without delay especially when occurred in a small, distributed generation system, as it would adversely affect the overall system and its operation. In the past, several methods were proposed for classification and localisation of a fault in a distributed generation system. Many of those methods were… More >

Bo Yang¹, Zhengxun Guo¹, Jingbo Wang^1,*, Chao Duan², Yaxing Ren³, Yixuan Chen⁴

Energy Engineering, Vol.119, No.5, pp. 1789-1795, 2022, DOI:10.32604/ee.2022.022217

Abstract This article has no abstract. More >

Md. Mottahir Alam^1,*, Ahteshamul Haque², Mohammed Ali Khan³, Nebras M. Sobahi¹, Ibrahim Mustafa Mehedi^1,4, Asif Irshad Khan⁵

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3999-4017, 2022, DOI:10.32604/cmc.2022.026353

Abstract The shift towards the renewable energy market for carbon-neutral power generation has encouraged different governments to come up with a plan of action. But with the endorsement of renewable energy for harsh environmental conditions like sand dust and snow, monitoring and maintenance are a few of the prime concerns. These problems were addressed widely in the literature, but most of the research has drawbacks due to long detection time, and high misclassification error. Hence to overcome these drawbacks, and to develop an accurate monitoring approach, this paper is motivated toward the understanding of primary failure concerning a grid-connected photovoltaic (PV)… More >

G. Indira Kishore¹, M. Premkumar^1,*, Ramesh Kumar Tripathi², Chandra Sekhar Nalamati²

Energy Engineering, Vol.118, No.2, pp. 199-209, 2021, DOI:10.32604/EE.2021.014079

Abstract Renewable energy with sources such as photovoltaic (PV) or fuel cells can be utilized for the generation of electrical power. But these sources generate fewer voltage values and therefore require high gain converters to match with DC bus voltage in microgrids. These high gain converters can be implemented with switched capacitors to meet the required DC bus voltage. Switched capacitors operate in a series and parallel combination during switching operation and produce high static gain, limits reverse voltage that appears across the components. A novel converter is proposed that satisfies all the features such as high voltage gain, only one… More >