A clothes dryer is a common household appliance to dry clothes or other fabrics after they have been washed using a washing machine. Clothes dryers use quite a bit energy because they need to spin and produce heat. The energy use of a dryer varies between 1800 watts and 5000 watts, a typical dryer will use around 3000 watts.
Price (kWh): Enter the cost you are paying on average per kilowatt hour, our caculators use the default value of 0.10 or 10 cents. To find an exact price check your electricity bill or take a look at Global Electricity Prices.
The best way to reduce energy use when drying clothes or towels is to hang dry them, this will avoid the clothes dryer all together. If you have a backyard or a balcony setup some hang lines and hang your clothes to dry, you will save energy and money. During winter it may not be possible to hang dry clothes, in that case using a dryer might be required. We recommend not to fully over dry clothes, instead dry your clothes until they are almost dry and hang them up in the house to dry completely.
Industrial energy consumption accounted for more than a fifth of all UK energy consumption in 2001 consuming 35,152 thousand tonnes of oil equivalent and a steady rising trend is shown in Fig. 26 .
Industrial energy use is predominantly used for production, as well as for lighting and other business uses in the manufacturing industries. Industrial production makes up just over half of all global energy use and is expected to grow by a similar 1.5% globally each year through 2035.7
Again according to EIA, not only because of faster anticipated economic expansion but also because of the composition of industrial sector production. OECD economies generally have more energy-efficient industrial operations than non-OECD countries, as well as a mix of industrial output that is more heavily weighted toward non-energy-intensive industry sectors. As a result, the ratio of industrial energy consumption to total GDP tends to be higher in non-OECD economies than in OECD economies. On average, industrial energy intensity (the consumption of energy consumed in the industrial sector per dollar of economic output) in non-OECD countries is double that in OECD countries.8
Industrial energy consumption represents 26% of the European total; industry is therefore incentivized by regulatory bodies to improve energy efficiency. Improving energy efficiency in industry has thus been a primary concern in research studies. PI techniques emerged after the oil crisis in 1970s and are still relevant and effective energy targeting methods to solve industrial energy efficiency problems (Kleme and Kravanja, 2013). PI results typically propose solutions that require modifications to existing plants. Although investment in new technologies and equipment is considered with PI techniques, heat exchanger modifications are typically neglected. Several methods are available to include the cost of the modifications in the heat exchangers within PI (Btn et al., 2017) or as post-processing (Ahmad et al., 1990). However, without knowing the HEN superstructure or even the stream matches, estimation from these methods might deviate significantly from the real cost. HEN design has been deeply studied to improve calculation of the total cost of energy saving measures.
Yee and Grossmann (1990) proposed the SYNHEAT model using mixed integer non-linear programming (MINLP) to solve energy targeting, the matches between hot and cold streams and the optimal superstructure of the HEN simultaneously. One of the nonlinear constraints in HEN is calculation of logarithmic mean temperature difference (LMTD). Barbaro and Bagajewicz (2005) eliminated the nonlinear LMTD constraints by using fixed temperature intervals and formulated the HEN problem in the form of MILP by using linear cost functions.
Since heat exchanger network design is a difficult problem to solve, decomposition methods for dividing and solving it as several subproblems have been developed. The most common three subproblems of HEN are energy targeting (i.e. energy integration), minimum number of hot-cold stream matches (i.e. HLD) and minimum heat exchanger area cost (i.e. HEN superstructure). Franois and Irsia (1989) proposed the SYNEP model which solves the heat exchanger network subproblems by including heuristics. Mian et al. (2016) improved the heat exchanger network superstructure by allowing both parallel and series configurations and coupled MP methods with particle swarm optimization.
Retrofitting problems are currently the focus of many European industries since energy efficiency improvements are implemented on existing sites. Ciric and Floudas (1989) proposed a method to solve the HLD subproblem by including retrofit constraints. Afterward, a MINLP model formulation (Ciric and Floudas, 1990) was used to find the optimal retrofit superstructure applying an iterative procedure. Nguyen et al. (2010) proposed a MILP formulation using the fixed temperature interval model of Barbaro and Bagajewicz (2005).
A gap is identified for solving the HLD in retrofit situations since existing methods either do not clearly state how LMTD is calculated (Ciric and Floudas, 1989) or use predefined temperature intervals and linear cost functions (Barbaro and Bagajewicz, 2005) to fit within the MILP domain. This paper proposes a method to solve HLD retrofit problems based on the work of Ciric and Floudas (1989). The results of HLD can be used for heat exchanger network design in case of unsplit acyclic HENs or can be followed by superstructure synthesis.
Together, commercial and industrial energy uses total 54.3 EJ, of which 41 EJ is industrial energy use. Industry was hardest hit by rising energy prices in the aftermath of the energy crises and had the largest incentive to reform. Indeed, the industrial sector has saved a considerable amount of energy since then (Fig. 4 shows how the industrial sector energy use breaks down). Work has been done on design of variable-speed motors and control mechanisms for machines used in industrial processes. Motors are much more efficient than those of a generation ago. Compressors are especially important to consider, as many heavy industries use compressors for many different purposes.
Many industries have the same opportunity as commercial business for reduction in energy use in officesinstallation of newer, more efficient HVAC systems, replacement of ballasts for fluorescent lighting, or installation of compact fluorescents in place of incandescents, and so on. Industries often buy their electricity on a interruptible basis, meaning that the utility can cut them off if demand from other users is high; the industry gets concessional electricity rates in return. The processes can be designed to result in load leveling for the utility's demand. For example, the industry can use high demand when the utility's other customers are near the low point of demand; this helps the utility by increasing base load slightly (base load is cheapest). Many energy management control systems have been designed that automatically shuffle load on and off in response to external conditions.
While much work has been done, opportunities remain for reducing industrial process energy use. In a 1992 study concerning reduction of carbon dioxide emissions by the United States, a National Academy expert panel identified billions of dollars in savings that would result from changing processes and materials with the aim of lowering carbon emissions (i.e., negative real cost), even in as mature an economy as was current in the United States at that time. Few of its recommendations have been adopted, mostly, it seems because of the attitude that we have not done it that way in the past (in other words, another case of inertia holding back rational change).
Opportunities remain, especially in mining technology, metals refining and working, and chemicals (large subsectors from Fig. 4). In steel processing, hot rolling of metals is being replaced by direct casting and rerolling in small hot strip mills as needed. Scrap to be melted can be preheated using furnace waste heat, reducing overall energy use. More than 50 such energy-saving measures have been identified in the steel industry alone.
Dow Chemical has been a leader in making waste streams into resource streams for other parts of the company or for other companies. This benefits society both by reducing waste emissions and reducing the impact of obtaining the resource. Dow has experienced economic returns over 100% on some programs. If such a well-managed company can find such opportunities, it is clear that practically all other companies can benefit. Experiences such as this and the success of the independent companies colocated in Kalundborg, Denmark, in exchanging materials to mutual benefit have led people to speak of a new field of study they call industrial ecology. There is a hope that bringing attention to these possibilities will result in greater savings and efficiencies in the future and that companies can learn from the best practices of other companies.
The science of chemical catalysis, originally strongest in the petroleum industry, has spread to other industrial sectors. Catalysts are chemicals that increase reaction rates without being themselves consumed in the process. Increases in reaction rates at low temperatures saves the application of thermal energy to raise the temperature (as reaction rates generally increase with temperature).
Glassmaking is an industry that uses a lot of energy per kilogram of output because of the necessity of melting the constituents of glass (or melting glass when it is recycled). New refactory materials have reduced energy use in the glass industry at no cost.
The agricultural industry is one area where penetration of ideas is slow; more energy conservation measures need to be implemented. Individual farmers are rugged individualists and apt to think in many instances that any change is for the worse. One promising avenue is for a combination of chemical and agricultural industry to grow chemical feedstocks and to achieve ways to grow plastics in the field. For this to be entirely successful, negative attitudes held by the general public toward genetic manipulation may have to be abandoned.
In order to understand the impact on industrial energy use, a set of disaggregated engineering process models of major energy using industries is under development. These models are driven by prices and industry output growth rates from the combined models. At present, the capital requirements generated by the industry models and the implicit product prices are not fed back to the more aggregated models. Long-run plans include marrying the disaggregate industry process models directly to the aggregated ones. One approach is to use a hierarchical structure embodying two way flows of output information between the aggregated and disaggregated models and iterating to convergence. This could even be formalized into a single model that would be solved by decomposition techniques. The alternative approach is to run each process model across a wide range of price and demand quantities, and fit the results to some mathematical function. Results from the aggregated models would be fed into the reduced form function as independent variables. The dependent variables generated would be fed back to the higher level aggregated functions. Table 1 indicates the current status of the industry process models. (Pilati and Rosen, 1978a; Marcuse et al., 1978; Pilati and Rosen, 1978b; Marcuse et al., 1979; Coward and Sparrow, forthcoming; Sparrow, forthcoming.)
Manufacturing activities account for a lion's share of the industrial energy consumption. In 1975 the share of manufacturing activities, including coke usage in the steel industry and feedstock inputs to petrochemical industries, out of total industrial energy consumption was 90-97% for Regions I-V, in spite of considerable differences in the composition of their economic structure. In Region VI (ME/NAf) this share was relatively smaller about 62% owing to the exceptionally low level of manufacturing activity and the dominance of oil and gas production in the industrial sector of this region. The scenario assumptions of changes in economic structure, composition of manufacturing activities, and technological coefficients result in projections for the years 2000 and 2030 for which the share of manufacturing in the industrial energy consumption varies between 76 and 90% in all world regions.
In the following paragraphs some salient features of the scenario assumptions affecting the energy consumption in the manufacturing sector in different world regions are outlined. As mentioned earlier these scenario assumptions are based on judgments, past trends, interregional and intercountry comparisons and estimated prospects of technological developments and conservation measures.
The projected changes in the overall economic structures of Region I-VI embodied in the scenarios were outlined in Table 6. Table 15 describes the assumed shifts in the composition of manufacturing activities for the high scenario. The projected changes for the low scenario are in the same general direction but occur relatively more slowly.
Note: In Regions I, II, and III, basic materials also include mining of non-energy products but exclude, manufacturing of petroleum and coal products.Sources: United Nations (1977b); United Nations (1977d); United Nations (1977c).
The requirements of energy for a given mix of manufacturing activities can be reduced as follows: by incorporating better machinery and processes (which reduces the energy intensiveness of these activities); by increasing the share of electricity, district heat and soft solar energy in meeting the demand for thermal processes (which reduces conversion losses); by making increased use of cogeneration and heat pumps (which reduces the requirements of final energy); and by improving the efficiency of fossil fuels for conversion to process heat (which also reduces conversion losses). Tables 16 and 17 outline assumptions of plausible changes in different regions of the world over the next 50 years. The data for 1975 (column 1, Table 16) show considerable differences in average useful energy intensiveness of manufacturing activities in various world regions. These differences are due in part to different mixes of component activities and in part to differences in processes, technologies, and the extent of automation. (For most of the regions the data are relatively scarce and estimates used here have been based on available information for representative countries.)
TABLE 17. Assumed Penetration of Electricity, District Heat, Cogeneration, Heat Pump and Soft Solar in Their Potential Industrial Heat Markets in 2030, High Scenario (% of potential industrial heat markets)(a)
One sees in these projections, in general, a greater reduction of energy intensiveness in the developed regions than in the developing regions. These reductions are particularly large in Regions II (SU/EE) and I (NA) but not so large in Region III (WE/JANZ) where manufacturing activities have already undergone considerable modernization. A part of these reductions is, of course, because of structural changes in the manufacturing activities. The largest structural changes in the manufacturing sector are assumed for the developing regions, where both the most energy-intensive basic material industries and the least energy-intensive machinery and equipment industries grow relatively faster than the nondurable goods industries; this has a balancing effect on the overall energy intensiveness of manufacturing.
For the projections of the penetration of various more efficient energy forms as well as cogeneration and heat pumps in the industrial heat market (see Table 17), regional differences in settlement patterns, past practices, current technological trends, geographical conditions, etc., have been kept in mind. In spite of these technological changes, more than 80% of the industrial process heat requirements in all regions except Region II (SU/EE) would still have to be met by fossil fuels in 2030 in the high scenario. Improvements of the order of 20% in the average efficiency of fossil fuel use are assumed to be possible over the next 50 years.
The overall effect of these technological developments, better practices, and structural changes would be to reduce the average final energy intensiveness of manufacturing activities (excluding use of coke in steel industry and feedstocks) by about 35-55% in different world regions, as shown in Table 18 for the high scenario. The effects of structural changes are somewhat smaller on final energy than on useful energy as the overall conversion efficiencies from final to useful energy are assumed to improve by 20-30% because of technological changes.
At present, the use of coke in the steel industry amounts to 3-12% of final energy requirements of manufacturing activities in various world regions. The consumption of coke per ton of pig iron produced varies considerably from country to country. Estimated regional averages for 1975 are between 500 kg in Region III (WE/JANZ) and 1000 kg in Region V (Af/SEA). The lowest consumption has been achieved by the Japanese steel industry where the consumption decreased to about 390 kg per ton of pig iron in 1972. However, following the oil crisis, the consumption of coke in Japan increased again as fuel oil use decreased; the consumption in 1975 was 441 kg per ton of pig iron. Despite this short term reversal in the trend of the Japanese steel industry, it is assumed here that reductions down to about 400 kg per ton of pig iron would become feasible in various world regions because of future technological improvements.
Table 19 summarizes the present and projected levels of final energy consumption in manufacturing and also shows the growth of electricity in manufacturing energy use in various world regions in the two scenarios. A large share of total final energy would go to manufacturing for all world regions in the scenarios. The trends generally show stable or declining shares (except for Regions I-NA and VI-ME/NAf).
Industrial process heat accounts for more than two-thirds of the total global industrial energy consumption. Half of this demand occurs at temperature levels below 400C. Approximately 40% of the current industrial energy consumption is covered by natural gas and approximately 40% by petroleum products (International Renewable Energy Agency (IRENA), 2015). In several industry sectors such as food, wine and beverages, textiles, transport equipment, machinery, or pulp and paper, the share of heat demand below 250C is around 60% (Potential of Solar Heat for Industrial Processes (POSHIP), 2001). There is a wide variety of promising applications in industry, commercial services, and agriculture. Common is, e.g., the preheating of water for washing or cleaning and the preheating of boiler makeup water. Solar heat can also be integrated directly into industrial heat supply networks, either by heating pressurized water or by solar steam generation. Furthermore, solar air collectors can be used to preheat air for drying or combustion, as well as to heat production halls.
Comparative studies of industrial energy use in similar countries should be encouraged. For example, the United Kingdom and the Federal Republic of Germany, with roughly similar populations, industry composition, and power requirements, use different amounts and forms of energy. International comparative studies, particularly within the NATO countries, will permit an identification of energy-efficient practices and a transfer of knowledge to other countries.
Energy flow diagrams, indicating how and where energy is used in industry, should be prepared. These diagrams should show the quantity, form, source, and quality (e.g. energy content or temperature) of energy required, in order to permit identification of areas where substitution or alternative processes will permit increased efficiency.
Tabulations of the direct energy content of various raw materials and manufactured goods should be compiled and published. Table 1 lists some representative values for common materials. However, it is felt that these values depend heavily on the process used, and such data must be correlated to specific processes to be useful.
There have been a number of international studies to evaluate best practices in major segments of industrial energy use.5 These studies examine specific energy use in various industrial applications (such as glass manufacture, petroleum refining, and iron and steel mills) at different plants in different countries. From these data, the most efficient plants are used to establish a best practice, or best available technology for each end use. Then, by comparing the best practice to the average specific energy required for that end use, an estimate of the savings possible by deploying the best practice can be made. Compilations of such data provide an efficiency benchmark for individual companies to compare their process performance against others in the same industry.
Today there are many tools available to the energy manager to analyze or evaluate specific industrial processes. An example is the U.S. Department of Energys Advanced Manufacturing Office (AMO), formerly the Office of Industrial Technology. This office provides many information sources, case studies, and tools for improving industrial process energy efficiency. Some of the specific types of equipment addressed are boilers and steam systems, air compressors, motors, fans, pumps, and process heat technologies. The website is www.energy.gov/eere/amo/information-resources. Besides free tools that help energy managers assess the efficiency of various industrial processes, the website has links to other sources of information. Another example is a website hosted by the European Community at http://iet.jrc.ec.europa.eu/energyefficiency. Technical guides, training courses, manuals, and other documents can be accessed at this site in various languages.
Caution must be exercised in applying any of the principles that follow on a general basis. Process energy use tends to be site- and process-specific. What is appropriate for one process and one plant may not be appropriate for a similar process in another plant, depending on fuel types and costs, weather patterns, variations in material properties, and a host of other variables. Judgment, careful analysis, and sound engineering are prerequisite for any successful energy management program.
Chapters 13 ofChapter 1Chapter 2Chapter 3 the Energy Audit Standard contain scope, normative references, and definitions of important concepts. Chapter 4, Industrial energy use, contains quality requirements and is broken down as follows:
Thermodynamic applications of exergy have occurred in a diverse range of fields, including electricity generation and cogeneration, fuel processing, energy storage, transportation, industrial energy use, building energy systems, and many others.
For example, the present authors, have applied exergy analysis to various industrial systems , renewable energy , hydrogen energy , energy storage , thermal energy storage [33,34], buildings [35,36], countries and sectors of countries , and electricity generation and multigeneration . Exergy methods can also be used in optimizing energy systems .
Several books on exergy analysis, including numerous applications, have been published over the past three decades [14,5056], as have many research articles dealing with applications . Also, exergy has been worked extensively into many books on thermodynamics .