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 >

Hamidreza Shabgard^a,* , Amir Faghri^b

Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-16, 2019, DOI:10.5098/hmt.12.9

Abstract Fundamentals of exergy analysis in energy systems are reviewed and presented in a cohesive and general manner for the study of energy systems. The exergy analysis is applied to several engineering systems and processes, namely fuel cells, latent heat thermal energy storage, heat exchangers and thermal desalination systems to obtain insight on the best optimization strategies as well as the theoretical limits of performance. The various sources of irreversibility and optimal operating conditions are presented for relevant applications. It is also shown that for some systems the exergy efficiency as a function of a given parameter may have opposite trend… More >

Bing Wang^1,2,*, Lu Li¹, Xinru Jiang¹

Energy Engineering, Vol.120, No.8, pp. 1763-1773, 2023, DOI:10.32604/ee.2023.027846

Abstract Climate change and energy security issues are prominent challenges in current energy system management, which should be governed synergistically due to the feedback relationships between them. The “Energy Systems Management and Climate Change” Special Collection Issue in the journal of Energy Engineering provide insights into the field of energy systems management and climate change. From an extended perspective, this study discusses the key issues, research methods and models for energy system management and climate change research. Comprehensive and accurate prediction of energy supply and demand, the evaluation on the energy system resilience to climate change and the coupling methodology application… More > Graphic Abstract

Halyna Bielokha¹, Leonora Chupryna², Sergey Denisyuk¹, Tatiana Eutukhova³, Oleksandr Novoseltsev^2,*

Energy Engineering, Vol.120, No.6, pp. 1307-1323, 2023, DOI:10.32604/ee.2023.025863

Abstract The transition of the global economy to a low-carbon development path has led to dramatic changes in the organization and functioning of energy markets around the world, where hybrid energy systems (HESs) are one of the decisive active agents. At the same time, a number of problems facing the modern HESs are primarily due to the stochastic nature of the renewable energy they use, require further profound changes not only in the technologies they use and how they manage them, necessary to meet the needs of end consumers and interact with the unified energy system, but also to preserve the… 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 >

Helen Josephine V L¹, Ramchand Vedaiyan², V. M. Arul Xavier³, Joy Winston J⁴, A. Jegatheesan⁵, D. Lakshmi⁶, Joshua Samuel Raj^7,*

Computer Systems Science and Engineering, Vol.45, No.1, pp. 701-714, 2023, DOI:10.32604/csse.2023.030611

Abstract The Internet of Things (IoT) technologies has gained significant interest in the design of smart grids (SGs). The increasing amount of distributed generations, maturity of existing grid infrastructures, and demand network transformation have received maximum attention. An essential energy storing model mostly the electrical energy stored methods are developing as the diagnoses for its procedure was becoming further compelling. The dynamic electrical energy stored model using Electric Vehicles (EVs) is comparatively standard because of its excellent electrical property and flexibility however the chance of damage to its battery was there in event of overcharging or deep discharging and its mass… More >

Anwer Mustafa Hilal^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Mohammad Alamgeer^4,5, Mohamed K. Nour⁶, Anas Abdelrahman⁷, Abdelwahed Motwakel²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6019-6035, 2022, DOI:10.32604/cmc.2022.031425

Abstract Smart Grid (SG) technologies enable the acquisition of huge volumes of high dimension and multi-class data related to electric power grid operations through the integration of advanced metering infrastructures, control systems, and communication technologies. In SGs, user demand data is gathered and examined over the present supply criteria whereas the expenses are then informed to the clients so that they can decide about electricity consumption. Since the entire procedure is valued on the basis of time, it is essential to perform adaptive estimation of the SG’s stability. Recent advancements in Machine Learning (ML) and Deep Learning (DL) models enable the… 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 >

Qidai Lin¹, Ying Gong^2,*, Yizhi Shi¹, Changsen Feng², Youbing Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 929-944, 2022, DOI:10.32604/cmes.2022.020752

Abstract The integrated energy systems, usually including electric energy, natural gas and thermal energy, play a pivotal role in the energy Internet project, which could improve the accommodation of renewable energy through multi-energy complementary ways. Focusing on the regional integrated energy system composed of electrical microgrid and natural gas network, a fault risk warning method based on the improved RelieF-softmax method is proposed in this paper. The raw data-set was first clustered by the K-maxmin method to improve the preference of the random sampling process in the RelieF algorithm, and thereby achieved a hierarchical and non-repeated sampling. Then, the improved RelieF… More >

Ashit Kumar Dutta^1,*, Manal Al Faraj¹, Yasser Albagory², Mohammad zeid M Alzamil¹, Abdul Rahaman Wahab Sait³

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1219-1231, 2023, DOI:10.32604/csse.2023.026467

Abstract A cyber physical energy system (CPES) involves a combination of processing, network, and physical processes. The smart grid plays a vital role in the CPES model where information technology (IT) can be related to the physical system. At the same time, the machine learning (ML) models find useful for the smart grids integrated into the CPES for effective decision making. Also, the smart grids using ML and deep learning (DL) models are anticipated to lessen the requirement of placing many power plants for electricity utilization. In this aspect, this study designs optimal multi-head attention based bidirectional long short term memory… More >