Publicaciones en las que colabora con Thamer Saad Alquthami (13)

2023

  1. A hybrid framework for short term load forecasting with a navel feature engineering and adaptive grasshopper optimization in smart grid

    Applied Energy, Vol. 338

2022

  1. A Performance Comparison of Machine Learning Algorithms for Load Forecasting in Smart Grid

    IEEE Access, Vol. 10, pp. 48419-48433

  2. A Short-Term Load Forecasting Model Based on Self-Adaptive Momentum Factor and Wavelet Neural Network in Smart Grid

    IEEE Access, Vol. 10, pp. 77587-77602

  3. Hyperparameter optimization of support vector machine using adaptive differential evolution for electricity load forecasting

    Energy Reports, Vol. 8, pp. 13333-13352

2021

  1. (DA-DOPF): A Day-Ahead Dynamic Optimal Power Flow With Renewable Energy Integration in Smart Grids

    Frontiers in Energy Research, Vol. 9

  2. A Joint Optimization Model for Energy and Reserve Capacity Scheduling with the Integration of Variable Energy Resources

    IEEE Access, Vol. 9, pp. 75252-75264

  3. An incentive based dynamic pricing in smart grid: A customer’s perspective

    Sustainability (Switzerland), Vol. 13, Núm. 11

  4. Mining software architecture knowledge: Classifying stack overflow posts using machine learning

    Concurrency and Computation: Practice and Experience, Vol. 33, Núm. 16

2020

  1. A novel load scheduling mechanism using artificial neural network based customer profiles in smart grid

    Energies, Vol. 13, Núm. 5

  2. A residential load scheduling with the integration of on-site PV and energy storage systems in micro-grid

    Sustainability (Switzerland), Vol. 12, Núm. 1

  3. An Optimal Scheduling and Distributed Pricing Mechanism for Multi-Region Electric Vehicle Charging in Smart Grid

    IEEE Access, Vol. 8, pp. 40298-40312

  4. Dynamic Pricing Mechanism with the Integration of Renewable Energy Source in Smart Grid

    IEEE Access, Vol. 8, pp. 16876-16892

  5. Multi-Objective Optimal Power Flow with Integration of Renewable Energy Sources Using Fuzzy Membership Function

    IEEE Access, Vol. 8, pp. 143185-143200