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  • Open Access

    ARTICLE

    Improving Heat Transfer in Parabolic Trough Solar Collectors by Magnetic Nanofluids

    Ritesh Singh1, Abhishek Gupta1, Akshoy Ranjan Paul1, Bireswar Paul1, Suvash C. Saha2,*

    Energy Engineering, Vol.121, No.4, pp. 835-848, 2024, DOI:10.32604/ee.2024.046849

    Abstract A parabolic trough solar collector (PTSC) converts solar radiation into thermal energy. However, low thermal efficiency of PTSC poses a hindrance to the deployment of solar thermal power plants. Thermal performance of PTSC is enhanced in this study by incorporating magnetic nanoparticles into the working fluid. The circular receiver pipe, with dimensions of 66 mm diameter, 2 mm thickness, and 24 m length, is exposed to uniform temperature and velocity conditions. The working fluid, Therminol-66, is supplemented with Fe3O4 magnetic nanoparticles at concentrations ranging from 1% to 4%. The findings demonstrate that the inclusion of nanoparticles increases the convective heat… More >

  • Open Access

    ARTICLE

    Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

    Ximin Cao*, Xinglong Chen, He Huang, Yanchi Zhang, Qifan Huang

    Energy Engineering, Vol.121, No.4, pp. 1067-1089, 2024, DOI:10.32604/ee.2023.046783

    Abstract Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals. Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system, a multi-time scale optimal scheduling strategy based on model predictive control (MPC) is proposed under the consideration of load optimization. First, load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature, and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost. Second, considering inter-day to… More >

  • Open Access

    ARTICLE

    Research on the Stability Analysis Method of DC Microgrid Based on Bifurcation and Strobe Theory

    Wei Chen, Nan Qiu*, Xusheng Yang

    Energy Engineering, Vol.121, No.4, pp. 987-1005, 2024, DOI:10.32604/ee.2023.045475

    Abstract During the operation of a DC microgrid, the nonlinearity and low damping characteristics of the DC bus make it prone to oscillatory instability. In this paper, we first establish a discrete nonlinear system dynamic model of a DC microgrid, study the effects of the converter sag coefficient, input voltage, and load resistance on the microgrid stability, and reveal the oscillation mechanism of a DC microgrid caused by a single source. Then, a DC microgrid stability analysis method based on the combination of bifurcation and strobe is used to analyze how the aforementioned parameters influence the oscillation characteristics of the system.… More >

  • Open Access

    ARTICLE

    Prediction Model of Wax Deposition Rate in Waxy Crude Oil Pipelines by Elman Neural Network Based on Improved Reptile Search Algorithm

    Zhuo Chen1,*, Ningning Wang2, Wenbo Jin3, Dui Li1

    Energy Engineering, Vol.121, No.4, pp. 1007-1026, 2024, DOI:10.32604/ee.2023.045270

    Abstract A hard problem that hinders the movement of waxy crude oil is wax deposition in oil pipelines. To ensure the safe operation of crude oil pipelines, an accurate model must be developed to predict the rate of wax deposition in crude oil pipelines. Aiming at the shortcomings of the ENN prediction model, which easily falls into the local minimum value and weak generalization ability in the implementation process, an optimized ENN prediction model based on the IRSA is proposed. The validity of the new model was confirmed by the accurate prediction of two sets of experimental data on wax deposition… More > Graphic Abstract

    Prediction Model of Wax Deposition Rate in Waxy Crude Oil Pipelines by Elman Neural Network Based on Improved Reptile Search Algorithm

  • 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

    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 and search accuracy of the… More >

  • Open Access

    ARTICLE

    Resilience-Oriented Load Restoration Method and Repair Strategies for Regional Integrated Electricity-Natural Gas System

    Keqiang Wang1, Pengyang Zhao1, Changjian Wang2, Zimeng Zhang1, Yu Zhang1, Jia Lu1, Zedong Yang2,*

    Energy Engineering, Vol.121, No.4, pp. 1091-1108, 2024, DOI:10.32604/ee.2023.044016

    Abstract The rising frequency of extreme disaster events seriously threatens the safe and secure operation of the regional integrated electricity-natural gas system (RIENGS). With the growing level of coupling between electric and natural gas systems, it is critical to enhance the load restoration capability of both systems. This paper proposes a coordinated optimization strategy for resilience-enhanced RIENGS load restoration and repair scheduling and transforms it into a mixed integer second-order cone programming (MISOCP) model. The proposed model considers the distribution network reconfiguration and the coordinated repair strategy between the two systems, minimizing the total system load loss cost and repair time.… More >

  • Open Access

    ARTICLE

    Investigating Load Regulation Characteristics of a Wind-PV-Coal Storage Multi-Power Generation System

    Zhongping Liu1, Enhui Sun2,*, Jiahao Shi2, Lei Zhang2, Qi Wang1, Jiali Dong1

    Energy Engineering, Vol.121, No.4, pp. 913-932, 2024, DOI:10.32604/ee.2023.043973

    Abstract There is a growing need to explore the potential of coal-fired power plants (CFPPs) to enhance the utilization rate of wind power (wind) and photovoltaic power (PV) in the green energy field. This study developed a load regulation model for a multi-power generation system comprising wind, PV, and coal energy storage using real-world data. The power supply process was divided into eight fundamental load regulation scenarios, elucidating the influence of each scenario on load regulation. Within the framework of the multi-power generation system with the wind (50 MW) and PV (50 MW) alongside a CFPP (330 MW), a lithium-iron phosphate… More > Graphic Abstract

    Investigating Load Regulation Characteristics of a Wind-PV-Coal Storage Multi-Power Generation System

  • Open Access

    ARTICLE

    Analysis and Modeling of Time Output Characteristics for Distributed Photovoltaic and Energy Storage

    Kaicheng Liu1,3,*, Chen Liang2, Xiaoyang Dong2, Liping Liu1

    Energy Engineering, Vol.121, No.4, pp. 933-949, 2024, DOI:10.32604/ee.2023.043658

    Abstract Due to the unpredictable output characteristics of distributed photovoltaics, their integration into the grid can lead to voltage fluctuations within the regional power grid. Therefore, the development of spatial-temporal coordination and optimization control methods for distributed photovoltaics and energy storage systems is of utmost importance in various scenarios. This paper approaches the issue from the perspective of spatiotemporal forecasting of distributed photovoltaic (PV) generation and proposes a Temporal Convolutional-Long Short-Term Memory prediction model that combines Temporal Convolutional Networks (TCN) and Long Short-Term Memory (LSTM). To begin with, an analysis of the spatiotemporal distribution patterns of PV generation is conducted, and… More >

  • Open Access

    ARTICLE

    Research on Carbon Emission for Preventive Maintenance of Wind Turbine Gearbox Based on Stochastic Differential Equation

    Hongsheng Su, Lixia Dong*, Xiaoying Yu, Kai Liu

    Energy Engineering, Vol.121, No.4, pp. 973-986, 2024, DOI:10.32604/ee.2023.043497

    Abstract Time based maintenance (TBM) and condition based maintenance (CBM) are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes, however, these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues. Hence, this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue. Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state, a stochastic differential equation model (SDE) and corresponding carbon emission model are… More > Graphic Abstract

    Research on Carbon Emission for Preventive Maintenance of Wind Turbine Gearbox Based on Stochastic Differential Equation

  • Open Access

    ARTICLE

    Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

    Mousumi Basu1, Chitralekha Jena2, Baseem Khan3,4,*, Ahmed Ali4

    Energy Engineering, Vol.121, No.4, pp. 849-867, 2024, DOI:10.32604/ee.2024.043294

    Abstract In the restructured electricity market, microgrid (MG), with the incorporation of smart grid technologies, distributed energy resources (DERs), a pumped-storage-hydraulic (PSH) unit, and a demand response program (DRP), is a smarter and more reliable electricity provider. DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines. Better bidding strategies, prepared by MG operators, decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources (RES). But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate. To solve these issues, this study… More >

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