2019
DOI: 10.1016/j.apenergy.2019.02.002 View full text |Buy / Rent full text
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Abstract: Energy economy models are central to decision making on energy and climate issues in the 21st century, such as informing the design of deep decarbonisation strategies under the Paris Agreement. Designing policies that are aimed at achieving such radical transitions in the energy system will require ever more in-depth modelling of end-use demand, efficiency and fuel switching, as well as an increasing need for regional, sectoral, and agent disaggregation to capture technological, jurisdictional and policy detai… Show more

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“…As energy storage and artificial intelligence improve the accessibility of energy sources, they will play an important role in energy production and consumption in the future. Furthermore, advances in machine-learning systems, such as artificial intelligence, will revolutionize the demand and supply of energy in our economy (Li et al, 2019;Jose et al, 2020). This is due to the capability of the smart grids and energy storage systems to effectively collect, analyze, and synthesize various data from a wide range of sources such as wind and solar, natural gas and coal to make decisions about the best allocation of energy resources.…”
Section: Literature Reviewmentioning
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“…As energy storage and artificial intelligence improve the accessibility of energy sources, they will play an important role in energy production and consumption in the future. Furthermore, advances in machine-learning systems, such as artificial intelligence, will revolutionize the demand and supply of energy in our economy (Li et al, 2019;Jose et al, 2020). This is due to the capability of the smart grids and energy storage systems to effectively collect, analyze, and synthesize various data from a wide range of sources such as wind and solar, natural gas and coal to make decisions about the best allocation of energy resources.…”
Section: Literature Reviewmentioning
“…Therefore, a hybrid approach using big data analysis has been selected. As Li et al (2019) suggests, the application of big data techniques has the potential to reduce blind spots in ESMs, such as the presented problem of characterising agriculture technologies.…”
Section: Quantitative Characterisation (Steps 4-6)mentioning
“…Current advancements and innovations in data mining, storage, processing, and retrieval have transformed science in various areas, including energy. These advancements will offer significant changes in energy models' operational environment [18]. Another widely used source of life in the world is natural gas as it is incredibly reliable and environment friendly.…”
Section: Introductionmentioning