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 >

Yu Xiao^1,2, Kai Li^1,2, Hongqiao Huang^1,2, Haibo Tan^1,2, Hua Li^3,*

Energy Engineering, Vol.120, No.2, pp. 511-527, 2023, DOI:10.32604/ee.2023.022750

Abstract The analysis of the loss of distributed photovoltaic power generation systems involves the interests of energy users, energy-saving service companies, and power grid companies, so it has always been the focus of the industry and society in some manner or another. However, the related analysis for an actual case that considers different cooperative corporations’ benefits is lacking in the presently available literature. This paper takes the distributed rooftop photovoltaic power generation project in an industrial park as the object, studies the analysis and calculation methods of line loss and transformer loss, analyzes the change of transformer loss under different temperatures… More >

Saeed Akbari¹, Seyed Saeed Fazel^1,*, Hamed Hashemi-Dezaki^2,3

Energy Engineering, Vol.120, No.1, pp. 69-86, 2023, DOI:10.32604/ee.2022.024121

Abstract The networking of microgrids has received significant attention in the form of a smart grid. In this paper, a set of smart railway stations, which is assumed as microgrids, is connected together. It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid. Also, the operational costs of stations under various conditions decrease by applying the proposed method. The smart railway stations are studied in the presence of photovoltaic (PV) units, energy storage systems (ESSs), and regenerative braking strategies. Studying regenerative braking is one of the essential contributions. Moreover, the… More > Graphic Abstract