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What if we never run out of oil? From certainty of "peak oil" to "peak demand".

ABSTRACT: The COVID-19 pandemic sent the oil industry into turmoil on a scale not seen since the 1970s. While the sector appears to be recovering, questions remain about the extent to which the pandemic has offered a glimpse into the possible future of the industry. This future is critical to the success of climate change mitigation, which requires significant cuts to the carbon dioxide emissions from using oil for energy. Therefore, it makes sense to consider future scenarios in which global oil demand peaks and then declines alongside scenarios of continued demand growth. This is a significant departure from historical development of oil demand and the dominant discussion of many decades about "peak oil" and the fear of demand outstripping readily available supply. The implications of peaking oil demand would be massive, not only for the oil industry but also for society as whole. There is not enough understanding of what the impacts would be, or how to prepare for them. The research community needs to take a clear-eyed view of potential futures of oil, which includes considering scenarios in which demand goes into long-term decline.

SUBMITTER: Halttunen K

PROVIDER: S-EPMC9765301 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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What if we never run out of oil? From certainty of "peak oil" to "peak demand".

Halttunen Krista K Slade Raphael R Staffell Iain I

Energy research & social science 20211127

The COVID-19 pandemic sent the oil industry into turmoil on a scale not seen since the 1970s. While the sector appears to be recovering, questions remain about the extent to which the pandemic has offered a glimpse into the possible future of the industry. This future is critical to the success of climate change mitigation, which requires significant cuts to the carbon dioxide emissions from using oil for energy. Therefore, it makes sense to consider future scenarios in which global oil demand p ...[more]

PMID: 36567695

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Project description:Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers' peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers' location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price, managed supply, etc., in a conceptual 'map' of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tickbox interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

Dataset Information

What if we never run out of oil? From certainty of "peak oil" to "peak demand".

Publications

What if we never run out of oil? From certainty of "peak oil" to "peak demand".

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