Article: An optimal daily fund scheduling model based on ARIMA Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.42 pp.93 - 114 Abstract: In the context of the continuous development of the energy market and increasing competition within the electricity sector, an effective daily fund scheduling model has become crucial for the management and operation of power enterprises. This paper proposes an optimal daily fund scheduling model based on the autoregressive integrated moving average (ARIMA) model, aiming to optimise the fund utilisation and daily operational decisions of power companies. Initially, we establish the ARIMA model, utilising historical sales data for training and validation to forecast future electricity sales volumes. Subsequently, we adjust the electricity sales revenue data to account for the impact of holidays. By comparing the deviation rates before and after the adjustments, we demonstrate that the adjusted model exhibits higher accuracy and stability. Finally, we propose an intra-month adjustment strategy to further refine the daily fund scheduling model, enhancing its adaptability to market changes and holiday effects. Empirical results indicate that the proposed ARIMA-based optimal daily fund scheduling model offers significant advantages in forecasting accuracy and decision-making effectiveness. This model can serve as a valuable reference for the fund management and daily operations of power enterprises. Inderscience Publishers - linking academia, business and industry through research

Title: An optimal daily fund scheduling model based on ARIMA

Authors: Jiaying Chen; Jiaming Jiang; Songlin Gao; Hao Li; Ying Zhuang

Addresses: State Grid Zhejiang Electric Power Co., Ltd., Hangzhou, Zhejiang, 310007, China ' State Grid Zhejiang Electric Power Co., Ltd., Hangzhou, Zhejiang, 310007, China ' State Grid Zhejiang Electric Power Co., Ltd., Hangzhou, Zhejiang, 310007, China ' State Grid Zhejiang Electric Power Co., Ltd., Hangzhou, Zhejiang, 310007, China ' State Grid Zhejiang Electric Power Co., Ltd., Hangzhou, Zhejiang, 310007, China

Abstract: In the context of the continuous development of the energy market and increasing competition within the electricity sector, an effective daily fund scheduling model has become crucial for the management and operation of power enterprises. This paper proposes an optimal daily fund scheduling model based on the autoregressive integrated moving average (ARIMA) model, aiming to optimise the fund utilisation and daily operational decisions of power companies. Initially, we establish the ARIMA model, utilising historical sales data for training and validation to forecast future electricity sales volumes. Subsequently, we adjust the electricity sales revenue data to account for the impact of holidays. By comparing the deviation rates before and after the adjustments, we demonstrate that the adjusted model exhibits higher accuracy and stability. Finally, we propose an intra-month adjustment strategy to further refine the daily fund scheduling model, enhancing its adaptability to market changes and holiday effects. Empirical results indicate that the proposed ARIMA-based optimal daily fund scheduling model offers significant advantages in forecasting accuracy and decision-making effectiveness. This model can serve as a valuable reference for the fund management and daily operations of power enterprises.

Keywords: autoregressive integrated moving average; ARIMA; daily fund scheduling; monthly day count adjustment.

DOI: 10.1504/IJICT.2026.153380

International Journal of Information and Communication Technology, 2026 Vol.27 No.42, pp.93 - 114

Received: 16 Dec 2025
Accepted: 21 Jan 2026
Published online: 06 May 2026 *

Title: An optimal daily fund scheduling model based on ARIMA

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