Penghui Liu^1,2,*, Yaning Zhang¹, Yuxing Dai², Yanzhou Sun^1,3

Energy Engineering, Vol.121, No.7, pp. 1883-1901, 2024, DOI:10.32604/ee.2024.049318

Abstract Arc grounding faults occur frequently in the power grid with small resistance grounding neutral points. The existing arc fault identification technology only uses the fault line signal characteristics to set the identification index, which leads to detection failure when the arc zero-off characteristic is short. To solve this problem, this paper presents an arc fault identification method by utilizing integrated signal characteristics of both the fault line and sound lines. Firstly, the waveform characteristics of the fault line and sound lines under an arc grounding fault are studied. After that, the convex hull, gradient product,… More >

Xin Shen¹, Jiahao Li¹, Yujun Yin¹, Jianlin Tang^2,3,*, Weibin Lin^2,3, Mi Zhou^2,3

Energy Engineering, Vol.121, No.7, pp. 1945-1961, 2024, DOI:10.32604/ee.2024.048388

Abstract Advanced carbon emission factors of a power grid can provide users with effective carbon reduction advice, which is of immense importance in mobilizing the entire society to reduce carbon emissions. The method of calculating node carbon emission factors based on the carbon emissions flow theory requires real-time parameters of a power grid. Therefore, it cannot provide carbon factor information beforehand. To address this issue, a prediction model based on the graph attention network is proposed. The model uses a graph structure that is suitable for the topology of the power grid and designs a supervised More >

Fuju Zhou^*, Li Li, Tengfei Jia, Yongchang Yin, Aixiang Shi, Shengrong Xu

Energy Engineering, Vol.121, No.6, pp. 1697-1711, 2024, DOI:10.32604/ee.2024.047680

Abstract When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changing the states of tie-switches and load demands. Computation speed is one of the major performance indicators in power grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault power grids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient. The tedious training process of the reinforcement learning model can be conducted offline, so the model shows satisfactory performance in real-time operation, More >

Bin Chen¹, Ziyang Li¹, Shipeng Li¹, Qingzhou Zhao¹, Xingdou Liu^2,*

Energy Engineering, Vol.121, No.5, pp. 1291-1307, 2024, DOI:10.32604/ee.2024.046374

Abstract To reduce carbon emissions, clean energy is being integrated into the power system. Wind power is connected to the grid in a distributed form, but its high variability poses a challenge to grid stability. This article combines wind turbine monitoring data with numerical weather prediction (NWP) data to create a suitable wind power prediction framework for distributed grids. First, high-precision NWP of the turbine range is achieved using weather research and forecasting models (WRF), and Kriging interpolation locates predicted meteorological data at the turbine site. Then, a preliminary predicted power series is obtained based on More >

Jialin Yu^1,*, Xiaodi Zhang², Qi Zhong¹, Jian Feng¹

Energy Engineering, Vol.121, No.3, pp. 789-806, 2024, DOI:10.32604/ee.2023.043299

Abstract With a further increase in energy flexibility for customers, short-term load forecasting is essential to provide benchmarks for economic dispatch and real-time alerts in power grids. The electrical load series exhibit periodic patterns and share high associations with metrological data. However, current studies have merely focused on point-wise models and failed to sufficiently investigate the periodic patterns of load series, which hinders the further improvement of short-term load forecasting accuracy. Therefore, this paper improved Autoformer to extract the periodic patterns of load series and learn a representative feature from deep decomposition and reconstruction. In addition, More >

Xueting Cheng¹, Ziqi Zhang^2,*, Yueshuang Bao¹, Huiping Zheng¹

Energy Engineering, Vol.120, No.11, pp. 2517-2529, 2023, DOI:10.32604/ee.2023.042633

Abstract At present, the proportion of new energy in the power grid is increasing, and the random fluctuations in power output increase the risk of cascading failures in the power grid. In this paper, we propose a method for identifying high-risk scenarios of interlocking faults in new energy power grids based on a deep embedding clustering (DEC) algorithm and apply it in a risk assessment of cascading failures in different operating scenarios for new energy power grids. First, considering the real-time operation status and system structure of new energy power grids, the scenario cascading failure risk More >

Huiru Zhao¹, Manyu Yao^1,*, Zhenqi Bai¹, Yue Zhang², Zhihua Ding³, Zhenda Hu⁴

Energy Engineering, Vol.120, No.10, pp. 2211-2231, 2023, DOI:10.32604/ee.2023.029371

Abstract As an essential infrastructure, the rural power grid is vital in promoting agricultural and rural carbon sequestration and improving rural energy electrification. It is necessary to carry out in-depth research on its comprehensive efficiency. Based on the requirements of “double carbon” and rural revitalization strategy for the rural Power Grid, this paper focuses on the modernization and low-carbon transformation of the rural Power Grid. It constructs an input-output index system for the investment efficiency of the rural Power Grid in China under the new situation. It uses the primary data of the rural Power Grid… More >

Shun Ma¹, Na Yu¹, Xiuna Wang², Shiyan Mei¹, Mingrui Zhao^2,*, Xiaoyu Han²

Energy Engineering, Vol.120, No.10, pp. 2369-2392, 2023, DOI:10.32604/ee.2023.028727

Abstract Using the improved prospect theory with the linear transformations of rewarding good and punishing bad (RGPBIT), a new investment ranking model for power grid construction projects (PGCPs) is proposed. Given the uncertainty of each index value under the market environment, fuzzy numbers are used to describe qualitative indicators and interval numbers are used to describe quantitative ones. Taking into account decision-maker’s subjective risk attitudes, a multi-criteria decision-making (MCDM) method based on improved prospect theory is proposed. First, the [−1, 1] RGPBIT operator is proposed to normalize the original data, to obtain the best and worst More >

Bo Yang¹, Yulin Li¹, Yaxing Ren², Yixuan Chen³, Xiaoshun Zhang⁴, Jingbo Wang^5,*

Energy Engineering, Vol.120, No.6, pp. 1287-1293, 2023, DOI:10.32604/ee.2023.027801

Abstract This article has no abstract. More >

Jingtang Luo¹, Shiying Yao¹, Changming Zhao^2,*, Jie Xu³, Jim Feng⁴

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4207-4216, 2023, DOI:10.32604/cmc.2023.034439

Abstract The power grid operation process is complex, and many operation process data involve national security, business secrets, and user privacy. Meanwhile, labeled datasets may exist in many different operation platforms, but they cannot be directly shared since power grid data is highly privacy-sensitive. How to use these multi-source heterogeneous data as much as possible to build a power grid knowledge map under the premise of protecting privacy security has become an urgent problem in developing smart grid. Therefore, this paper proposes federated learning named entity recognition method for the power grid field, aiming to solve… More >