•Energy flow in energy harvesting systems applied in land transportation is presented.•Different applications for road, track and vehicle are introduced and compared.•The research gaps and technical ...difficulties that remain unresolved are discussed.•The work on renewable land transportation is helpful for future research.
The development of land transportation has effectively contributed to countries’ economic and social development. Roads, rails and vehicles have come into widespread use in transporting things from one location to another on land. However, much energy is dissipated in traditional land transportation, and this energy is worthy of being recovered. Many researchers in recent decades have presented different types of energy harvesting systems to harness this dissipated energy. Regenerative energy harvesting systems can convert dissipated energy into electricity for different applications. This paper is a comprehensive review of energy harvesting technologies for different applications in the land transportation. First, the commonly used energy harvesting technologies in land transportation are summarized. Second, different energy harvesting systems are presented in terms of designs, simulations, and experiments. Third, a common analysis of energy harvesting technologies is conducted to calculate and simulate the performance of these systems. Also, a comparison of the presented energy harvesting systems is conducted in various ways. Then different applications and energy utilizations of the energy harvesting systems are summarized. Moreover, research gaps and technical difficulties that remain unresolved are discussed, and some recommendations are made, which aim to be helpful for further research.
Oxy-coal combustion is one of the technical solutions for mitigating CO₂ in thermal power plants. For designing a technically viable and economically effective CO₂ capture process, effects by coals ...and configurations of flue gas cleaning steps are of importance. In this paper, characterization of the flue gas recycle (FGR) is conducted for an oxy-coal combustion process. Different configurations of FGR as well as cleaning units including electrostatic precipitators (ESP), flue gas desulfurization (FGD), selective catalytic reduction (SCR) deNOₓ and flue gas condensation (FGC) are studied for the oxy-coal combustion process. In addition, other important parameters such as FGR rate and FGR ratio, flue gas compositions, and load of flue gas cleaning units are analyzed based on coal properties and plant operational conditions.
•A comprehensive analysis framework for roof-mounted solar PV systems is developed.•The estimated roof area for Västerås municipality is 5.74 km2.•Different scenarios are considered for the potential ...installation of PV systems.•The potential capacity is 727-956 MWp and annual yield is 626-801 GWh for Västerås.•504 km2 usable roof area and 65-84 GWp installed capacity are estimated for Sweden.
Solar photovoltaic energy, driven mostly by the residential and commercial market segments, has been growing a lot in recent years in Sweden. In response to the commitment towards sustainability goals, this paper explores the potential of roof-mounted solar photovoltaic projects. This paper focuses on: roof area estimation, potential installed capacity, and potential electricity generation, at the single municipal scale and at the national scale. The following categories of different building types have been investigated: residential buildings, industrial buildings, buildings of social function, buildings of business function, buildings of economic/agricultural function, buildings of complementary function, and buildings of other unknown functions. The analysis starts from Västerås, a typical Swedish municipality and ranking seventh among the largest cities in Sweden. An estimate of 5.74 km2 available roof area potential is calculated, by considering factors such as building purposes, roof orientations, shadows and obstacles. The total potential installed capacity is calculated, assuming the installation of commercial photovoltaic modules, and design parameters for flat roofs such as inter-row distances and tilt angles. With the inputs of meteorological parameters and geographical information, the potential yearly electricity generation is calculated. The results reveal 727, 848, and 956 MWp potential installed capacity and 626, 720, and 801 GWh annual electricity production for Västerås on pitched roofs and flat roofs with three scenarios, respectively. The extrapolation of the methodology to the entire of Sweden yields a total of 504 km2 usable roof area and 65, 75, and 84 GWp installed capacity. Finally, we reveal a new understanding of usable roof area distribution and of potential installed capacity of roof-mounted solar photovoltaic systems, which can largely help evaluate subsidy scale and solar energy policy formulation in Sweden.
•Property impacts on CCS processes have been reviewed.•Properties were ranked and priority of properties in model development was analyzed.•Relevant properties in the design and operation of CCS ...processes have been identified.•The studied CCS processes include CO2 capture, conditioning, transport and storage.
The knowledge of thermodynamic and transport properties of CO2-mixtures is important for designing and operating different processes in carbon capture and storage systems. A literature survey was conducted to review the impact of uncertainty in thermos-physical properties on the design and operation of components and processes involved in CO2 capture, conditioning, transport and storage. According to the existing studies on property impacts, liquid phase viscosity and diffusivity as well as gas phase diffusivity significantly impact the process simulation and absorber design for chemical absorption. Moreover, the phase equilibrium is important for regenerating energy estimation. For CO2 compression and pumping processes, thermos-physical properties have more obvious impacts on pumps than on compressors. Heat capacity, density, enthalpy and entropy are the most important properties in the pumping process, whereas the compression process is more sensitive to heat capacity and compressibility. In the condensation and liquefaction process, the impacts of density, enthalpy and entropy are low on heat exchangers. For the transport process, existing studies mainly focused on property impacts on the performance of pipeline steady flow processes. Among the properties, density and heat capacity are most important. In the storage process, density and viscosity have received the most attention in property impact studies and were regarded as the most important properties in terms of storage capacity and enhanced oil recovery rate. However, for physical absorption, physical adsorption and membrane separation, there has been a knowledge gap about the property impact. In addition, due to the lack of experimental data and process complexity, little information is available about the influence of liquid phase properties on the design of the absorber and desorber for chemical absorption process. In the CO2 conditioning process, knowledge of the impacts of properties beyond density and enthalpy is insufficient. In the transport process, greater attention should focus on property impacts on transient transport processes and ship transport systems. In the storage process, additional research is required on the dispersion process in enhanced oil recovery and the dissolution process in ocean and saline aquifer storage.
Machine learning has been widely adopted for improving building energy efficiency and flexibility in the past decade owing to the ever-increasing availability of massive building operational data. ...However, it is challenging for end-users to understand and trust machine learning models because of their black-box nature. To this end, the interpretability of machine learning models has attracted increasing attention in recent studies because it helps users understand the decisions made by these models. This article reviews previous studies that adopted interpretable machine learning techniques for building energy management to analyze how model interpretability is improved. First, the studies are categorized according to the application stages of interpretable machine learning techniques: ante-hoc and post-hoc approaches. Then, the studies are analyzed in detail according to specific techniques with critical comparisons. Through the review, we find that the broad application of interpretable machine learning in building energy management faces the following significant challenges: (1) different terminologies are used to describe model interpretability which could cause confusion, (2) performance of interpretable ML in different tasks is difficult to compare, and (3) current prevalent techniques such as SHAP and LIME can only provide limited interpretability. Finally, we discuss the future R&D needs for improving the interpretability of black-box models that could be significant to accelerate the application of machine learning for building energy management.
A strategy that informs on countries' potential losses due to lack of climate action may facilitate global climate governance. Here, we quantify a distribution of mitigation effort whereby each ...country is economically better off than under current climate pledges. This effort-sharing optimizing approach applied to a 1.5 °C and 2 °C global warming threshold suggests self-preservation emissions trajectories to inform NDCs enhancement and long-term strategies. Results show that following the current emissions reduction efforts, the whole world would experience a washout of benefit, amounting to almost 126.68-616.12 trillion dollars until 2100 compared to 1.5 °C or well below 2 °C commensurate action. If countries are even unable to implement their current NDCs, the whole world would lose more benefit, almost 149.78-791.98 trillion dollars until 2100. On the contrary, all countries will be able to have a significant positive cumulative net income before 2100 if they follow the self-preservation strategy.
In general, the post-combustion capture of CO2 is costly; however, swing adsorption processes can reduce these costs under certain conditions. This review highlights the issues related to ...adsorption-based processes for the capture of CO2 from flue gas. In particular, we consider studies that investigate CO2 adsorbents for vacuum swing or temperature swing adsorption processes. Zeolites, carbon molecular sieves, metal organic frameworks, microporous polymers, and amine-modified sorbents are relevant for such processes. The large-volume gas flows in the gas flue stacks of power plants limit the possibilities of using regular swing adsorption processes, whose cycles are relatively slow. The structuring of CO2 adsorbents is crucial for the rapid swing cycles needed to capture CO2 at large point sources. We review the literature on such structured CO2 adsorbents. Impurities may impact the function of the sorbents, and could affect the overall thermodynamics of power plants, when combined with carbon capture and storage. The heat integration of the adsorption-driven processes with the power plant is crucial in ensuring the economy of the capture of CO2, and impacts the design of both the adsorbents and the processes. The development of adsorbents with high capacity, high selectivity, rapid uptake, easy recycling, and suitable thermal and mechanical properties is a challenging task. These tasks call for interdisciplinary studies addressing this delicate optimization process, including integration with the overall thermodynamics of power plants.
•Assessment of the criteria for a range of low-carbon city (LCC) indicators at global level.•Establishment of an LCC indicator system covering the holistic perspectives of sustainable ...development.•The indicator system benchmark values for the standardization of cities.
Many cities are pursuing the low-carbon practices to reduce CO2 and other environmental emissions. However, it is still unclear which aspects a low-carbon city (LCC) covers and how to quantify and certify its low carbon level. In this paper, an indicator framework for the evaluation of LCC was established from the perspectives of Economic, Energy pattern, Social and Living, Carbon and Environment, Urban mobility, Solid waste, and Water. A comprehensive evaluation method was employed for LCC ranking by using the entropy weighting factor method. The benchmark values for LCC certification were also identified. The framework was applied to 10 global cities to rank their low-carbon levels. The comparison of cities at different levels of economic, social, and environmental development enhances the holistic of the study. The results showed that Stockholm, Vancouver, and Sydney ranked higher than the benchmark value, indicating these cities achieved a high level of low-carbon development. São Paulo, London, and Mexico City are still in the slow transition towards LCC. Beijing and New York each has much lower LCC level than the benchmark value due to the poor environmental performance and infrastructure supports caused by intensive human activities. The proposed indicator system serves as a guideline for the standardization of LCC and further identifies the key aspects of low-carbon management for different cities.
•Battery sizing and rule-based operation are achieved concurrently.•Hybrid operation strategy that combines different strategies is proposed.•Three operation strategies are compared through ...multi-objective optimization.•High Net Present Value and Self Sufficiency Ratio are achieved at the same time.
The optimal components design for grid-connected photovoltaic-battery systems should be determined with consideration of system operation. This study proposes a method to simultaneously optimize the battery capacity and rule-based operation strategy. The investigated photovoltaic-battery system is modeled using single diode photovoltaic model and Improved Shepherd battery model. Three rule-based operation strategies—including the conventional operation strategy, the dynamic price load shifting strategy, and the hybrid operation strategy—are designed and evaluated. The rule-based operation strategies introduce different operation parameters to run the system operation. multi-objective Genetic Algorithm is employed to optimize the decisional variables, including battery capacity and operation parameters, towards maximizing the system’s Self Sufficiency Ratio and Net Present Value. The results indicate that employing battery with the conventional operation strategy is not profitable, although it increases Self Sufficiency Ratio. The dynamic price load shifting strategy has similar performance with the conventional operation strategy because the electricity price variation is not large enough. The proposed hybrid operation strategy outperforms other investigated strategies. When the battery capacity is lower than 72kWh, Self Sufficiency Ratio and Net Present Value increase simultaneously with the battery capacity.
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