• Energy Research
• 11. Sustainability close
• Applied Energy close

Abstract Optimizing energy structure to reduce carbon intensity is an effective way to build the low-carbon city development model. To assess the contribution potential of energy structure optimization in order to achieve the carbon intensity target in Hangzhou City, the component data prediction, scenario prediction, GMI (1, 1) model and other multidisciplinary approaches were adopted to predict the carbon intensity trends in the above said City from 2014 to 2020. This contribution potential is evaluated based on 9 kinds of combined scenarios. The results show that: 1. Under the same economic growth rate, with the increase in energy structure adjustment range, the carbon intensity “decline range” becomes larger, and the higher is the “contribution potential” of energy structure optimization to achieve the carbon intensity target. 2. Within the same range of energy structure optimization, the economic growth rate is lower, the carbon intensity “decline range” is smaller, and the “contribution potential” of energy structure optimization is higher for the same carbon intensity objective. By optimizing energy structure and industrial structures adjustment, the technology upgrading for carbon emissions and the scientific and technological level of the systematic industrial policies are more conducive to supporting the realization of low-carbon city.

Abstract Around 43% of the cumulative CO2 emissions from the power sector between 2012 and 2050 could be mitigated through implementation of carbon capture and storage, and utilisation of renewable energy sources. Energy storage technologies can increase the efficiency of energy utilisation and thus should be widely deployed along with low-emission technologies. This study evaluates the techno-economic performance of cryogenic O2 storage implemented in an oxy-combustion coal-fired power plant as a means of energy storage. Such system was found to have high energy density and specific energy that compare favourably with other energy storage technologies. The average daily efficiency penalty of the analysed system was 12.3–12.5%HHV points, which is higher than the value for the oxy-combustion coal-fired power plant without energy storage (11.2%HHV points). Yet, investment associated with cryogenic O2 storage has marginal effect on the specific capital cost, and thus the levelised cost of electricity and cost of CO2 avoided. Therefore, the benefits of energy storage can be incorporated into oxy-combustion coal-fired power plants at marginal capital investment. Importantly, implementation of cryogenic O2 storage was found to increase the daily profit by 3.8–4.1%. Such performance would result in higher daily profit from oxy-combustion compared to an air-combustion system if the carbon tax is higher than 29.1–29.2 €/tCO2. Finally, utilisation of renewable energy sources for cryogenic O2 production can reduce the daily efficiency penalty by 4.7%HHV points and increase the daily profit by 11.6%. For this reason, a synergy between fossil fuel electricity generation and renewable energy sources via CO2 capture integrated with energy storage needs to be commercially established.

Abstract Industry is frequently highlighted as the world’s largest energy-using end-use sector. More specifically, the demand for heat drives much of the demand for energy and fossil fuels in the industrial sector. We conduct a top-down analysis to characterize historical energy and fossil fuel use in 14 top-GHG-emitting industries in the United States, their heat demand requirements, and the potential to substitute heat from geothermal, solar thermal (including concentrating technologies), and small modular nuclear reactors to meet these needs while reducing fossil-fuel use and greenhouse gas (GHG) emissions. We base this analysis on publicly-available facility-level GHG emissions and fuel-combustion data, in addition to assumed requirements for process temperature, to demonstrate the potential value to industry energy analysts of the U.S. Environmental Protection Agency’s Greenhouse Gas Reporting Program data. We estimate on a county level that the adoption of these alternative heat sources could have reduced 2015 fossil-fuel use by approximately 31% and combustion GHG emissions by approximately 24%. The most extensive substitution opportunities are in the ethyl alcohol manufacturing and wet corn-milling industries; petroleum refining represents the largest absolute emissions mitigation potential. This initial top-down analysis of substitution potential does not consider more detailed technical factors, including resource availability that will influence the actual deployment of alternative energy technologies. The analysis also does not consider the economic or market factors, including the expected cost to build and operate these generators. We do assume process byproducts that are extensively used for combustion fuels would not be good candidates for substitution for alternative energy generators. Based on these caveats, our analysis could be considered a top-range estimate for this mix of heat generators and industry heat demands. Any subsequent analysis of these alternate energy sources should increase the level of technical, economic, and policy detail.

Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs.

Abstract Even with the automotive technological evolution steadily improving energy efficiency, the transportation sector continues to account for more than one-fifth of greenhouse gas emissions (GHG). The official fuel consumption information has presented divergences in relation to the values found in real driving. Due to this variation, the effectiveness of technologies for the improvement of energy efficiency has been questioned. Aiming to verify these divergences, the aim of this study was to evaluate the relationship between embedded technologies intended to reduce fuel consumption and the official data on energy consumption. For the development of this method, the official on energy consumption of the light vehicles sold in Brazil were used. The innovative method developed in this study allowed the evaluation of consumption without the influence of vehicle weight, in a way to identify the best performing technologies. As a result, it was identified that technologies, such as the direct fuel injection (DFI) and electric power steering (EPS), presented positive correlation with fuel economy for all vehicle loads. The 3-cylinder engines showed favourable performance in vehicles up to 1200 kg, and 2.0-litre 4-cylinder engines had the best correlation coefficient of the evaluated fleet, with the best performance in models that were up to two tons. The boosted engines, with turbocharger or compressor, performed favourably across all vehicle sizes. Variable Valve Timing (VVT) also showed superiority in efficiency across all weight ranges, regardless of the number of valves per cylinder. The benefits of manual transmissions, with five and six speeds, stood out in vehicles up to 1200 kg and in the ones near two tons. The method used in this work demonstrated consistency by comparing fuel economy in other research. This study contributes to the activities of researchers, legislators, suppliers and vehicle manufacturers in the identification of the most recommended technologies for each vehicle size.

Abstract The quantitative tools and methods that have been developed to identify and cultivate industrial symbiotic exchanges in existing industrial parks to minimize overall energy and material consumption are reviewed. The issues relevant to adapting an existing park differs from those associated with constructing a new park using eco-industrial principles. Published literature was surveyed for methodologies which identify and establish viable inter-company exchanges for water, heat, power and materials. Studies which address issues associated with infrastructure alterations are specifically highlighted, as well as methods to quantify and manipulate any potential financial and/or ecological benefits gained by adopting proposed eco-industrial measures. Additional topics, such as network analysis, company motivation, confidentiality issues and introduction of new industries or facilities are included. This review surveys current quantitative methodologies that can be applied to the process of adapting established industrial park networks into eco-industrial park systems and case studies which are pertinent to this type of adaptation.

Abstract Increasing and projected shortages in non-renewable energy sources have directed attention toward the potential for using regenerated energy from road traffic. There are currently three primary techniques for harvesting energy from roadways—piezoelectricity, thermoelectricity and photoelectricity—although, to date very few studies have focussed on the potential for integrating two or more of these, with most examining the application and optimisation of single-mode harvesting. To address this gap, this paper reviews and analyses the body of past research on road energy harvesting with the goal of developing a ‘dynamic-heat-light division recommendation’ based on the literature. From this research, a new concept of ‘e-Roads’ is proposed and defined in detail. If full use can be made of roadways as e-Roads under the division recommendation made in this paper, these structures have the potential to serve as one of the largest sources of energy in the near future. In this manner, this study serves as a reference for road construction and road network planning as well as a source of ideas for the development of intelligent traffic systems.

Abstract The international heat pump trade transports equipment and new energy technology to urban renewable energy systems around the world. However, this trade is unstable because of technology transfer, the ever-changing economic environment and policies. Thus, to quantitatively explore the stability of the international heat pump trade, three stability indices are designed to reflect changes in trade volume and relations. Then, the stability of international heat pump pattern is analyzed in three aspects, global, communities and countries. We found that (1) The global heat pump trade is relatively stable, which offers big opportunities for countries to develop new technology. Traditional energy trade and trade in new energies technologies like photovoltaic have influence on the stability of heat pump trade. (2) The European community is more stable than the East Asian-North community. The urgent mandate for energy savings and technical progress have made the East Asian-North American community the market with the greatest potential for the global heat pump trade. The US plays an important role in the East Asian-North American market. Thus, when countries like the US change trade policies, it might be a market signal for other countries that they should take measures against the potential shocks. (3) It is essential to maintain stable trade relationships with partners. Greenland, Canada and Mexico are the three most stable countries. Finally, the stability indices and network modeling could be introduced to study other international energy trade patterns.