Maissa A. Al Metrik^*, Dhiaa A. Musleh

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1427-1444, 2022, DOI:10.32604/cmc.2022.025722

Abstract Electricity, being the most efficient secondary energy, contributes for a larger proportion of overall energy usage. Due to a lack of storage for energy resources, over supply will result in energy dissipation and substantial investment waste. Accurate electricity consumption prediction is vital because it allows for the preparation of potential power generation systems to satisfy the growing demands for electrical energy as well as: smart distributed grids, assessing the degree of socioeconomic growth, distributed system design, tariff plans, demand-side management, power generation planning, and providing electricity supply stability by balancing the amount of electricity produced and consumed. This paper proposes… More >

Pingping Xia^{1, *}, Aihua Xu², Tong Lian¹

Journal of Quantum Computing, Vol.2, No.1, pp. 25-32, 2020, DOI:10.32604/jqc.2019.09232

Abstract Electricity consumption forecasting is one of the most important tasks for power system workers, and plays an important role in regional power systems. Due to the difference in the trend of power load and the past in the new normal, the influencing factors are more diversified, which makes it more difficult to predict the current electricity consumption. In this paper, the grey system theory and BP neural network are combined to predict the annual electricity consumption in Jiangsu. According to the historical data of annual electricity consumption and the six factors affecting electricity consumption, the gray correlation analysis method is… More >