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Natural gas demand prediction: Methods, time horizons, geographical scopes, sustainability issues, and scenarios

持续性 期货合约 天然气 环境经济学 比例(比率) 期限(时间) 环境资源管理 环境科学 计算机科学 经济 工程类 地理 金融经济学 生态学 生物 量子力学 地图学 物理 废物管理
作者
Reza Hafezi,Mohammad Alipour,David A. Wood,Naser Bagheri Moghaddam
出处
期刊:Elsevier eBooks [Elsevier]
卷期号:: 29-53 被引量:3
标识
DOI:10.1016/b978-0-12-824495-1.00002-4
摘要

Research studies published over the past decade provide insight to the methods and focus of long-terms natural gas predictions recently proposed and adopted. A search-engine-based research study location protocol identified 107 studies that had focused on such predictions. By applying filters 45 relevant studies were found to address appropriate time horizons and focus on national/international scale predictions. The analysis presented of these relevant studies provides insight concerning the range of prediction methodologies adopted, the prediction influencing factors (inputs) and time horizons typically employed. Whereas short-term predictions are widely considered across global energy markets, long-term natural gas demand forecasts are most studied in Asia, particularly China, India, and Turkey. These areas are characterized by rapidly expanding gas demand and the recent construction of large gas-related infrastructure developments. Most natura gas prediction studies persist in deriving single deterministic forward-looking trends based only on quantitative data that tend to be less useful to policy makers than several potential trends reflecting alternative possible future scenarios that incorporate data from both qualitative and quantitative influencing variables. Apart from a few exceptions, most long-term gas prediction studies fail to adequately consider environmental and sustainability criteria. A strong case can be made that in coming years the consideration such influencing factors, plus competition from renewable energies will become essential in long-term forecasting of natural gas demand from national and global perspectives. A case study, evaluating a learning scenario development model with six alternative futures provides long-term global gas demand forecasts incorporating sustainability input variables. Close review of relevant gas prediction studies recently published provides insight regarding the methods used, and the time horizons, and geographic areas concentrated upon. Most studies focus on rapidly growing gas markets in Asia and on time horizons of 5–15 years forward. Environmental and sustainability criteria are only just being considered in the most recent studies. Single trend deterministic methods, whereas multiple trends using alternative possible futures and influences are more useful.

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