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  • Open Access

    ARTICLE

    Machine Learning-based Electric Load Forecasting for Peak Demand Control in Smart Grid

    Manish Kumar1,2,*, Nitai Pal1

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4785-4799, 2023, DOI:10.32604/cmc.2022.032971

    Abstract Increasing energy demands due to factors such as population, globalization, and industrialization has led to increased challenges for existing energy infrastructure. Efficient ways of energy generation and energy consumption like smart grids and smart homes are implemented to face these challenges with reliable, cheap, and easily available sources of energy. Grid integration of renewable energy and other clean distributed generation is increasing continuously to reduce carbon and other air pollutants emissions. But the integration of distributed energy sources and increase in electric demand enhance instability in the grid. Short-term electrical load forecasting reduces the grid fluctuation and enhances the robustness… More >

  • Open Access

    ARTICLE

    Photovoltaic Models Parameters Estimation Based on Weighted Mean of Vectors

    Mohamed Elnagi1, Salah Kamel2, Abdelhady Ramadan2, Mohamed F. Elnaggar3,4,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5229-5250, 2023, DOI:10.32604/cmc.2023.032469

    Abstract Renewable energy sources are gaining popularity, particularly photovoltaic energy as a clean energy source. This is evident in the advancement of scientific research aimed at improving solar cell performance. Due to the non-linear nature of the photovoltaic cell, modeling solar cells and extracting their parameters is one of the most important challenges in this discipline. As a result, the use of optimization algorithms to solve this problem is expanding and evolving at a rapid rate. In this paper, a weIghted meaN oF vectOrs algorithm (INFO) that calculates the weighted mean for a set of vectors in the search space has… More >

  • Open Access

    ARTICLE

    Engine Performance Using Blended Fuels of Biodiesel and Eco Diesel

    Muhammad Idris1,*, I. Husin2, Indra Hermawan1, Uun Novalia3, R. D. Batubara1, Nugroho Agung Pambudi4,*, Alfan Sarifudin4

    Energy Engineering, Vol.120, No.1, pp. 107-123, 2023, DOI:10.32604/ee.2023.019203

    Abstract Diesel engines is an internal combustion engine with high thermal efficiency, which also uses biodiesel fuel, an environmentally friendly, non-toxic, and low sulfur content. Biodiesel has been around for a long time due to its similar characteristics to diesel fuels which has limited availability. However, several disadvantages are associated with biodiesel, such as poor volatility and high viscosity, which reduces engine performance. Therefore, this study was carried out to improve the diesel engine performance by mixing biodiesel with ecodiesel (ED), an additive produced from natural ingredients that is dissolvable in biodiesel. The biodiesel fuel properties used are  density 860 kg/, dynamic… More >

  • Open Access

    ARTICLE

    Research on Evaluation of Multi-Timescale Flexibility and Energy Storage Deployment for the High-Penetration Renewable Energy of Power Systems

    Hongliang Wang1, Jiahua Hu1, Danhuang Dong1, Cenfeng Wang1, Feixia Tang2, Yizheng Wang1, Changsen Feng2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1137-1158, 2023, DOI:10.32604/cmes.2022.021965

    Abstract With the rapid and wide deployment of renewable energy, the operations of the power system are facing greater challenges when dispatching flexible resources to keep power balance. The output power of renewable energy is uncertain, and thus flexible regulation for the power balance is highly demanded. Considering the multi-timescale output characteristics of renewable energy, a flexibility evaluation method based on multi-scale morphological decomposition and a multi-timescale energy storage deployment model based on bi-level decision-making are proposed in this paper. Through the multi-timescale decomposition algorithm on the basis of mathematical morphology, the multi-timescale components are separated to determine the flexibility requirements… More >

  • Open Access

    ARTICLE

    Selection of Wind Turbine Systems for the Sultanate of Oman

    M. A. A. Younis1,*, Anas Quteishat1,2

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 343-359, 2023, DOI:10.32604/csse.2023.029510

    Abstract The Sultanate of Oman has been dealing with a severe renewable energy issue for the past few decades, and the government has struggled to find a solution. In addition, Oman’s strategy for converting power generation to sources of renewable energy includes a goal of 60 percent of national energy demands being met by renewables by 2040, including solar and wind turbines. Furthermore, the use of small-scale energy from wind devices has been on the rise in recent years. This upward trend is attributed to advancements in wind turbine technology, which have lowered the cost of energy from wind. To calculate… More >

  • Open Access

    ARTICLE

    Maximum Power Extraction Control Algorithm for Hybrid Renewable Energy System

    N. Kanagaraj*, Mohammed Al-Ansi

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 769-784, 2023, DOI:10.32604/csse.2023.029457

    Abstract In this research, a modified fractional order proportional integral derivate (FOPID) control method is proposed for the photovoltaic (PV) and thermoelectric generator (TEG) combined hybrid renewable energy system. The faster tracking and steady-state output are aimed at the suggested maximum power point tracking (MPPT) control technique. The derivative order number (µ) value in the improved FOPID (also known as PIλDµ) control structure will be dynamically updated utilizing the value of change in PV array voltage output. During the transient, the value of µ is changeable; it’s one at the start and after reaching the maximum power point (MPP), allowing for… More >

  • Open Access

    ARTICLE

    Genetic Algorithm Based Smart Grid System for Distributed Renewable Energy Sources

    M. Mythreyee*, Dr A. Nalini

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 819-837, 2023, DOI:10.32604/csse.2023.028525

    Abstract This work presents the smart grid system for distributed Renewable Energy Sources (RES) with control methods. The hybrid MicroGrids (MG) are trending in small-scale power systems that involve distributed generations, power storage, and various loads. RES of solar are implemented with boost converter using Maximum Power Point Tracking (MPPT) with perturb and observe technique to track the maximum power. Also, the wind system is designed by permanent magnet synchronous generator that includes boost converter with MPPT technique. The battery is also employed with a Direct Current (DC)-DC bidirectional converter, and has a state of charge. The MATLAB/Simulink Simscape software is… More >

  • Open Access

    ARTICLE

    Optimal FOPID Controllers for LFC Including Renewables by Bald Eagle Optimizer

    Ahmed M. Agwa1, Mohamed Abdeen2, Shaaban M. Shaaban1,3,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5525-5541, 2022, DOI:10.32604/cmc.2022.031580

    Abstract In this study, a bald eagle optimizer (BEO) is used to get optimal parameters of the fractional-order proportional–integral–derivative (FOPID) controller for load frequency control (LFC). Since BEO takes only a very short time in finding the optimal solution, it is selected for designing the FOPID controller that improves the system stability and maintains the frequency within a satisfactory range at different loads. Simulations and demonstrations are carried out using MATLAB-R2020b. The performance of the BEO-FOPID controller is evaluated using a two-zone interlinked power system at different loads and under uncertainty of wind and solar energies. The robustness of the BEO-FOPID… More >

  • Open Access

    EDITORIAL

    Key Optimization Issues for Renewable Energy Systems under Carbon-Peaking and Carbon Neutrality Targets: Current States and Perspectives

    Bo Yang1, Zhengxun Guo1, Jingbo Wang1,*, Chao Duan2, Yaxing Ren3, Yixuan Chen4

    Energy Engineering, Vol.119, No.5, pp. 1789-1795, 2022, DOI:10.32604/ee.2022.022217

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Distributionally Robust Optimal Dispatch of Virtual Power Plant Based on Moment of Renewable Energy Resource

    Wenlu Ji, Yong Wang*, Xing Deng, Ming Zhang, Ting Ye

    Energy Engineering, Vol.119, No.5, pp. 1967-1983, 2022, DOI:10.32604/ee.2022.020011

    Abstract Virtual power plants can effectively integrate different types of distributed energy resources, which have become a new operation mode with substantial advantages such as high flexibility, adaptability, and economy. This paper proposes a distributionally robust optimal dispatch approach for virtual power plants to determine an optimal day-ahead dispatch under uncertainties of renewable energy sources. The proposed distributionally robust approach characterizes probability distributions of renewable power output by moments. In this regard, the faults of stochastic optimization and traditional robust optimization can be overcome. Firstly, a second-order cone-based ambiguity set that incorporates the first and second moments of renewable power output… More >

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