Fengyong Li^1,*, Weicheng Shen¹, Zhongqin Bi¹, Xiangjing Su²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2095-2115, 2024, DOI:10.32604/cmes.2023.044431

Abstract False data injection attack (FDIA) is an attack that affects the stability of grid cyber-physical system (GCPS) by evading the detecting mechanism of bad data. Existing FDIA detection methods usually employ complex neural network models to detect FDIA attacks. However, they overlook the fact that FDIA attack samples at public-private network edges are extremely sparse, making it difficult for neural network models to obtain sufficient samples to construct a robust detection model. To address this problem, this paper designs an efficient sample generative adversarial model of FDIA attack in public-private network edge, which can effectively bypass the detection model to… More >

Yan Shi¹, Wenjie Li¹, Gongbo Fan^2,*, Luxi Zhang¹, Fengjiu Yang¹

Energy Engineering, Vol.121, No.2, pp. 461-482, 2024, DOI:10.32604/ee.2023.043835

Abstract Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation, this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side. A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation, with the overarching goal of optimizing the system for low-carbon operation. To begin with, an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side… More >

Fan Xiao¹, Xiong Ping¹, Yeyang Li^2,*, Yusen Xu², Yiqun Kang¹, Dan Liu¹, Nianming Zhang¹

Energy Engineering, Vol.121, No.2, pp. 359-376, 2024, DOI:10.32604/ee.2023.040887

Abstract The fluctuation of wind power affects the operating safety and power consumption of the electric power grid and restricts the grid connection of wind power on a large scale. Therefore, wind power forecasting plays a key role in improving the safety and economic benefits of the power grid. This paper proposes a wind power predicting method based on a convolutional graph attention deep neural network with multi-wind farm data. Based on the graph attention network and attention mechanism, the method extracts spatial-temporal characteristics from the data of multiple wind farms. Then, combined with a deep neural network, a convolutional graph… More >

Baogang Chen¹, Fenglin Miao^2,*, Jing Yang¹, Chen Qi², Wenyan Ji¹

Energy Engineering, Vol.121, No.2, pp. 541-555, 2024, DOI:10.32604/ee.2023.028327

Abstract Energy storage systems (ESS) and permanent magnet synchronous generators (PMSG) are speculated to be able to exhibit frequency regulation capabilities by adding differential and proportional control loops with different control objectives. The available PMSG kinetic energy and charging/discharging capacities of the ESS were restricted. To improve the inertia response and frequency control capability, we propose a short-term frequency support strategy for the ESS and PMSG. To this end, the weights were embedded in the control loops to adjust the participation of the differential and proportional controls based on the system frequency excursion. The effectiveness of the proposed control strategy was… More >

Emmanuel Lule^1,2,*, Chomora Mikeka³, Alexander Ngenzi⁴, Didacienne Mukanyiligira⁵

Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 57-81, 2023, DOI:10.32604/iasc.2023.037988

Abstract Local markets in East Africa have been destroyed by raging fires, leading to the loss of life and property in the nearby communities. Electrical circuits, arson, and neglected charcoal stoves are the major causes of these fires. Previous methods, i.e., satellites, are expensive to maintain and cause unnecessary delays. Also, unit-smoke detectors are highly prone to false alerts. In this paper, an Interval Type-2 TSK fuzzy model for an intelligent lightweight fire intensity detection algorithm with decision-making in low-power devices is proposed using a sparse inference rules approach. A free open–source MATLAB/Simulink fuzzy toolbox integrated into MATLAB 2018a is used… More >

Yuzheng Yang^*, Zhe Tu, Ying Liu, Huachun Zhou

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3163-3184, 2023, DOI:10.32604/cmc.2023.043974

Abstract Currently, data security and privacy protection are becoming more and more important. Access control is a method of authorization for users through predefined policies. Token-based access control (TBAC) enhances the manageability of authorization through the token. However, traditional access control policies lack the ability to dynamically adjust based on user access behavior. Incorporating user reputation evaluation into access control can provide valuable feedback to enhance system security and flexibility. As a result, this paper proposes a blockchain-empowered TBAC system and introduces a user reputation evaluation module to provide feedback on access control. The TBAC system divides the access control process… More >

Sahar Arooj¹, Muhammad Farhan Khan², Tariq Shahzad³, Muhammad Adnan Khan^4,5,6, Muhammad Umar Nasir⁷, Muhammad Zubair¹, Atta-ur-Rahman⁸, Khmaies Ouahada^3,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2813-2831, 2023, DOI:10.32604/cmc.2023.043013

Abstract Breast cancer (BC) is the most widespread tumor in females worldwide and is a severe public health issue. BC is the leading reason of death affecting females between the ages of 20 to 59 around the world. Early detection and therapy can help women receive effective treatment and, as a result, decrease the rate of breast cancer disease. The cancer tumor develops when cells grow improperly and attack the healthy tissue in the human body. Tumors are classified as benign or malignant, and the absence of cancer in the breast is considered normal. Deep learning, machine learning, and transfer learning… More >

Lei Hu^1,*, Yuanwen Lu¹, Si Wang², Wenbin Wang³, Yongmei Zhang⁴

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2735-2749, 2023, DOI:10.32604/cmc.2023.042974

Abstract The YOLOx-s network does not sufficiently meet the accuracy demand of equipment detection in the autonomous inspection of distribution lines by Unmanned Aerial Vehicle (UAV) due to the complex background of distribution lines, variable morphology of equipment, and large differences in equipment sizes. Therefore, aiming at the difficult detection of power equipment in UAV inspection images, we propose a multi-equipment detection method for inspection of distribution lines based on the YOLOx-s. Based on the YOLOx-s network, we make the following improvements: 1) The Receptive Field Block (RFB) module is added after the shallow feature layer of the backbone network to… More >

Manjur Kolhar^*, Sultan Mesfer Aldossary

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2857-2879, 2023, DOI:10.32604/cmc.2023.042726

Abstract In many commercial and public sectors, the Internet of Things (IoT) is deeply embedded. Cyber security threats aimed at compromising the security, reliability, or accessibility of data are a serious concern for the IoT. Due to the collection of data from several IoT devices, the IoT presents unique challenges for detecting anomalous behavior. It is the responsibility of an Intrusion Detection System (IDS) to ensure the security of a network by reporting any suspicious activity. By identifying failed and successful attacks, IDS provides a more comprehensive security capability. A reliable and efficient anomaly detection system is essential for IoT-driven decision-making.… More >

Wei Chen, Ming Li^*, Tingting Pei, Cunyu Sun, Huan Lei

Energy Engineering, Vol.121, No.1, pp. 125-144, 2024, DOI:10.32604/ee.2023.042812

Abstract At present, the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance, breakdown maintenance, and condition-based maintenance, which is very likely to lead to over- or under-repair of equipment. Therefore, a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed. First, a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment, and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle. Then, based on… More >