Energy-efficient induction motors performance characteristics and life-cycle cost comparisons for centrifugal loads

1997 ◽  
Vol 33 (5) ◽  
pp. 1312-1320 ◽  
Author(s):  
P.S. Hamer ◽  
D.M. Lowe ◽  
S.E. Wallace
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.


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.


2018 ◽  
Vol 174 ◽  
pp. 01025 ◽  
Author(s):  
Jacek Korentz ◽  
Beata Nowogońska

Environmental assessment over the course of the full life cycle of a building (LCA - Life Cycle Assessment) covers the environmental burden connected with energy consumption and the accompanying emission of contaminants into the atmosphere from the moment of obtaining a raw material and all stages of its processing and treatment, through the service life of a building, up to the moment that the use value of the building expires and the storage of waste. Literature on the subject is already very rich in this scope. There are numerous works pertaining to the guidelines for calculating all costs of the life cycle of buildings, i.e. environmental, economic and social costs. In these works, however, not much is said about the means of determining the life cycle of building structures. This is very important, especially in the case of the analysing the cycle of the further existence of buildings no longer in use, as well as newly designed ones. The article presents a method of predicting the performance characteristics of a building over the course of its use. The application of this method has been illustrated by the prediction of the performance characteristics of masonry walls, verified by studies carried out on existing buildings. The method - the purpose of research, can be applied to determine the life cycle (LC) of buildings for which LCCA (Life Cycle Cost Analysis) is carried out. A significant problem pertaining to every object in use is ensuring adequate reliability. The process of modeling reliability should have a mathematical basis enabling the problem to be described in detail. The ultimate aim is applying this description when solving problems connected with planning renovation work.


2019 ◽  
Vol 11 (8) ◽  
pp. 2444 ◽  
Author(s):  
Ming Hu

A comprehensive case study on life-cycle cost analysis (LCCA) was conducted on a two- story education building with a projected 40-year lifespan in College Park, Maryland. The aim of this paper was to (1) create a life cycle assessment model, using an education building to test the model, (2) compare the life cycle cost (LCC) of different renovation scenarios, taking into account added renewable energy resources to achieve the university’s overall carbon neutrality goal, and (3) verify the robustness of the LCC model by conducting sensitivity analysis and studying the influence of different variables. Nine renovation scenarios were constructed by combining six renovation techniques and three renewable energy resources. The LCCA results were then compared to understand the cost-effective relation between implementing energy reduction techniques and renewable energy sources. The results indicated that investing in energy-efficient retrofitting techniques was more cost-effective than investments in renewable energy sources in the long term. In the optimum scenario, renovation and renewable energy, when combined, produced close to a 90% reduction in the life cycle cost compared to the baseline. The payback period for the initial investment cost, including avoided electricity costs, varies from 1.4 to 4.1 years. This suggests that the initial investment in energy-efficient renovation is the primary factor in the LCC of an existing building.


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