Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (115)
  • Open Access

    ARTICLE

    Impact of Short-Term Power Shortage from Low Voltage Ride through and DC Commutation Failure on Power Grid Frequency Stability

    Wenjia Zhang*, Sixuan Xu, Wanchun Qi, Zhuyi Peng, Wentao Sun

    Energy Engineering, Vol.122, No.6, pp. 2371-2387, 2025, DOI:10.32604/ee.2025.064160 - 29 May 2025

    Abstract Countries worldwide are advocating for energy transition initiatives to promote the construction of low-carbon energy systems. The low voltage ride through (LVRT) characteristics of renewable energy units and commutation failures in line commutated converter high voltage direct current (LCC-HVDC) systems at the receiving end leads to short-term power shortage (STPS), which differs from traditional frequency stability issues. STPS occurs during the generator’s power angle swing phase, before the governor responds, and is on a timescale that is not related to primary frequency regulation. This paper addresses these challenges by examining the impact of LVRT on… More >

  • Open Access

    ARTICLE

    Multi-Timescale Optimization Scheduling of Distribution Networks Based on the Uncertainty Intervals in Source-Load Forecasting

    Huanan Yu, Chunhe Ye, Shiqiang Li*, He Wang, Jing Bian, Jinling Li

    Energy Engineering, Vol.122, No.6, pp. 2417-2448, 2025, DOI:10.32604/ee.2025.061214 - 29 May 2025

    Abstract With the increasing integration of large-scale distributed energy resources into the grid, traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load. Accounting for these issues, this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks. First, the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts, based on which, the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed. Subsequently, a multi-timescale optimization framework was constructed, incorporating the generation and load forecast uncertainties. More >

  • Open Access

    ARTICLE

    Advanced Nodal Pricing Strategies for Modern Power Distribution Networks: Enhancing Market Efficiency and System Reliability

    Ganesh Wakte1,*, Mukesh Kumar2, Mohammad Aljaidi3, Ramesh Kumar4, Manish Kumar Singla4

    Energy Engineering, Vol.122, No.6, pp. 2519-2537, 2025, DOI:10.32604/ee.2025.060658 - 29 May 2025

    Abstract Nodal pricing is a critical mechanism in electricity markets, utilized to determine the cost of power transmission to various nodes within a distribution network. As power systems evolve to incorporate higher levels of renewable energy and face increasing demand fluctuations, traditional nodal pricing models often fall short to meet these new challenges. This research introduces a novel enhanced nodal pricing mechanism for distribution networks, integrating advanced optimization techniques and hybrid models to overcome these limitations. The primary objective is to develop a model that not only improves pricing accuracy but also enhances operational efficiency and… More > Graphic Abstract

    Advanced Nodal Pricing Strategies for Modern Power Distribution Networks: Enhancing Market Efficiency and System Reliability

  • Open Access

    REVIEW

    A Review of Wind Turbine Blade Morphing: Power, Vibration, and Noise

    Md. Mahbub Alam*

    FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.4, pp. 657-695, 2025, DOI:10.32604/fdmp.2025.060942 - 06 May 2025

    Abstract Wind turbines play a vital role in renewable energy production. This review examines advancements in wind turbine blade morphing technologies aimed at enhancing power coefficients, reducing vibrations, and minimizing noise generation. Efficiency, vibration, and noise levels can be optimized through morphing techniques applied to the blade’s shape, leading edge, trailing edge, and surface. Leading-edge morphing is particularly effective in improving efficiency and reducing noise, as flow attachment and separation at the leading edge significantly influence lift and vortex generation. Morphing technologies often draw inspiration from bionic designs based on natural phenomena, highlighting the potential of More > Graphic Abstract

    A Review of Wind Turbine Blade Morphing: Power, Vibration, and Noise

  • Open Access

    ARTICLE

    Renewable Energy-Based Solutions for Decentralized Electrification: Demand Assessment and Multi-Tier Framework Approach

    Jacob Manyuon Deng1,*, Cyrus Wabuge Wekesa2, Khan Jean De Dieu Hakizimana1, Joseph Nzabahimana3

    Energy Engineering, Vol.122, No.5, pp. 1839-1862, 2025, DOI:10.32604/ee.2025.063398 - 25 April 2025

    Abstract Energy access remains a critical challenge in rural South Sudan, with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass. This study addresses the predicament by evaluating the feasibility of renewable energy-based decentralized electrification in the selected village of Doleib Hill, Upper Nile, South Sudan. Using a demand assessment and the Multi-Tier Framework (MTF) approach, it categorizes households, public facilities, private sector, Non-Governmental Organizations (NGOs) and business energy needs and designs an optimized hybrid energy system incorporating solar Photovoltaic (PV), wind turbines, batteries, and a generator. The proposed… More > Graphic Abstract

    Renewable Energy-Based Solutions for Decentralized Electrification: Demand Assessment and Multi-Tier Framework Approach

  • Open Access

    ARTICLE

    Optimization and Intelligent Control in Hybrid Renewable Energy Systems Incorporating Solar and Biomass

    Arpita Johri1,2,*, Varnita Verma3, Mainak Basu1,*

    Energy Engineering, Vol.122, No.5, pp. 1887-1918, 2025, DOI:10.32604/ee.2025.062355 - 25 April 2025

    Abstract The globe faces an urgent need to close the energy demand-supply gap. Addressing this difficulty requires constructing a Hybrid Renewable Energy System (HRES), which has proven to be the most appropriate solution. HRES allows for integrating two or more renewable energy resources, successfully addressing the issue of intermittent availability of non-conventional energy resources. Optimization is critical for improving the HRES’s performance parameters during implementation. This study focuses on HRES using solar and biomass as renewable energy supplies and appropriate energy storage technologies. However, energy fluctuations present a problem with the power quality of HRES. To… More > Graphic Abstract

    Optimization and Intelligent Control in Hybrid Renewable Energy Systems Incorporating Solar and Biomass

  • Open Access

    ARTICLE

    The Role of Participant Distribution and Consumption Habits in the Optimization of PV Based Renewable Energy Communities

    Antonio Sassone1,*, Shoaib Ahmed1, Alessandro Ciocia2, Gabriele Malgaroli2, Antonio D’Angola1,*

    Energy Engineering, Vol.122, No.5, pp. 1715-1733, 2025, DOI:10.32604/ee.2025.058781 - 25 April 2025

    Abstract The expansion of renewable energy sources (RESs) in European Union countries has given rise to the development of Renewable Energy Communities (RECs), which are made up of locally generated energy by these RESs controlled by individuals, businesses, enterprises, and public administrations. There are several advantages for creating these RECs and participating in them, which include social, environmental, and financial. Nonetheless, according to the Renewable Energy Directive (RED II), the idea of RECs has given opportunities for researchers to investigate the behavior from all aspects. These RECs are characterized by energy fluxes corresponding to self-consumption, energy… More >

  • Open Access

    ARTICLE

    Utilizing Machine Learning and SHAP Values for Improved and Transparent Energy Usage Predictions

    Faisal Ghazi Beshaw1, Thamir Hassan Atyia2, Mohd Fadzli Mohd Salleh1, Mohamad Khairi Ishak3, Abdul Sattar Din1,*

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3553-3583, 2025, DOI:10.32604/cmc.2025.061400 - 16 April 2025

    Abstract The significance of precise energy usage forecasts has been highlighted by the increasing need for sustainability and energy efficiency across a range of industries. In order to improve the precision and openness of energy consumption projections, this study investigates the combination of machine learning (ML) methods with Shapley additive explanations (SHAP) values. The study evaluates three distinct models: the first is a Linear Regressor, the second is a Support Vector Regressor, and the third is a Decision Tree Regressor, which was scaled up to a Random Forest Regressor/Additions made were the third one which was… More >

  • Open Access

    ARTICLE

    Multi-Neighborhood Enhanced Harris Hawks Optimization for Efficient Allocation of Hybrid Renewable Energy System with Cost and Emission Reduction

    Elaine Yi-Ling Wu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1185-1214, 2025, DOI:10.32604/cmes.2025.064636 - 11 April 2025

    Abstract Hybrid renewable energy systems (HRES) offer cost-effectiveness, low-emission power solutions, and reduced dependence on fossil fuels. However, the renewable energy allocation problem remains challenging due to complex system interactions and multiple operational constraints. This study develops a novel Multi-Neighborhood Enhanced Harris Hawks Optimization (MNEHHO) algorithm to address the allocation of HRES components. The proposed approach integrates key technical parameters, including charge-discharge efficiency, storage device configurations, and renewable energy fraction. We formulate a comprehensive mathematical model that simultaneously minimizes levelized energy costs and pollutant emissions while maintaining system reliability. The MNEHHO algorithm employs multiple neighborhood structures… More >

  • Open Access

    ARTICLE

    Monthly Reduced Time-Period Scheduling of Thermal Generators and Energy Storage Considering Daily Minimum Chargeable Energy of Energy Storage

    Xingxu Zhu1,*, Shiye Wang1, Gangui Yan1, Junhui Li1, Hongda Dong2, Chenggang Li2

    Energy Engineering, Vol.122, No.4, pp. 1469-1489, 2025, DOI:10.32604/ee.2025.059956 - 31 March 2025

    Abstract To address the excessive complexity of monthly scheduling and the impact of uncertain net load on the chargeable energy of storage, a reduced time-period monthly scheduling model for thermal generators and energy storage, incorporating daily minimum chargeable energy constraints, was developed. Firstly, considering the variations in the frequency of unit start-ups and shutdowns under different levels of net load fluctuation, a method was proposed to reduce decision time periods for unit start-up and shut-down operations. This approach, based on the characteristics of net load fluctuations, minimizes the decision variables of units, thereby simplifying the monthly… More >

Displaying 11-20 on page 2 of 115. Per Page