Energy-saving potential of the industrial sector of Taiwan

Lu, Shyi-Min; Lu, Ching; Tseng, Kuo-Tung; Chen, Falin; Chen, Chen-Liang

doi:10.1016/j.rser.2013.01.021

Cited by 78 publications

(31 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The industrial sector is one of the primary targets for the investigation of energy-saving potentials [9][10][11][12][13]. From the methodological perspective, "top-down" and "bottom-up" models are the mainstream approaches for assessing strategies for energy conservation and emissions reduction.…”

Section: Literature Reviewmentioning

confidence: 99%

Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

Sun

2015

Sustainability

View full text Add to dashboard Cite

Electricity intensity is an important indicator for measuring production efficiency. A comparative study could offer a new perspective on investigating determinants of electricity demand. The Japanese non-metallic mineral products industry is chosen as the object for comparison considering its representative position in production efficiency. By adopting the cointegration model, this paper examines influencing factors of electricity demand in Japanese and Chinese non-metallic mineral products industries under the same framework. Results indicate that although economic growth and industrial development stages are different between the two countries, major factors that affect the sectoral energy consumption are the same. Specifically, economic growth and industrial activity contribute to the growth of sectoral electricity consumption, while R&D intensity, per capita productivity and electricity price are contributors to the decline of sectoral electricity consumption. Finally, in order to further investigate the development trend of sectoral electricity demand, future electricity consumption and conservation potential are predicted under different scenarios. Electricity demand of the Chinese non-metallic mineral products industry is predicted to be 680.53 TWh (terawatt-hours) in 2020 and the sectoral electricity conservation potentials are estimated to be 118.26 TWh and 216.25 TWh under the moderate and advanced electricity-saving scenarios, respectively. OPEN ACCESSSustainability 2015, 7 7113

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

Sun

2015

Sustainability

View full text Add to dashboard Cite

show abstract

“…With respect to sectors and technologies, the focus is mostly laid on those which consume most energy, i.e. energy-intensive industries and buildings ( [11], [12], [13], [14]) or heating/cooling and lighting ( [15], [16], [17]). If national efficiency potentials are available, e.g.…”

Section: Introductionmentioning

confidence: 99%

The potential for energy efficiency in the EU Member States – A comparison of studies

Knoop

Lechtenböhmer

2017

Renewable and Sustainable Energy Reviews

View full text Add to dashboard Cite

In October 2014, the European Council agreed on a target of improving overall energy efficiency by at least 27 per cent by 2030. According to the European Council's conclusions, this target should not be translated into nationally binding targets. Nevertheless individual Member States are free to set higher national objectives if desired. However, it is difficult to assess the degree of ambition of a national target because so far not much light has been shed upon the exact size of the untapped efficiency potentials. This paper provides an in-depth analysis and comparison of existing studies on energy efficiency potentials in the European Union's (EU) Member States by 2030. It includes a structured overview of the results, information on the quality of the available data and suggestions for improvement. The review shows that comprehensive studies on national energy efficiency potentials are rare and hardly comparable. The existing studies agree on the existence of significant potentials for energy efficiency. Their outcomes, however, vary significantly in terms of national levels. Assuming low policy intensity, energy savings between 10 and 28 per cent could be realised by 2030 compared to a baseline development, in the case of high policy intensity 7 to 44 per cent. Technical energy efficiency potentials in the different EU Member States are estimated at 14 to 52 per cent. On average, energy savings of 27 per cent by 2030 appear to be feasible with significant policy effort. We conclude that the deviation in Member States' energy efficiency potentials resulting from different studies represents an indication of the so far poor quality of underlying data. In order to allow for a concretisation of efficiency potential estimates, the comparability and detail of information sources should be improved.

show abstract

“…The total energy saving in Taiwan's industry is assessed as 5.3% of the national energy use per year. The maximal GHG emissions reduction of Taiwan's six most energy-intensive industrial sectors is estimated as 6.4% of the national GHG emissions (Lu et al, 2013). Production activities are widely seen in the manufacturing industry (Chiarini, 2014).…”

Section: Introductionmentioning

confidence: 99%

A generic method for energy-efficient and energy-cost-effective production at the unit process level

Gong

Pessemier

Joseph

et al. 2016

Journal of Cleaner Production

View full text Add to dashboard Cite

Generally, industry includes various sectors like manufacturing, energy, materials & mining, and transportation. Industry consumes about one half of the world's total delivered energy, and manufacturing is one of the energyintensive industrial sectors. With the rising energy price, the energy cost is becoming a controllable expenditure in manufacturing. In this paper, a generic method has been proposed to minimize the energy cost and improve the energy efficiency of manufacturing unit processes. Finite state machines have been used to build the transitional state-based energy model of a single machine. A mixed-integer linear programming mathematical model has been formulated for energy-cost-aware job order scheduling on a single machine. A generic algorithm has been implemented to search for an energy-cost-effective schedule at volatile energy prices with the constraint of due dates. As a result, plant managers can have an energy-cost-effective job order schedule which is associated with machine energy states along time, and can also get time-indexed energy simulation of the schedule. In comparison to most of the static scheduling approaches, stochasticity has been further handled through a cyclic interaction between the scheduler and the energy model, which facilitates to investigate how stochasticity on a shop floor affects the performance of energy-cost-aware scheduling. Empirical data have been used in the case study, including the power measured from a grinding machine, and the real-time pricing and time-of-use pricing tariffs. The proposed method has been demonstrated to be both energy-efficient and energy-cost-efficient even at the presence of stochasticity. As a joint effort of energy efficiency and demand response within demand side management, this method shows its effectiveness for contributing to the reduction of greenhouse gas emissions during peak periods, and for leading to energy-efficient, demand-responsive, and cost-effective manufacturing processes.

show abstract

Energy-saving potential of the industrial sector of Taiwan

Cited by 78 publications

References 10 publications

Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

Determinants of Electricity Demand in Nonmetallic Mineral Products Industry: Evidence from a Comparative Study of Japan and China

The potential for energy efficiency in the EU Member States – A comparison of studies

A generic method for energy-efficient and energy-cost-effective production at the unit process level

Contact Info

Product

Resources

About