scholarly journals Energy Efficient EAF Transformer – A Holistic Life Cycle Cost Approach

Procedia CIRP ◽  
2016 ◽  
Vol 48 ◽  
pp. 319-324 ◽  
Author(s):  
B. Marchi ◽  
S. Zanoni ◽  
L. Mazzoldi ◽  
R. Reboldi
2021 ◽  
Vol 1764 (1) ◽  
pp. 012185
Author(s):  
Winda Nur Cahyo ◽  
Riza S.I. Raben ◽  
Haryo Prawahandaru ◽  
Bayu A. Swasono ◽  
Riyan Tri Sutartono ◽  
...  

2021 ◽  
Author(s):  
Amir Fereidouni Kondri

This report presents the methodology for determining least cost energy efficient upgrade solutions in new residential housing using brute force sequential search (BFSS) method for integration into the reference house to reduce energy consumption while minimizing the net present value (NPV) of life cycle costs. The results showed that, based on the life cycle cost analysis of 30 years, the optimal upgrades resulted in the average of 19.25% (case 1), 31% (case 2a), and 21% (case 2b) reduction in annual energy consumption. Economic conditions affect the sequencing of the upgrades. In this respect the preferred upgrades to be performed in order are; domestic hot water heating, above grade wall insulation, cooling systems, ceiling insulation, floor insulation, heat recovery ventilator, basement slab insulation and below grade wall insulation. When the gas commodity pricing becomes high, the more energy efficient upgrades for domestic hot water (DHW) get selected at a cost premium.


Water Policy ◽  
2011 ◽  
Vol 14 (3) ◽  
pp. 409-429 ◽  
Author(s):  
V. Ratna Reddy ◽  
Charles Batchelor

Water, sanitation and hygiene (WASH) service levels remain stubbornly low in rural India despite high levels of public expenditure recently. In many areas, this is because service levels have slipped back for reasons including inadequate protection of water sources (quantity and quality) and more attention given to capital expenditure than expenditure on operational and capital maintenance. This paper argues that adoption of a life-cycle cost approach (LCCA) could play a significant role in rectifying this by providing a framework for identifying and plugging gaps in the present pattern of expenditure. It is argued that LCCA will provide a sound basis for implementing the WASH Guidelines released by the Rajiv Gandhi National Drinking Water Mission in 2010. These guidelines signal a shift away from viewing the provision of WASH services as primarily an engineering challenge to one that requires activities that include source protection, institution building and long-term support and pro-poor planning, all of which need to be budgeted for by WASH service providers and/or users. Preliminary findings indicate that LCCA can be used to assess actual life-cycle costs of sustainable, equitable and efficient WASH service delivery. The challenge now is to investigate how best LCCA can be mainstreamed into WASH planning and other governance processes.


Author(s):  
Khanh Q. Bui ◽  
Lokukaluge P. Perera

Abstract Stringent regulations regarding environmental protection and energy efficiency (i.e., emission limits regarding NOx, SOx pollutants and the IMO greenhouse gases reduction target) will mark a significant shift to the maritime industry. In the first place, the shipping industry has strived to work towards feasible technologies for regulatory compliance. Nevertheless, life cycle cost appraisal attaches much consideration of decision-makers when it comes to investment decisions on new technologies. Therefore, the life cycle cost analysis (LCCA) is proposed in this study to evaluate the cash flow budgeting and cost performance of the proposed technologies over their life cycles. In the second place, environmental regulations may support innovation especially in the era of digitalization. The industrial digitalization is expected to revolutionize all of the aspects of shipping and enable the achievement of energy-efficient and environmental-friendly maritime operations. The so-called Internet of things (IoT) with the utilization of sensor technologies as well as data acquisition systems can facilitate the respective maritime operations by means of vessel operational performance monitoring. The big data sets obtained from IoT should be properly analyzed with the help of Artificial Intelligence (AI) and Machine Learning (ML) approaches. Our contribution in this paper is to propose a decision support framework, which comprises the LCCA analysis and advanced data analytics for ship performance monitoring, will play a pivotal role for decision-making processes towards cost-effective and energy-efficient shipping.


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