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The turbo-expander is designed to generate more energy output than the air blower needs, so in certain operating situations, it can export additional power up to 4 MW for sale to the grid. Retrieved 12 Nov. Home Resources Energy Efficient Design. Commercially available?
This needs to be weighed against future savings in fuel inputs and possible charges for pollution outputs, such as through Net Present Value NPV calculations and scenario planning. Highly efficient plants will use less energy and therefore emit less greenhouse gases Time to perform engineering and installation: Designing facilities for high energy efficiency is more complex than traditional design approaches, which may make for a slower design phase.
It can include: Design of a process with low power and heat demand Design and selection of efficient system components e. This involves consideration of new technologies and comparison of the life-time energy savings of different alternatives. The general arrangement can be determined by the most efficient design available. Efficiency gains from upgrading existing faciltiesfacilities, however, can be constrained by the arrangement of existing equipment. The potential gains from EE design must be evaluated against these risks Environmental: Emissions reduction is directly related to EE design Economic rule-of-thumb: EE design savings may be justifiable if the return-on-investment ROI period is short enough.
Feedstock yield-related revamp designs are dependent on market fluctuations i. U5 S Unknown. More options. Find it at other libraries via WorldCat Limited preview. Summary There are so many different energy "fixes" available today, that many energy users are hesitant to do anything because of the apparent complexity of these "fixes. Strange as this may sound, many users today have little or no practical knowledge about their energy purchases. This book covers the basics of rates, components of energy purchases, and the methods and techniques required for maximizing energy savings and minimizing costs.
Energy Efficient Design
For new energy manager or seasoned energy professionals, this book provides the foundation upon which any successful, long-term energy strategy should be based. Bibliographic information. Publication date Note Includes index. The climate scaling increased the CCEs by about 15 percent and was only applied to the space-heating end-use.
Figures 2. The x-axis shows the total reduction in energy use, and the Y-axis shows the CCE in fuel-specific units.
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Each step on the graphs in these two figures represents the total savings for a given end-use for all the cost-effective efficiency measures analyzed for that end-use. The CCE is calculated as the savings-weighted average for all the measures in that end-use cluster. End-uses that do not have technology costs reported in Tables 2.
It should be noted that the space-heating and the space-cooling steps in Figures 2. Each of the supply curves indicates that the projected BAU energy consumption in can be reduced by about 30—35 percent at a cost less than current retail energy prices. The data in the table show that the average CCE is well below the retail energy price in all areas, meaning that adopting these efficiency measures is cost-effective for households and businesses.
In fact, the average CCE for these electricity-savings measures is only about one-quarter of the average retail electricity price. Of course, factors such as local energy prices and weather will influence cost-effectiveness in any particular location. Thus, these efficiency measures in aggregate have a 2.
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These investments would be made by the individuals and private entities making the purchases. The costs of programs to support, motivate, or require these improvements are not included. The CCEs for potential energy efficiency measures numbered are shown versus the ranges of potential energy savings for these measures.
The total savings potential is TWh per year in the residential sector blue solid line and TWh per year in the commercial sector red solid line. For comparison, the national average retail price of electricity in the United States is shown for the residential sector blue dashed line and the commercial sector red dashed line. For many of the technologies considered, on average the investments have positive payback without additional incentives.
CCEs include the costs for add-ons such as insulation. For replacement measures, the CCE accounts for the incremental cost—for example, between purchasing a new but standard boiler and purchasing a new high-efficiency one. CCEs do not reflect the cost of programs to drive efficiency. All costs are shown in dollars. There is an up-front cost to achieving substantial energy savings, but this cost is paid back a number of times over the lifetime of the energy efficiency measures. A few other studies have developed conservation supply curves or, equivalently, the cost of reducing carbon dioxide CO 2 emissions for the United States.
A recent study prepared by McKinsey and Company has received considerable attention Creyts et al. The panel was unable to verify owing to lack of. The total savings potential is 1. For comparison, the national average retail price of natural gas in the United States is shown for the residential sector blue dashed line and the commercial sector red dashed line.
Nevertheless, the results of the McKinsey and Company study generally parallel those of the studies that the panel reviewed in terms of the magnitude and cost of saved energy in buildings. Owing to time and resource constraints, the Brown et al. As a result, the analysis can be improved on in several respects, some of which are highlighted below. Note: For the specific savings, see Figures 2. Efficiency Investment and Savings by for the Buildings Sector. The end-use technology data used in this study are mostly drawn from the CEF study IWG, , which reflects technology and market conditions in the late s.
Clearly, many factors have changed since then, including new technologies becoming available as well as costs falling for some energy efficiency measures owing to improved manufacturing processes, increased volumes, and the relocation of manufacturing facilities to countries where costs are lower.
For example, one study found.
As explained in Section 2. This is a simplifying assumption that introduces uncertainty in the point estimates of the savings potential presented above. Energy prices have risen significantly since the CEF study IWG, , which increases the number of energy efficiency technologies that are cost-effective, thus increasing the energy efficiency potential. For the residential natural-gas end-uses, the New York study Mosenthal et al.
A national study that includes all relevant technologies including shell retrofits would add considerable value to a study extrapolated from New York. The effect of the Energy Independence and Security Act of is considered part of the remaining efficiency potential; that is, the effect of EISA is not included in the baseline. This assumption probably has the largest effect on the lighting end-use, because EISA contains aggressive provisions for lighting efficiency.
The results of Brown et al. Some of the major areas of uncertainty include energy prices, the availability and price of efficiency technologies, and potential changes in consumer behavior.
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They also include the policy context—for example, whether or not limits on greenhouse gas emissions are enacted, and if so, with what degree of stringency. Studies of efficiency potential, such as the CEF and New York studies, are highly aggregated analyses that tend to ignore the great variability in the building stock with respect to climate, building configuration, equipment ownership, building occupancy and use, and other factors.
Future studies should be conducted at a greater level of disaggregation to address variability in the building stock. As noted above, the conservation supply-curve approach to estimating potential savings itself has limitations. The initial models of the cost of saving energy did not account for the life of energy-using equipment or for whether the new. The models assumed that the existing equipment needed to be replaced and could be replaced with a more efficient technology.
The models were static in assuming that customers would want to buy the best technology today, instead of waiting until a better technology was available. The models did not account for the time and costs of disseminating information about the new technologies, the availability of capital to acquire the often more expensive equipment, the risks to existing production, and other barriers.
Some economists expressed skepticism about the results—especially when businesses and consumers did not take advantage of the new, better technologies that promised large economic benefits.