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  • Open Access

    ARTICLE

    Energy Price Forecasting Through Novel Fuzzy Type-1 Membership Functions

    Muhammad Hamza Azam1, Mohd Hilmi Hasan1,*, Azlinda A Malik2, Saima Hassan3, Said Jadid Abdulkadir1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1799-1815, 2022, DOI:10.32604/cmc.2022.028292 - 18 May 2022

    Abstract Electricity price forecasting is a subset of energy and power forecasting that focuses on projecting commercial electricity market present and future prices. Electricity price forecasting have been a critical input to energy corporations’ strategic decision-making systems over the last 15 years. Many strategies have been utilized for price forecasting in the past, however Artificial Intelligence Techniques (Fuzzy Logic and ANN) have proven to be more efficient than traditional techniques (Regression and Time Series). Fuzzy logic is an approach that uses membership functions (MF) and fuzzy inference model to forecast future electricity prices. Fuzzy c-means (FCM)… More >

  • Open Access

    ARTICLE

    Optimized Gated Recurrent Unit for Mid-Term Electricity Price Forecasting

    Rashed Iqbal1, Hazlie Mokhlis1, Anis Salwa Mohd Khairuddin1,*, Syafiqah Ismail1, Munir Azam Muhammad2

    Computer Systems Science and Engineering, Vol.43, No.2, pp. 817-832, 2022, DOI:10.32604/csse.2022.023617 - 20 April 2022

    Abstract Electricity price forecasting (EPF) is important for energy system operations and management which include strategic bidding, generation scheduling, optimum storage reserves scheduling and systems analysis. Moreover, accurate EPF is crucial for the purpose of bidding strategies and minimizing the risk for market participants in the competitive electricity market. Nevertheless, accurate time-series prediction of electricity price is very challenging due to complex nonlinearity in the trend of electricity price. This work proposes a mid-term forecasting model based on the demand and price data, renewable and non-renewable energy supplies, the seasonality and peak and off-peak hours of… More >

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