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Abstract The absorption refrigeration system driven by low grade heat sources, especially the waste heat sources, becomes more and more attractive in recent decades. However, most traditional absorption systems cannot achieve a high utilization rate of the waste heat with limited heat capacity. These systems are usually designed to obtain heat in the generator, which means that the waste heat sources cannot be utilized to the temperature lower than the generator temperature. This paper proposed a new structure heated by heat conduction oil in the generator and electric heating rings around the stripping section. This structure can simulate the temperature-distributed heat sources when the electric heating rings work. It can also simulate a traditional generator when the electric heating rings do not work. Influences of different heat distributions are analyzed in detail in this paper. The results show that the heat sources utilization rate will increase with the increase of the heat in the stripping section, while the coefficient of performance will be negatively affected by the increasing heat in the stripping section. By optimizing the heating structure, the coefficient of performance can be similar to that of a traditional system when the heat is just added in the middle and lower part of stripping section. The optimum utilization rate of heat sources in this test model can reach 1.8 times to that of a traditional system. Under this heating model, the lowest temperature required in the heating section is 82 °C when the heat conduction oil inlet temperature is 169 °C. It is much lower than the temperature inside the generator, which is 137.3 °C.

Abstract Large amounts of heat is wasted through air coolers and water coolers for cooling low temperature ( H ) recovered in the evaporator were 8.0–8.6 MW for ORC using i-pentane as working fluid and 8.2–8.3 MW for Kalina cycle, respectively. Efficiency (η) of selected systems obtained at the highest power generated (W T ) was 10.0% (W T = 862 kW) for ORC and 10.57% (W T = 996 kW) for Kalina cycle within the design boundaries. Calculated carbon dioxide (CO 2 ) emission reduction potential was 2260 t/y for ORC and 2600 t/y for Kalina system, respectively, at advantageous process conditions. Results showed that Kalina cycle provided higher efficiency and power generation ability on expense of higher system pressure (29 bar–7 bar). Economic calculations showed that the payback time is about 5.0 year for both systems.

Abstract We will consider cumulative socioeconomic impacts in environmental impact assessment and mitigation processes. Cumulative impacts from several simultaneous projects are greater than aggregate impacts for projects built in isolation. Impacts of energy facilities provide a baseline for potential cumulative impacts in a number of regions. Case studies illustrate the importance of cumulative impacts, as well as their uneven treatment in the environmental impact statement (EIS) process. Important institutional, legal, and practical considerations associated with cumulative impacts are analyzed, and descriptions are offered of how cumulative impact assessments can be used as tools in decision-making.

An operational cost minimisation model is established for a smart energy hub (S.E. Hub) consisting of a combined heat and power (CHP) unit, a heating, ventilation and air-conditioning (HVAC) system, and thermal and electricity storage units. The optimal operation of CHP is combined with the load management of HVAC under a time-of-use (TOU) tariff. The heat and power split ratio of CHP is dynamically determined during the operation. The scheduling of HVAC load and the charging/discharging of energy storage systems are also determined through the optimisation model. The energy management system can therefore shift the load demand and manage energy supply simultaneously. System operation requirements and environment factors including the outdoor air-temperature variation, seasonal variation, and battery degradation are considered. Comprehensive case studies are carried out to examine the effectiveness of the proposed strategy, from which insights are obtained for different energy management strategies and possible upgrade of S.E. Hub. Simulation results reveal that dynamic control of the CHP heat and power split ratio is an effective way to save the total operational cost, and a clear cost saving is shown through the proposed optimal operation strategy.

Identifying the drivers of carbon dioxide emissions in the manufacturing industry is vital for developing effective environmental policies. This study adopts provincial panel data from 2000 to 2013 and uses nonparametric additive regression models to analyze the drivers of CO2 emissions in the industry. The results show that the nonlinear effect of economic growth on CO2 emissions supports the Environmental Kuznets Curve (EKC) hypothesis. Energy structure has an inverted “U-shape” effect owing to massive coal consumption in the early stages and the optimization of energy structure in the later stage. The inverted “U-shaped” impact of industrialization may be due to the priority development of heavy industry in the early stages and the optimization of industrial structure in the later stages. The impact of urbanization also exhibits an inverted “U-shaped” pattern because of mass consumption of steel and cement products in the early stages and the advancement in clean energy technologies at the later stages. However, specific energy consumption has a positive “U-shaped” impact because of the difference in the speed of technological progress at different times. Thus, the differential effects of these indicators at different times should be taken into consideration when discussing reduction of CO2 emissions in China's manufacturing industry.

Abstract Under conditions of low funding for the production of “green energy” in Poland, it became necessary to search for other – cheaper sources of biomass and the development of more efficient technologies. The maize straw is waste material arising in the production of grain. Therefore currently has no wider application and the cost of acquisition is several times lower than in case of maize silage. This paper presents the results of research on biogas efficiency of the maize straw silage, the dynamics of the fermentation process and the decomposition time of biomass under the meso- and thermophilic conditions. Moreover, the exploitation costs of a biogas plant working on this substrate and maize silage have been compared. It has been proved that thermophilic fermentation is significantly shorter (17%) than mesophilic and permits to increase biogas production (8.6%) and methane content (9.3%). In turn, mesophilic fermentation has more stable pH changes in comparison with the thermophilic technology. However, it is related to inhibition of the propionic acid, which can be of great importance in case of continuous fermentation. On the basis of energetic calculations it was shown that the substitution of the maize silage with the maize straw silage allows for nearly three-fold costs reduction and thus increase of the biogas plant profitability.

Abstract Administrators and policymakers at regional, national and global level are well aware of the necessity and undeniable benefits of renewable energy for long-term sustainability. In this study, we developed a two-stage analytical methodology to assess the efficiency of energy sources (a combination of various energy sources, mostly based on renewable sources), and Turkey, a country with a variety of renewable energy potential because of its favorable geographic and climatic conditions, was used as an illustrative case. Specifically, in the first stage, we utilized a nonparametric method and a powerful benchmarking tool—Data Envelopment Analysis (DEA)—to analyze energy efficiencies for each province. In the second stage, we employed the Ordinary Least Square (OLS) regression and Tobit regression models to investigate the environmental factors affecting energy efficiency. And then, we used the Charnes-Cooper-Rhodes (CCR) DEA and Tobit regression combination to perform a validation of the findings. The tandem utilization of DEA, OLS, and Tobit regression models allowed us to overcome some of the shortcomings of these methods when they are utilized individually. The results revealed the factors that have direct and positive influence/effect on the efficiencies, which included gross domestic product per-capita, population size, and the amount of energy production from renewable energy sources. The findings also suggested that starting the investments at the less-efficient provinces result in a better overall nationwide technical efficiency. These results can potentially help decision makers to develop and manage energy investment strategies.