• Energy Research
• 11. Sustainability close
• 12. Responsible consumption close
• Applied Energy close

Abstract District heating (DH) enables the utilisation and distribution of heating from sources unfeasible for stand-alone applications and combined with cogeneration of heat and power (CHP), has been the cornerstone of Denmark’s realisation of a steady national primary energy supply over the last four decades. However, progressively more energy-efficient houses and a steadily improving heat pump (HP) performance for individual dwellings is straining the competitive advantage of the CHP–DH combination as DH grid losses are growing in relative terms due to decreasing heating demands of buildings and relatively high DH supply temperatures. A main driver for the DH water temperature is the requirements for domestic hot water (DHW) production. This article investigates two alternatives for DHW supply: (a) DH based on central HPs combined with a heat exchanger, and (b) a combination of DH based on central HPs and a small booster HP using DH water as low-temperature source for DHW production. The analyses are conducted using the energyPRO simulation model and are conducted with hourly varying factors; heating demands, DH grid losses, HP coefficient of performance (COP) and spot market prices in order to be able to analyse the relative performance of the two options and their performance over the year. Results are also compared to individual boilers and individual HPs. The results indicate that applying booster HPs enables the DH system to operate at substantially lower temperature levels, improving the COP of central DH HPs while simultaneously lowering DH grid losses significantly. Thus, DH performance is increased significantly. Additionally, performance for the DH HP with booster combination is considerably better than individual boiler or HP solutions.

Abstract The hybrid pneumatic power system (HPPS) proposed in this research replaces the battery’s electric-chemical energy with flow work and optimizes the management and utilization of the energy. This power system is able to keep the internal-combustion engine working at its optimal condition and turn its waste energy into effective mechanical energy and so enhance the thermal efficiency of the whole system. Using computer simulation software ITI-SIM, this study simulates the overall dynamic characteristics of the system in accordance with the regulated running-vehicle test-mode ECE47, and, with experimental verification and analysis, proves that this system can meet the requirements of the standard running-car mode. As for recycling the waste energy, the experimental results show that this design could offset the shortcomings of the low-density of pneumatic power and so effectively enhance the efficiency of the whole system.

Shale gas, due to its clean-burning and efficient nature, is becoming an increasingly promising alternative energy resource. It is commonly held that promoting shale gas development will gradually play a significant role in meeting the energy needs of economic and social development as well as reducing harm to the environment. Given the significant implications, many countries are pursuing shale gas opportunities. However, numerous concerns have been raised about the economics of shale gas development, as it is difficult to evaluate. Accurately evaluating the economic viability of shale gas development to reduce investment risks and increase investment opportunity is the key issue that needs to be urgently addressed. This paper presents a systematic review and examination of the technical and economic evaluation techniques for the development of shale gas to provide an overview of their current status. Over time, some progress has been made in existing technical–economic evaluation techniques. It is worth noting that these techniques need to be further improved to more precisely assess the economic feasibility of developing shale gas for assisting investment decisions effectively. For this reason, various potentially useful ideas and approaches are presented to propose some potential improvement in evaluation techniques for shale gas development, which may materialize in possible future trends.

Abstract A variety of novel, recyclable and reusable, construction materials has already been studied within literature during the past years, aiming at improving the overall energy efficiency ranking of the building envelope. However, several studies show that a delicate control of indoor climating elements can lead to a significant performance improvement by exploiting the building’s savings potential via smart adaptive HVAC regulation to exogenous uncertain disturbances (e.g. weather, occupancy). Building Optimization and Control (BOC) systems can be categorized into two different groups: centralized (requiring high data transmission rates at a central node from every corner of the overall system) and decentralized 1 (assuming an intercommunication among neighboring constituent systems). Moreover, both approaches can be further divided into two subcategories, respectively: model-assisted (usually introducing modeling oversimplifications) and model-free (typically presenting poor stability and very slow convergence rates). This paper presents the application of a novel, decentralized, agent-based , model-free BOC methodology (abbreviated as L4GPCAO) to a modern non-residential building (E.ON. Energy Research Center’s main building), equipped with controllable HVAC systems and renewable energy sources by utilizing the existing Building Management System (BES). The building testbed is located inside the RWTH Aachen University campus in Aachen, Germany. A combined rule criterion composed of the non-renewable energy consumption (NREC) and the thermal comfort index – aligned to international comfort standards – was adopted in all cases presented herein. Besides the limited availability of the specified building testbed, real-life experiments demonstrated operational effectiveness of the proposed approach in BOC applications with complex, emerging dynamics arising from the building’s occupancy and thermal characteristics. L4GPCAO outperformed the control strategy that was designed by the planers and system provider, in a conventional manner, requiring no more than five test days.

Abstract Urban planners, local authorities, and energy policymakers often develop strategic sustainable energy plans for the urban building stock in order to minimize overall energy consumption and emissions. Planning at such scales could be informed by building stock modeling using existing building data and Geographic Information System-based mapping. However, implementing these processes involves several issues, namely, data availability, data inconsistency, data scalability, data integration, geocoding, and data privacy. This research addresses the aforementioned information challenges by proposing a generalized integrated methodology that implements bottom-up, data-driven, and spatial modeling approaches for multi-scale Geographic Information System mapping of building energy modeling. This study uses the Irish building stock to map building energy performance at multiple scales. The generalized data-driven methodology uses approximately 650,000 Irish Energy Performance Certificates buildings data to predict more than 2 million buildings’ energy performance. In this case, the approach delivers a prediction accuracy of 88% using deep learning algorithms. These prediction results are then used for spatial modeling at multiple scales from the individual building level to a national level. Furthermore, these maps are coupled with available spatial resources (social, economic, or environmental data) for energy planning, analysis, and support decision-making. The modeling results identify clusters of buildings that have a significant potential for energy savings within any specific region. Geographic Information System-based modeling aids stakeholders in identifying priority areas for implementing energy efficiency measures. Furthermore, the stakeholders could target local communities for retrofit campaigns, which would enhance the implementation of sustainable energy policy decisions.

Over the past three decades, Swedish energy policy has evolved in three major stages—oil reduction, phase-out of nuclear energy, renewable energy—each with a different focus. Since 1977, Swedish law has required municipalities to develop an energy plan that addresses the supply, distribution, and use of energy. Whether such plans have contributed to the development of local energy-systems has been a subject for debate. This paper is based on a study of 12 municipal energy-plans that attempted to control and develop local energy-systems in southern Sweden. The analysis examines how municipalities promote oil reduction, efficient energy use, and the use of renewable energy. The plans varied in planning processes, contents, and level of ambition. The results of the study show that the contents of the plans follow the national energy-policies with respect to reduction of oil use, improved energy efficiency, and increased use of renewable energy.

Abstract In the past, most studies considered solar as a drawback to road pavement, especially the asphalt pavement. Not only its radiation causes the asphalt aging, simultaneously with high temperature, asphalt pavement contributes to the urban heat island (UHI) effect. In recent, as the world becomes more supportive towards implementing sustainable energy as the alternatives to the scarcity of non-renewable resources, utilizing the abundant solar radiation as the main source of energy has gradually attracted attention from both industries and academia with its potentials, including solar application on roads. Nevertheless, more researches have focused on the potential energy collection with less consideration to simultaneously overcome the side effects of abundant solar radiation on its lifecycle. This study found the necessity to review a comprehensive correlation between solar radiation and asphalt pavement from both positive and negative effects. The negative effects included asphalt aging and its effects on surroundings i.e. UHI effect. Meanwhile, the positive effects included exhaust purification and solar energy conversion into other forms of energy that can be used by humans using pavement solar heat collection for winter snowmelt, thermoelectric technology and photoelectric technology to convert solar energy into electrical energy. The cases in various application scenarios were analysed and summarized and the existing problems in the current research were proposed in this paper. Also, the reflection on the transformation of road design concept from “avoiding harm” to “seeking profit” was included. Finally, a new concept of “solar-road harmonious symbiosis” for future road application was proposed based on a comprehensive review of previous published works. It is also the new suggestion to scholars on the treatment of solar diseases on roads to prolong its symbiosis functions.

Abstract Motivated by a real-world case, this paper deals with uncertainty issues in the resilient and sustainable electricity supply chain network design. Uncertainty is always found in electricity demand prediction and perfect foresight is not possible. The resilience of electricity networks in face of uncertainty can prevent catastrophic impacts. Besides, due to the growing concerns about social impacts, considering social measures along with the other measures is becoming critical when analyzing the network costs. In this paper, a multi-objective optimization model is developed, which consists of the total cost in the first objective, resiliency measures in the second objective, and some aspects of corporate social responsibility in the third objective. The resiliency measures minimize de-resiliency, including successive establishment, distributed generators inadequacy, congestion through electrical lines, and energy dissatisfaction level. A novel robust approach is also proposed to deal with the uncertainty of electricity demand based on the light robust programming and possibilistic theory in the fuzzy logic. By investigating a real case in Iran, the contributions of the considered measures, and the effects of uncertainty are analyzed. The analyses reveal that by applying the proposed model the decision-makers can enhance corporate social responsibility and resiliency by 50% and 20%, respectively, although it increases the total cost by 50%. Moreover, the results of applying the proposed fuzzy-robust approach show that how the decision-makers can effectively allocate the uncertainty budget and protection level to attain more robust solutions in terms of standard deviation and mean value of the total cost.