Download Analytics for Smart Energy Management: Tools and by Seog-Chan Oh, Alfred J. Hildreth PDF
By Seog-Chan Oh, Alfred J. Hildreth
This e-book introduces the problems and difficulties that come up whilst imposing shrewdpermanent strength administration for sustainable production within the car production and the analytical instruments and functions to house them. It makes use of a couple of illustrative examples to give an explanation for power administration in car production, which includes such a lot kinds of production know-how and numerous degrees of strength intake.
It demonstrates how analytical instruments may also help enhance power administration methods, together with forecasting, intake, and function research, rising new know-how identity in addition to funding judgements for constructing shrewdpermanent strength intake practices.
It additionally info sensible strength administration platforms, making it a helpful source for pros excited by actual power administration procedures, and permitting readers to enforce the systems and purposes presented.
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Additional info for Analytics for Smart Energy Management: Tools and Applications for Sustainable Manufacturing
While SFA is likely to have trouble in (a) Energy intensity (kWh/unit) The -th year frontier line The -th year frontier line (b) Energy intensity (kWh/unit) The same -th & year frontier line Plants now appear less efficient Input -th Plants now appear more efficient Input Fig. 3 Two main sources affecting changes in the plant energy efﬁciency over time. 1 Background of Energy Performance Analysis 37 distinguishing technical improvements from efﬁciency improvements, DEA can do so by implementing the Malmquist total factor productivity (TFP) index, which will be discussed in detail in Sect.
This study uses Spearman’s rank-order correlation coefﬁcient test to determine the consistency in ranks between SFA and DEA models in the illustrative study. The rationale for using this test is that though efﬁciency levels (or scores) differ between models, these methods may nonetheless generate similar rankings. If the two models’ rankings are completely different, then any action taken based on the assessment may be temporary and depend on which frontier model is employed. 2 SFA for Energy Performance Analysis The SFA models in this study follow the model speciﬁcation proposed by Battese and Coelli (1995) and expands the cross-sectional data model speciﬁed by Boyd (2005) to a panel data model by incorporating two cross-sectional data sets.
Either output oriented or input oriented) the TFP indices differ. Recently, a new approach adopting a directional distance function was introduced to provide a flexibility in measurement by allowing negative input and output quantities. For more details on the underlying theory and application of directional distance function, see Nin et al. (2003). For the consistency between SFA and DEA models, a new vector variable 1 Zi ¼ ðHDDi ; CDDi ; Wheelbasei ; Utilization Þ is introduced to represent the sysi tematic external factors given for i-th company or plant.