Water use and demand forecasting model for coal-fired power generation plant in China

• Main Authors: Wang, Xiao Jun, Elmahdi, Amgad, Zhang, Jian Yun, Shahid, Shamsuddin, Liao, Chuan Hua, Zhang, Xu, Liu, Yong Gang
• Format: Article
• Published: Springer Netherlands 2019
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/89498/; http://dx.doi.org/10.1007/s10668-018-0124-0
• Institution: Universiti Teknologi Malaysia

China is planning to expand its coal power generation to meet its energy demand and support the economic development. The current level of water use for thermal power generation is 8% of total water use, China is a water-stressed country which is facing many new challenges including climate change and population growth. China’s future coal power industry will add further pressures on already stressed water resources. This raised the key question on how the limited water resources can be managed to meet the demand of planned coal power expansion. A great level of understanding on the present status of water use and forecasting future demand in coal power plant is very important to answer this question. However, knowledge gap, data availability and accessibility are the major challenge in this regard. This paper attempts to improve the knowledge of the water demand in the coal power generation plant in China by using a simple water use model. Furthermore, a method is proposed to forecast future water demand in coal power plant. The proposed method is applied for forecasting water demand in Shaanxi coal power bases in Northern China under four scenarios. The results showed that the future water demand for Shaanxi coal power base will increase by 102–161% compared to current use under different scenarios in order to increase the production capacity by 206%. Adopting the optimum level of current status of water use, it is possible to limit the increase in water demand by 102% or 47.119 million-m3. It is expected that the finding of the study would help decision-making processes in water resources management in Chinese coal power generation.