Research on forecasting coal bed methane demand and resource allocation system based on time series. Issue 5 (September 2020)

• Record Type: Journal Article
• Authors: Linghu, Jianshe; Chen, Jinhua; Yan, Zhiming
• Is Part Of: Energy exploration & exploitation. Volume 38:Issue 5(2020)
• Page Start: 1467
• Page End: 1483
• Publication Date: 2020-09
• Subjects: Coalbed methane -- time series -- demand prediction -- resource allocation; Power resources -- Periodicals; 333.79
• DOI: 10.1177/0144598720953505
• Languages: English
• ISSNs: 0144-5987

Abstract

The mining area is the main place for the development and utilization of Coalbed Methane (CBM), and there are a series of systems for the development and utilization of CBM. However, owing to lack of a clear understanding of demand-side gas consumption rules and a reasonable resource allocation system, a large amount of CBM resources in the mining area are wasted. In order to predict the demand for CBM dynamically, the Seasonal Auto Regressive Integrated Moving Average (SARIMA) model, Additive Holt-Winters (AHW) model and Multiplicative Holt-Winters (MHW) model based on time series are used to predict the monthly demand for CBM in Yangquan Mine Area in 2020, respectively. Then the predicted results are evaluated by using the prediction model parameters combined with the characteristics of actual demand for CBM. Finally, a resource allocation system under different supply and demand conditions is built to reduce the waste of resources. In this paper, it is found that the information of the actual data is not sufficiently extracted in the MHW model while the SARIMA model can reflect the cyclical trend of monthly demand for CBM under ideal conditions. Furthermore, the AHW model can reasonably predict the demand for CBM under the influence of COVID-19, with a mean relative error of 0.099. The supply and demand distribution system built based on the proposed models can solve the problem of seasonal unevenness of CBM demand in mining areas and ensure the economic benefits of mining areas.