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Top1. Introduction
The reliability and economy of power system operation are important guarantees for the healthy development of both society and the economy. Before a significant breakthrough in energy storage technology, the electricity generation and consumption are roughly equal (Hong et al., 2020; Wang et al., 2022; Chodakowska et al., 2021). Therefore, the planning and operation of the power system, as well as the daily scheduling work of the power system, require REC prediction as the decision-making basis, which has important research significance (Rendon-Sanchez & De Menezes, 2022).
With the continuous development of new energy grids, the combination of new energy and REC has become increasingly close. REC prediction has higher value, higher difficulty, and new technological foundation in the new era. When the power grid consumes intermittent, random, and fluctuating new energy generation, it needs to have a certain reserve capacity. However, when the grid's capacity is insufficient, serious waste of resources, such as wind and solar power, may occur (Phyo & Jeenanunta, 2021; Barman & Dev Choudhury, 2022; Tran et al., 2021). With the further development of electricity market reform, the number of users in the electricity market is gradually increasing. The power market adopts the market mechanism to improve the efficiency of various users in the power sector. Accurate and reliable REC prediction is an important basis for the business decisions of users, such as power companies and retailers. Therefore, as the number of market participants increases, the number of stakeholders who need to make decisions based on REC predictions gradually increases (Li et al., 2022; Mustaqeem & Kwon, 2022). In addition, with the further opening of the electricity market, the impact of REC's predictive power on the profitability of relevant power companies and retailers is gradually increasing. Therefore, REC prediction has a more important position in the new market environment (Ahmed et al., 2020; Huang et al., 2021; Basiri et al., 2021). Moreover, the accuracy of REC prediction results will directly affect the quality of urban power grid planning work (Shahid, Zameer, Muneeb et al., 2021; Wang et al., 2020; Kong et al., 2019). Due to the complex and diverse factors that affect the prediction of residential electricity REC, simply considering the characteristics of the energy consumption system itself is completely insufficient in the energy Internet mode. On the basis of in-depth analysis of electrical characteristics, taking into account social, meteorological, economic, and other influencing factors is necessary to ensure the accuracy and stability of prediction accuracy (Chen et al., 2022; Sheng et al., 2021).
In addition, accurate REC prediction can ensure better trading in the dynamic electricity trading market and is also an important indicator for future planning of the power system. Accurately providing predicted load data for the corresponding period plays a crucial role in generating and selling electricity, formulating reasonable electricity prices, and ensuring the normal production and life of residents. However, the level of REC is influenced by local economic development level, human activities, REC characteristics, and climate conditions, which undoubtedly increase the difficulty of predicting electricity REC (Bento et al., 2021; Gao et al., 2022).