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  • Open Access

    ARTICLE

    Optimal Configuration Method for Multi-Type Reactive Power Compensation Devices in Regional Power Grid with High Proportion of Wind Power

    Ying Wang1, Jie Dang1, Cangbi Ding2,*, Chenyi Zheng2, Yi Tang2

    Energy Engineering, Vol.121, No.11, pp. 3331-3353, 2024, DOI:10.32604/ee.2024.052066 - 21 October 2024

    Abstract As the large-scale development of wind farms (WFs) progresses, the connection of WFs to the regional power grid is evolving from the conventional receiving power grid to the sending power grid with a high proportion of wind power (WP). Due to the randomness of WP output, higher requirements are put forward for the voltage stability of each node of the regional power grid, and various reactive power compensation devices (RPCDs) need to be rationally configured to meet the stable operation requirements of the system. This paper proposes an optimal configuration method for multi-type RPCDs in More >

  • Open Access

    ARTICLE

    Stackelberg Game-Based Optimal Dispatch for PEDF Park and Power Grid Interaction under Multiple Incentive Mechanisms

    Weidong Chen1,2,*, Yun Zhao3, Xiaorui Wu1,2, Ziwen Cai3, Min Guo1,2, Yuxin Lu3

    Energy Engineering, Vol.121, No.10, pp. 3075-3093, 2024, DOI:10.32604/ee.2024.051404 - 11 September 2024

    Abstract The integration of photovoltaic, energy storage, direct current, and flexible load (PEDF) technologies in building power systems is an important means to address the energy crisis and promote the development of green buildings. The friendly interaction between the PEDF systems and the power grid can promote the utilization of renewable energy and enhance the stability of the power grid. For this purpose, this work introduces a framework of multiple incentive mechanisms for a PEDF park, a building energy system that implements PEDF technologies. The incentive mechanisms proposed in this paper include both economic and noneconomic… More >

  • Open Access

    ARTICLE

    Enhancing Autonomy Capability in Regional Power Grids: A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

    Jie Ma1, Tong Zhao2, Yuanzhao Hao3, Wenwen Qin2, Haozheng Yu1, Mingxuan Du2, Yuanhong Liu4, Liang Zhang2, Shixia Mu5, Cuiping Li2, Junhui Li2,*

    Energy Engineering, Vol.121, No.9, pp. 2449-2477, 2024, DOI:10.32604/ee.2024.051244 - 19 August 2024

    Abstract After the integration of large-scale Distributed Generation (DG) into the distribution network, the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network, exacerbating the phenomenon of wind and solar power wastage. As a novel power system model, the fundamental concept of Regional Autonomous Power Grids (RAPGs) is to achieve localized management and energy autonomy, thereby facilitating the effective consumption of DGs. Therefore, this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple… More > Graphic Abstract

    Enhancing Autonomy Capability in Regional Power Grids: A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

  • Open Access

    ARTICLE

    A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

    Wentao Li1, Jiantao Liu2, Yudun Li3, Guoxin Ming1, Kaifeng Zhang1, Kun Yuan1,*

    Energy Engineering, Vol.121, No.9, pp. 2479-2503, 2024, DOI:10.32604/ee.2024.050852 - 19 August 2024

    Abstract With the large-scale development and utilization of renewable energy, industrial flexible loads, as a kind of load-side resource with strong regulation ability, provide new opportunities for the research on renewable energy consumption problem in power systems. This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning, aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy, and achieving the safe, stable and economical operation of power grids. Firstly, according to the evaluation index of renewable energy… More >

  • Open Access

    ARTICLE

    Arc Grounding Fault Identification Using Integrated Characteristics in the Power Grid

    Penghui Liu1,2,*, Yaning Zhang1, Yuxing Dai2, Yanzhou Sun1,3

    Energy Engineering, Vol.121, No.7, pp. 1883-1901, 2024, DOI:10.32604/ee.2024.049318 - 11 June 2024

    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 >

  • Open Access

    ARTICLE

    Carbon Emission Factors Prediction of Power Grid by Using Graph Attention Network

    Xin Shen1, Jiahao Li1, Yujun Yin1, Jianlin Tang2,3,*, Weibin Lin2,3, Mi Zhou2,3

    Energy Engineering, Vol.121, No.7, pp. 1945-1961, 2024, DOI:10.32604/ee.2024.048388 - 11 June 2024

    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 >

  • Open Access

    ARTICLE

    Intelligent Power Grid Load Transferring Based on Safe Action-Correction Reinforcement Learning

    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 - 21 May 2024

    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 >

  • Open Access

    ARTICLE

    A Wind Power Prediction Framework for Distributed Power Grids

    Bin Chen1, Ziyang Li1, Shipeng Li1, Qingzhou Zhao1, Xingdou Liu2,*

    Energy Engineering, Vol.121, No.5, pp. 1291-1307, 2024, DOI:10.32604/ee.2024.046374 - 30 April 2024

    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 >

  • Open Access

    ARTICLE

    Investigating Periodic Dependencies to Improve Short-Term Load Forecasting

    Jialin Yu1,*, Xiaodi Zhang2, Qi Zhong1, Jian Feng1

    Energy Engineering, Vol.121, No.3, pp. 789-806, 2024, DOI:10.32604/ee.2023.043299 - 27 February 2024

    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 >

  • Open Access

    ARTICLE

    Identification of High-Risk Scenarios for Cascading Failures in New Energy Power Grids Based on Deep Embedding Clustering Algorithms

    Xueting Cheng1, Ziqi Zhang2,*, Yueshuang Bao1, Huiping Zheng1

    Energy Engineering, Vol.120, No.11, pp. 2517-2529, 2023, DOI:10.32604/ee.2023.042633 - 31 October 2023

    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 >

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