# A Novel Model for Accurate Daily Urban Gas Load Prediction Using Genetic Algorithms
## 1 Introduction  
### Background  
In recent years, China's natural gas consumption has shown a continuous growth trend [1]. In the context of the \"Dual carbon goals\" strategy, renewable energy is increasingly becoming a core component of the energy mix. However, natural gas is the category with the lowest carbon emission per unit of fossil fuel. It can not only replace high-carbon fossil energy but also form synergy and complementarity with renewable energy. This dual function still gives it irreplaceable strategic value in the process of energy system transformation to low carbon [2]. In 2020, China's carbon emissions will be about \(98.9\times 10^{8}\) tons, accounting for about 30.9% of the world's total carbon emissions, while natural gas only accounts for 5.4% [3]. With the enhancement of environmental awarenessand the promotion of energy structure adjustment, natural gas, as a relatively clean and efficient energy, has been increasing its proportion in the energy consumption structure. Since 2006, China's natural gas consumption has grown at an average annual rate of about 8%, climbing from 69.3 \(\times\) 10\({}^{8}\) m\({}^{3}\) in 2006 to 4584 \(\times\) 10\({}^{8}\) m\({}^{3}\) in 2020, an increase of nearly 4.7 times in 15 years [4; 5]. This growth is not only due to the demand for energy replacement in the industrial sector but also closely related to the transformation of residential energy consumption structure. However, the rapid expansion of consumption is in sharp contrast to the insufficient capacity of urban natural gas reserves, and the working gas storage in 2024 only accounts for 5.8% of consumption, far below the internationally recognized safe reserve level of 15-20% [6]; consequently; the imbalance between supply and demand in the winter heating period is particularly prominent. From the industrial field to residential life, the application range of natural gas is more and more extensive; for example, in industrial production, natural gas is used for heating, power generation, and other links; in the life of residents, the demand for gas heating and gas cooking is growing day by day. According to the \"China Urban Gas Development Report (2024)\" [7], from 2018 to 2022, the domestic gas consumption increased from 82 \(\times\) 10\({}^{8}\) m\({}^{3}\) to 105 \(\times\) 108 m\({}^{3}\), with an average annual growth of 3.2%, of which the heating and cooking gas consumption accounted for 45% and 30%, respectively. However, due to the rapid growth of natural gas consumption, the contradiction between fuel supply and demand has become the core issue restricting urban energy security. The rapid growth of natural gas consumption has made the gas supply-demand imbalance become gradually prominent. Due to the shortage of natural gas reserves in cities, the situation of gas supply and demand is becoming increasingly severe, and \"gas shortage\" and \"guaranteed supply\" have become the key words of gas industry development. Gas load data are of great significance in alleviating the gas supply-demand imbalance [8]. Gas load forecasting can predict gas load data and provide a basis for gas supply planning, the maintenance planning of gas pipe network, and distribution network scheduling [9]. Therefore, research on gas load forecasting has been an area of focus. Accurate gas demand forecasting is of great importance to ensure the smooth and reliable use of gas in cities. In addition, the accurate prediction of daily gas load, as well as the reasonable formulation and decision-making of natural gas peak regulation measures, are very necessary to effectively alleviate the uneven gas consumption and ensure a safe and stable gas supply [10]. Gas forecasting faces many challenges and has certain difficulties. Firstly, gas demand is affected by many factors [11], including weather conditions, economic development level, residents' living habits, industrial production activities, etc. These factors interweave with each other, making the changing law of gas demand complicated and difficult to distinguish.