Reducing industrial energy demand in the UK: A review of energy efficiency technologies and energy saving potential in selected sectors

Chowdhury, Jahedul Islam; Hu, Yukun; Haltaş, İsmail; Balta‐Ozkan, Nazmiye; Matthew, George; Varga, Liz

doi:10.1016/j.rser.2018.06.040

Cited by 134 publications

(48 citation statements)

References 86 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Bioenergy and biowaste utilization, including anaerobic digestion, pyrolysis and gasification, is a broad and active field focused on reducing fossil energy dependence (Chowdhury et al, 2018).…”

Section: Technologies and Energy Intensitymentioning

confidence: 99%

Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel

Liu

Yang

Fujii

et al. 2021

Economic Analysis and Policy

View full text Add to dashboard Cite

The continued development of artificial intelligence (AI) has changed production methods but may also pose challenges related to energy consumption; in addition, the effectiveness of AI differs across industries. Thus, to develop efficient policies, it is necessary to discuss the effect of AI adoption on energy intensity and to identify industries that are more significantly affected.Using data on industrial robots installed in 16 Chinese industrial subsectors from 2006 to 2016, this paper investigates both the effect of AI on energy intensity and the channel through which this effect is transmitted. The empirical results show, first, that boosting applications of AI can significantly reduce energy intensity by both increasing output value and reducing energy consumption, especially for energy intensities at high quantiles. Second, compared with the impacts in capital-intensive sectors (e.g., basic metals, pharmaceuticals, and cosmetics), the negative impacts of AI on energy intensity in labor-intensive sectors (e.g., textiles and paper) and technology-intensive sectors (e.g., industrial machinery and transportation equipment) are more pronounced. Finally, the impact of AI on energy intensity is primarily achieved through its facilitation of technological progress; this accounts for 78.3% of the total effect. To reduce energy intensity, the Chinese government should effectively promote the development of AI and its use in industry, especially in labor-intensive and technology-intensive sectors.

show abstract

Section: Technologies and Energy Intensitymentioning

confidence: 99%

Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel

Liu

Yang

Fujii

et al. 2021

Economic Analysis and Policy

View full text Add to dashboard Cite

show abstract

“…In [11], a two-stage model has been proposed to consider the impacts of DRs and EEPs in a smart grid environment. An overview of the potential of energy efficiency in reducing energy consumption as well as dropping the pollutants emission in the UK industry has been presented in [12]. Due to the nonlinear nature and complexity of an optimization problem, various innovative solution methods have been studied by researchers [13][14][15].A comprehensive review of articles with the applications of heuristic methods to energy efficiency is presented in [16].…”

Section: Introductionmentioning

confidence: 99%

An application of energy efficiency programs on multi-stage transmission network expansion and reactive power planning

2020

View full text Add to dashboard Cite

Energy efficiency programs as an energy source with multiple advantages (low cost, more reliable and better clean) are considered as one of the most effective solutions to meet future energy needs. In this paper, energy efficiency programs (EEPs) are modelled as virtual sources of power generation to investigate their impacts on expanding transmission network and reactive power planning (RPP). A multi-stage model based on AC power flow has been used to indicate the possibility of postponing the investment actions as the investment deferral in transmission expansion planning (TEP). Two groups of regulatory support schemes are considered as investor income to promote participation in EEPs, namely purchasing certified emission reductions (CERs) and shared saving model. In addition, two standard case studies (Garver & 46-bus Brazilian) are evaluated to demonstrate the promising potential of the proposed model in handling the planning problems of practical power systems. The simulation results show the effectiveness of the proposed model to solve such planning problems in the presence of EEPs.

show abstract

“…The iron and steel industry is one of the largest energy consumers in the industrial sector, accounting for about 18% of delivered industrial sector energy use from non-OECD countries in 2012, and predicted to still account for about 14% in 2040 ( Figure 1). Although modern integrated iron and steel-making plants tend to be more energy efficient, the International Energy Agency reported in 2012 [1] that there is still the potential for the iron and steel industry to reduce its current total energy consumption by approximately 20% through applying the best available technologies in energy efficiency and waste heat recovery [2]. In a typical integrated steel plant, the energy consumption is distributed into roughly 70% for iron and steel production, 20% for rolling, and 10% for miscellaneous consumption such as lighting and air conditioning [3].…”

Section: Introductionmentioning

confidence: 99%

Modelling and simulation of steel reheating processes under oxy-fuel combustion conditions – Technical and environmental perspectives

Tan

Niska

et al. 2019

Energy

Self Cite

View full text Add to dashboard Cite

This paper investigates the impact of flameless oxy-fuel combustion on the thermal performance of a pilot-scale steel reheating furnace. A comprehensive mathematical model, based on the zone method of radiation analysis, was developed, which takes into account the non-grey behaviour of the furnace atmosphere under oxy-fuel combustion conditions. The model was subsequently used to simulate the temperature profile of an instrumented slab used in the experiment. The results showed that the predicted slab temperature profile along the furnace is in good agreement with measurement. However the model over predicted the absolute slab temperatures due to the influence of formation of oxide scales on the slab surface, which was not taken into account in the current model. When compared to air-fuel combustion simulation, the results of oxy-fuel combustion also indicated a marked improvement in the furnace specific fuel consumption (approximately 16%). This was mainly due to the enhanced radiative properties of the furnace atmosphere and reduced exhaust energy losses as the result of less dilution effect from nitrogen. This resulted in reduction in the overall heating time by approximately 14 minutes. Furthermore, if the economics of carbon capture is taken into consideration, theoretically, the energy consumption per kilogram of CO 2 captured can be reduced from 3.5-4.2 MJ kg-1 to 0.96 MJ kg-1. In conclusion, the current studies support the view that oxy-fuel combustion retrofitting to reheating furnaces is a promising option, both from a technical and from an environmental point of view.

show abstract

Reducing industrial energy demand in the UK: A review of energy efficiency technologies and energy saving potential in selected sectors

Cited by 134 publications

References 86 publications

Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel

Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel

An application of energy efficiency programs on multi-stage transmission network expansion and reactive power planning

Modelling and simulation of steel reheating processes under oxy-fuel combustion conditions – Technical and environmental perspectives

Contact Info

Product

Resources

About