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  • Open Access

    ARTICLE

    Research on Spatial Statistical Downscaling Method of Meteorological Data Applied to Photovoltaic Prediction

    Yan Jin1,*, Dingmei Wang2, Ruiping Zhang1, Haiying Dong1

    Energy Engineering, Vol.119, No.5, pp. 1923-1940, 2022, DOI:10.32604/ee.2022.018750 - 21 July 2022

    Abstract Aiming at the low spatial resolution of meteorological data output from a numerical model in photovoltaic power prediction, a geographically weighted statistical downscaling method considers the influence factors such as normalized vegetation index (NDVI), digital elevation model (DEM), slope direction, longitude and latitude is proposed. This method is based on the correlation between meteorological data and NDVI, DEM, slope direction, latitude and longitude, and introduces DEM and local Moran index to improve the regression model, and obtains 100 * 100 m high-resolution meteorological spatial distribution data. Finally, combining the measured data of the study area and More >

  • Open Access

    ARTICLE

    A Design of 220 kV Line Protection Action Deduction System Based on Numerical Simulation

    Tiecheng Li1, Qingquan Liu1, Hui Fan2, Xianzhi Wang1, Daming Zhou3,*, Junan Guo3, Lee Li3, Kun Zhou3, Yujie Hu3

    Energy Engineering, Vol.119, No.5, pp. 2105-2134, 2022, DOI:10.32604/ee.2022.017718 - 21 July 2022

    Abstract Accurate conditions monitoring and early wrong action warnings of relay protection in the Smart Substation is the basic guarantee to realize the normal operation of primary and secondary system of the power grid. At present, the traditional operation and maintenance monitoring methods of relay protections have poor timeliness, while some automatic monitoring methods have insufficient early warning performance, and lack the online action deduction function independent of the actual device. In this paper, a design method of integrated action deduction system including protection logic reasoning and software and hardware operation condition is proposed. The system More >

  • Open Access

    ARTICLE

    Optimal Intelligent Reconfiguration of Distribution Network in the Presence of Distributed Generation and Storage System

    Gang Lei1,*, Chunxiang Xu2

    Energy Engineering, Vol.119, No.5, pp. 2005-2029, 2022, DOI:10.32604/ee.2022.021154 - 21 July 2022

    Abstract In the present paper, the distribution feeder reconfiguration in the presence of distributed generation resources (DGR) and energy storage systems (ESS) is solved in the dynamic form. Since studies on the reconfiguration problem have ignored the grid security and reliability, the non-distributed energy index along with the energy loss and voltage stability indices has been assumed as the objective functions of the given problem. To achieve the mentioned benefits, there are several practical plans in the distribution network. One of these applications is the network rearrangement plan, which is the simplest and least expensive way… More >

  • Open Access

    ARTICLE

    Effects of Hydrogen Storage System and Renewable Energy Sources for Optimal Bidding Strategy in Electricity Market

    Can Li*, Xiaode Zuo

    Energy Engineering, Vol.119, No.5, pp. 1879-1903, 2022, DOI:10.32604/ee.2022.020472 - 21 July 2022

    Abstract This work suggested a novel model for obtaining optimum bidding/offering strategy to improve the benefits in case of big users. Aiming this regard, several electrical energy resources including: micro turbines, green power sources (wind turbine and photovoltaic system), power storage unit such as Hydrogen storage system with fuel cell, as well as mutual treaties are taken into account in offered model. Considering various models for uncertain parameters based on their natures such as power demand, electricity market tariffs, solar irradiation, temperature and wind speed is one of the contributions of the proposed model. Uncertainty of… More >

  • Open Access

    ARTICLE

    Deep Learning Network for Energy Storage Scheduling in Power Market Environment Short-Term Load Forecasting Model

    Yunlei Zhang1, Ruifeng Cao1, Danhuang Dong2, Sha Peng3,*, Ruoyun Du3, Xiaomin Xu3

    Energy Engineering, Vol.119, No.5, pp. 1829-1841, 2022, DOI:10.32604/ee.2022.020118 - 21 July 2022

    Abstract In the electricity market, fluctuations in real-time prices are unstable, and changes in short-term load are determined by many factors. By studying the timing of charging and discharging, as well as the economic benefits of energy storage in the process of participating in the power market, this paper takes energy storage scheduling as merely one factor affecting short-term power load, which affects short-term load time series along with time-of-use price, holidays, and temperature. A deep learning network is used to predict the short-term load, a convolutional neural network (CNN) is used to extract the features, More >

  • Open Access

    ARTICLE

    Production Dynamic Prediction Method of Waterflooding Reservoir Based on Deep Convolution Generative Adversarial Network (DC-GAN)

    Liyuan Xin1,2,3, Xiang Rao1,2,3,*, Xiaoyin Peng1,2,3, Yunfeng Xu1,2,3, Jiating Chen1,2,3

    Energy Engineering, Vol.119, No.5, pp. 1905-1922, 2022, DOI:10.32604/ee.2022.019556 - 21 July 2022

    Abstract The rapid production dynamic prediction of water-flooding reservoirs based on well location deployment has been the basis of production optimization of water-flooding reservoirs. Considering that the construction of geological models with traditional numerical simulation software is complicated, the computational efficiency of the simulation calculation is often low, and the numerical simulation tools need to be repeated iteratively in the process of model optimization, machine learning methods have been used for fast reservoir simulation. However, traditional artificial neural network (ANN) has large degrees of freedom, slow convergence speed, and complex network model. This paper aims to… More >

  • Open Access

    REVIEW

    Deep Learning-Based 3D Instance and Semantic Segmentation: A Review

    Siddiqui Muhammad Yasir1, Hyunsik Ahn2,*

    Journal on Artificial Intelligence, Vol.4, No.2, pp. 99-114, 2022, DOI:10.32604/jai.2022.031235 - 18 July 2022

    Abstract The process of segmenting point cloud data into several homogeneous areas with points in the same region having the same attributes is known as 3D segmentation. Segmentation is challenging with point cloud data due to substantial redundancy, fluctuating sample density and lack of apparent organization. The research area has a wide range of robotics applications, including intelligent vehicles, autonomous mapping and navigation. A number of researchers have introduced various methodologies and algorithms. Deep learning has been successfully used to a spectrum of 2D vision domains as a prevailing A.I. methods. However, due to the specific… More >

  • Open Access

    ARTICLE

    Research on the Dissemination and Influencing Factors of Big Data and Artificial Intelligence Related Courses in Colleges and Universities-Taking MOOC as an Example

    Zhu Junyan1, Min Yuguo2, Li Yudi3, Chen Xiaoyu4,*, Zhou Yu5

    Journal on Artificial Intelligence, Vol.4, No.2, pp. 115-132, 2022, DOI:10.32604/jai.2022.030353 - 18 July 2022

    Abstract The rapid development of information technologies such as artificial intelligence, Internet and big data has promoted the deep integration of technology and education, especially the rise of large-scale online courses, which provides a great opportunity for curriculum teaching reform in colleges and universities. At the same time, artificial intelligence, as a cutting-edge technology, has good development prospects and has become a popular professional course in colleges and universities, artificial intelligence technology has become the focus of subject education in many universities. The combination of online education and AI courses will also greatly enhance the enthusiasm… More >

  • Open Access

    ARTICLE

    Tibetan Sorting Method Based on Hash Function

    AnJian-CaiRang1,2, Dawei Song3,4,*

    Journal on Artificial Intelligence, Vol.4, No.2, pp. 85-98, 2022, DOI:10.32604/jai.2022.029141 - 18 July 2022

    Abstract Sorting the Tibetan language quickly and accurately requires first identifying the component elements that make up Tibetan syllables and then sorting by the priority of the component. Based on the study of Tibetan text structure, grammatical rules and syllable structure, we present a structure-based Tibetan syllable recognition method that uses syllable structure instead of grammar. This method avoids complicated Tibetan grammar and recognizes the components of Tibetan syllables simply and quickly. On the basis of identifying the components of Tibetan syllables, a Tibetan syllable sorting algorithm that conforms to the language sorting rules is proposed.… More >

  • Open Access

    ARTICLE

    Research on Higher Education Collaborative Management Platform Based on Relationship Graph

    Wu Aiyan*

    Journal on Artificial Intelligence, Vol.4, No.2, pp. 77-84, 2022, DOI:10.32604/jai.2022.028511 - 18 July 2022

    Abstract According to the current problems of higher education management informatization, this paper puts forward a development scheme of collaborative platform on education management. The main technology includes three parts. First, integrate the distributed database and use two-tier linked list to realize dynamic data access. Second, the relation graph is used to display the data of each student, so as to realize the visual sharing of data. Third, realize the collaborative information security mechanism from three aspects to ensure the legal sharing of data. Finally, the platform development is completed with Java. It can help to More >

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