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  • Open Access

    ARTICLE

    A Task Offloading Strategy Based on Multi-Agent Deep Reinforcement Learning for Offshore Wind Farm Scenarios

    Zeshuang Song1, Xiao Wang1,*, Qing Wu1, Yanting Tao1, Linghua Xu1, Yaohua Yin2, Jianguo Yan3

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 985-1008, 2024, DOI:10.32604/cmc.2024.055614 - 15 October 2024

    Abstract This research is the first application of Unmanned Aerial Vehicles (UAVs) equipped with Multi-access Edge Computing (MEC) servers to offshore wind farms, providing a new task offloading solution to address the challenge of scarce edge servers in offshore wind farms. The proposed strategy is to offload the computational tasks in this scenario to other MEC servers and compute them proportionally, which effectively reduces the computational pressure on local MEC servers when wind turbine data are abnormal. Finally, the task offloading problem is modeled as a multi-intelligent deep reinforcement learning problem, and a task offloading model… More >

  • Open Access

    ARTICLE

    Ladder Time Stepwise Inertia Coordinated Control Method of Multiple Wind Farms to Suppress System Frequency Secondary Drop

    He Li1, Xianchao Liu2,*, Jidong Li1, Yuchen Qiu2

    Energy Engineering, Vol.121, No.8, pp. 2293-2311, 2024, DOI:10.32604/ee.2024.048752 - 19 July 2024

    Abstract When employing stepwise inertial control (SIC), wind power generation can offer significant frequency support to the power system, concurrently mitigating energy shortages and suppressing secondary frequency drop. Nonetheless, further investigation is imperative for implementing stepped inertia control due to variations in frequency regulation capabilities and operational safety among diverse wind farm groups. Consequently, this paper advocates a multi-wind farm ladder timing SIC method designed to alleviate secondary drops in system frequency. Initially, the paper introduces the fundamental principles of stepped inertia control for a doubly-fed induction generator (DFIG) and deduces the relationship between support energy,… More >

  • Open Access

    ARTICLE

    Transient Stability Preventive Control of Wind Farm Connected Power System Considering the Uncertainty

    Yuping Bian*, Xiu Wan, Xiaoyu Zhou

    Energy Engineering, Vol.121, No.6, pp. 1637-1656, 2024, DOI:10.32604/ee.2024.047678 - 21 May 2024

    Abstract To address uncertainty as well as transient stability constraints simultaneously in the preventive control of wind farm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilistic multi-objective particle swarm optimization based on the point estimate method is employed to cope with the stochastic factors. The transient security region of the system is accurately ensured by the interior point method in the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforced in the last stage. Furthermore, the proposed strategy is a general More >

  • Open Access

    ARTICLE

    GNN Representation Learning and Multi-Objective Variable Neighborhood Search Algorithm for Wind Farm Layout Optimization

    Yingchao Li1,*, Jianbin Wang1, Haibin Wang2

    Energy Engineering, Vol.121, No.4, pp. 1049-1065, 2024, DOI:10.32604/ee.2023.045228 - 26 March 2024

    Abstract With the increasing demand for electrical services, wind farm layout optimization has been one of the biggest challenges that we have to deal with. Despite the promising performance of the heuristic algorithm on the route network design problem, the expressive capability and search performance of the algorithm on multi-objective problems remain unexplored. In this paper, the wind farm layout optimization problem is defined. Then, a multi-objective algorithm based on Graph Neural Network (GNN) and Variable Neighborhood Search (VNS) algorithm is proposed. GNN provides the basis representations for the following search algorithm so that the expressiveness… More >

  • Open Access

    PROCEEDINGS

    Field Observation and Numerical Simulation of Extreme Met-Ocean Conditions: A Case Study of Typhoon Events in South China Sea

    Chen Gu1,*, Caiyu Wang1, Mengjiao Du2, Kan Yi2, Bihong Zhu1, Hao Wang2, Shu Dai1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.09776

    Abstract Site measurement is essential to the meteorological and oceanographic parameters of offshore wind farms. A floating lidar measurement buoy was deployed at a Qingzhou VI wind farm where is 45-80 km away from Guangdong coast. The field observation including wind and wave data start from March, 2021.The lidar wind data is compared and calibrated with the fixed wind tower data for three months, the accuracy meets the standard of stadge3 carbon trust. In this study, all these data are used to recalibrate for the met-ocean model to relies extreme conditions, such as Typhoon Kompasu(2118) and More >

  • Open Access

    ARTICLE

    Research on Equivalent Modeling Method of AC-DC Power Networks Integrating with Renewable Energy Generation

    Weigang Jin1, Lei Chen2,*, Yifei Li2, Shencong Zheng2, Yuqi Jiang2, Hongkun Chen2

    Energy Engineering, Vol.120, No.11, pp. 2469-2487, 2023, DOI:10.32604/ee.2023.043021 - 31 October 2023

    Abstract Along with the increasing integration of renewable energy generation in AC-DC power networks, investigating the dynamic behaviors of this complex system with a proper equivalent model is significant. This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator (DFIG) based wind farms to decrease the simulation scale and computational burden. For the AC-DC power networks, the equivalent modeling strategy in accordance with the physical structure simplification is stated. Regarding the DFIG-based wind farms, the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo More >

  • Open Access

    ARTICLE

    Research on Reactive Power Optimization of Offshore Wind Farms Based on Improved Particle Swarm Optimization

    Zhonghao Qian1, Hanyi Ma1, Jun Rao2, Jun Hu1, Lichengzi Yu2,*, Caoyi Feng1, Yunxu Qiu1, Kemo Ding1

    Energy Engineering, Vol.120, No.9, pp. 2013-2027, 2023, DOI:10.32604/ee.2023.028859 - 03 August 2023

    Abstract The lack of reactive power in offshore wind farms will affect the voltage stability and power transmission quality of wind farms. To improve the voltage stability and reactive power economy of wind farms, the improved particle swarm optimization is used to optimize the reactive power planning in wind farms. First, the power flow of offshore wind farms is modeled, analyzed and calculated. To improve the global search ability and local optimization ability of particle swarm optimization, the improved particle swarm optimization adopts the adaptive inertia weight and asynchronous learning factor. Taking the minimum active power… More >

  • Open Access

    ARTICLE

    Research on Asymmetric Fault Location of Wind Farm Collection System Based on Compressed Sensing

    Huanan Yu1, Gang Han1,*, Hansong Luo2, He Wang1

    Energy Engineering, Vol.120, No.9, pp. 2029-2057, 2023, DOI:10.32604/ee.2023.028365 - 03 August 2023

    Abstract Aiming at the problem that most of the cables in the power collection system of offshore wind farms are buried deep in the seabed, which makes it difficult to detect faults, this paper proposes a two-step fault location method based on compressed sensing and ranging equation. The first step is to determine the fault zone through compressed sensing, and improve the data measurement, dictionary design and algorithm reconstruction: Firstly, the phase-locked loop trigonometric function method is used to suppress the spike phenomenon when extracting the fault voltage, so that the extracted voltage value will not… More >

  • Open Access

    ARTICLE

    Fault Diagnosis of Wind Turbine Generator with Stacked Noise Reduction Autoencoder Based on Group Normalization

    Sihua Wang1,2, Wenhui Zhang1,2,*, Gaofei Zheng1,2, Xujie Li1,2, Yougeng Zhao1,2

    Energy Engineering, Vol.119, No.6, pp. 2431-2445, 2022, DOI:10.32604/ee.2022.020779 - 14 September 2022

    Abstract In order to improve the condition monitoring and fault diagnosis of wind turbines, a stacked noise reduction autoencoding network based on group normalization is proposed in this paper. The network is based on SCADA data of wind turbine operation, firstly, the group normalization (GN) algorithm is added to solve the problems of stack noise reduction autoencoding network training and slow convergence speed, and the RMSProp algorithm is used to update the weight and the bias of the autoenccoder, which further optimizes the problem that the loss function swings too much during the update process. Finally, More >

  • Open Access

    ARTICLE

    Wind Energy Data Analysis and Resource Mapping of Dangla, Gojjam, Ethiopia

    Belayneh Yitayew1,*, Wondwossen Bogale2

    Energy Engineering, Vol.119, No.6, pp. 2513-2532, 2022, DOI:10.32604/ee.2022.018961 - 14 September 2022

    Abstract Energy is one of the most important factors in socio-economic development. The rapid increase in energy demand and air pollution has increased the number of ways to generate energy in the power sector. Currently, wind energy capacity in Ethiopia is estimated at 10,000 MW. Of these, however, only eight percent of its capacity has been used in recent years. One of the reasons for the low use of wind energy is the lack of accurate wind atlases in the country. Therefore, the purpose of this study is to develop an accurate wind atlas and review… More >

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