An Examination of the Economic Value and Contribution to Energy Efficiency of SaaS Solutions: The Case of E-Invoicing

Author(s):  
Dietmar Nedbal

2018 ◽  
Vol 20 ◽  
pp. 86-97
Author(s):  
Jan Slad ◽  
Andreas Pickard ◽  
Frank Strobelt

The transition of energy mix in Europe is placing greater focus on energy efficiency. Lawmakers in some of EU countries have already recognized that combined heat and power generation (cogeneration, CHP) can help increase energy efficiency. Targeted promotion and subsidization have raised the cost-effective profitability of cogeneration plants significantly. But how can the economic value of this investment be maximized?



2010 ◽  
Vol 100 (5) ◽  
pp. 2492-2509 ◽  
Author(s):  
Piet Eichholtz ◽  
Nils Kok ◽  
John M Quigley

This paper provides the first credible evidence on the economic value of “green buildings” derived from impersonal market transactions rather than engineering estimates. We analyze clusters of certified green and nearby buildings, establishing that “rated” buildings command substantially higher rents and selling prices than otherwise identical buildings. Variations in premiums are systematically related to energy-saving characteristics. Increased energy efficiency is associated with increased selling prices -- beyond the premiums paid for a labeled building. Evidence suggests that the intangible effects of the label itself may also play a role in determining the values of green buildings in the marketplace. (JEL G31,M14,Q52,R33)



2017 ◽  
Vol 33 (5) ◽  
pp. 667-677 ◽  
Author(s):  
C S Shin ◽  
K U Kim ◽  
Patrick Kwon

Abstract. This study involved performing an economic analysis on agricultural tractors classified based on energy efficiency grades using the energy efficiency index. Specifically, 131 models of agricultural tractors commonly used between 2006 and 2010 in South Korea were classified into five categories. The relationship between energy efficiency and economic value was evaluated by a numerical method, and a method of predicting cost and fuel savings based on energy efficiency was developed. Grades of energy efficiency labeled from 1–5 were assumed in order to calculate annual fuel and cost savings. The results indicated that the use of the proposed method resulted in fuel and cost savings given an upgrade from the 5th level of energy efficiency to the 1st level and indicated subsequent improvements with each grade level. This method was applied to data from the year 2008, and total fuel and cost savings were obtained. This indicated that fuel and cost savings in an arbitrary year could be predicted using the proposed method and assuming data from an arbitrary year. Keywords: Agricultural tractors, Economic analysis, Energy efficiency classification grade, Energy efficiency index.



2015 ◽  
Vol 733 ◽  
pp. 303-308 ◽  
Author(s):  
Liang Wen Yue ◽  
Chun You Wu ◽  
Mi'er Zhang

This paper integrated systematically the method of MFA, DEA, and the evaluation method of eco-efficiency, constructed a method of evaluating total factor non-renewable energy efficiency based on the perspective of green growth. And it defined the indicators system of evaluating total factor non-renewable energy efficiency. This paper gave an empirical research of total factor non-renewable energy efficiency, economic efficiency of non-renewable energy, environmental efficiency of non-renewable energy, and eco-efficiency of non-renewable energy, of Chinese provincial regions for the year 2012.Study results confirms: the method of evaluating total factor non-renewable energy efficiency of this paper, not only discussed the evaluating problem of total factor non-renewable energy efficiency of the process of non-renewable energy using, but also brought economic value, environmental influence and ecological cost into evaluating framework of total factor non-renewable energy efficiency; so it is a scientific and comprehensive tool of evaluating non-renewable energy efficiency, and is in conformity with the idea of green growth.



Energy Policy ◽  
2016 ◽  
Vol 97 ◽  
pp. 39-49 ◽  
Author(s):  
Andrea Chegut ◽  
Piet Eichholtz ◽  
Rogier Holtermans




2015 ◽  
Author(s):  
Andrea Chegut ◽  
Piet M. A. Eichholtz ◽  
Rogier Holtermans


Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4336
Author(s):  
Andrew J. Satchwell ◽  
Peter A. Cappers ◽  
Jeff Deason ◽  
Sydney P. Forrester ◽  
Natalie Mims Frick ◽  
...  

Energy efficiency (EE) and demand response (DR) resources provide important utility systems and ratepayer benefits. At the same time, the rapid change in the amount and type of variable renewable energy, like solar and wind, is reshaping the role and economic value of EE and DR, and will likely affect the time-dependent valuation of EE and DR measures. Utilities are increasingly interested in integrating EE and DR measures as a strategic approach to improve their collective cost-effectiveness and performance. We develop a framework to identify the EE and DR attributes, system conditions, and technological factors that are likely to drive interactions between EE and DR. We apply the framework to example measures with different technology specifics in the context of different utility system conditions. We find that EE and DR interactions are likely driven by changes in discretionary load, the addition of controls or other capabilities to shift loads, and the coincidence of savings with system peak or load building periods. Our analysis suggests increasing complexity in evaluating EE and DR interactions when moving from standalone equipment to integrated systems. The framework can be applied to research on integrated building systems by grouping measures into portfolios with different likely implications for EE and DR interactions.



2020 ◽  
Vol 12 (1) ◽  
pp. 115-139 ◽  
Author(s):  
Judson Boomhower ◽  
Lucas Davis

Most analyses of energy efficiency investments ignore that the value of electricity varies widely across hours. We show how much timing matters. Using novel hourly consumption data from an air conditioner rebate program in California, we find that energy savings are concentrated in high-value hours. This significantly increases the value of these investments, especially after we account for the large capacity payments that electricity generators receive to guarantee supply in peak hours. We then use engineering predictions to calculate timing premiums for a wide range of energy efficiency investments, finding substantial variation in economic value across investments. (JEL L94, L98, Q41, Q48)



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