To tackle the crisis of global warming, it is imperative to control and mitigate the atmospheric carbon dioxide level. Photocatalytic reduction of carbon dioxide into solar fuels furnishes a gratifying solution to utilize and reduce carbon dioxide emission and simultaneously generate renewable energy to sustain the societies. So far, titanium oxide-based semiconductors have been the most prevalently adopted catalysts in carbon dioxide photoreduction. This mini-review provides a general summary of the recent progresses in titanium oxide-catalyzed photocatalytic reduction of carbon dioxide. It first illustrates the use of structural engineering as a strategy to adjust and improve the catalytic performances. Then, it describes the introduction of one/two exogenous elements to modify the photocatalytic activity and/or selectivity. Lastly, it discusses multi-component hybrid titanium oxide composites.
Metal-organic frameworks (MOFs) have attracted much attention because of their large surface areas, tunable structures, and potential applications in many areas. In recent years, MOFs have shown much promise in CO2 photoreduction. This review summarized recent research progresses in MOF-based photocatalysts for photocatalytic reduction of CO2. Besides, it discussed strategies in rational design of MOF-based photocatalysts (functionalized pristine MOFs, MOF-photosensitizer, MOF-semiconductor, MOF-metal, and MOF-carbon materials composites) with enhanced performance on CO2 reduction. Moreover, it explored challenges and outlook on using MOF-based photocatalysts for CO2 reduction.
In an era of graphene-based nanomaterials as the most widely studied two-dimensional (2D) materials for enhanced performance of devices and systems in solar energy conversion applications, molybdenum disulfide (MoS2) stands out as a promising alternative 2D material with excellent properties. This review first examined various methods for MoS2 synthesis. It, then, summarized the unique structure and properties of MoS2 nanosheets. Finally, it presented the latest advances in the use of MoS2 nanosheets for important solar energy applications, including solar thermal water purification, photocatalytic process, and photoelectrocatalytic process.
The present paper has disseminated the design approach, project implementation, and economics of a nano-grid system. The deployment of the system is envisioned to acculturate the renewable technology into Indian society by field-on-laboratory demonstration (FOLD) and “bridge the gaps between research, development, and implementation.” The system consists of a solar photovoltaic (PV) (2.4 kWp), a wind turbine (3.2 kWp), and a battery bank (400 Ah). Initially, a prefeasibility study is conducted using the well-established HOMER (hybrid optimization model for electric renewable) software developed by the National Renewable Energy Laboratory (NREL), USA. The feasibility study indicates that the optimal capacity for the nano-grid system consists of a 2.16 kWp solar PV, a 3 kWp wind turbine, a 1.44 kW inverter, and a 24 kWh battery bank. The total net present cost (TNPC) and cost of energy (COE) of the system are US$20789.85 and US$0.673/kWh, respectively. However, the hybrid system consisting of a 2.4 kWp of solar PV, a 3.2 kWp of wind turbine, a 3 kVA of inverter, and a 400 Ah of battery bank has been installed due to unavailability of system components of desired values and to enhance the reliability of the system. The TNPC and COE of the system installed are found to be US$20073.63 and US$0.635/kWh, respectively and both costs are largely influenced by battery cost. Besides, this paper has illustrated the installation details of each component as well as of the system. Moreover, it has discussed the detailed cost breakup of the system. Furthermore, the performance of the system has been investigated and validated with the simulation results. It is observed that the power generated from the PV system is quite significant and is almost uniform over the year. Contrary to this, a trivial wind velocity prevails over the year apart from the month of April, May, and June, so does the power yield. This research demonstration provides a pathway for future planning of scaled-up hybrid energy systems or microgrid in this region of India or regions of similar topography.
In consideration of geometric parameters, several researches have already optimized the thermal efficiency of the cylindrical cavity receiver. However, most of the optimal results have been achieved at a fixed solar radiation. At different direct normal irradiance (DNI), any single optimal result may not be suitable enough for different regions over the world. This study constructed a 3-D numerical model of cylindrical cavity receiver with DNI variation. In the model of a cylindrical cavity receiver containing a helical pipe, the heat losses of the cavity and heat transfer of working medium were also taken into account. The simulation results show that for a particular DNI in the range of 400 W/m2 to 800 W/m2, there exists a best design for achieving a highest thermal efficiency of the cavity receiver. Besides, for a receiver in constant geometric parameters, the total heat losses increases dramatically with the DNI increasing in that range, as well as the temperature of the working medium. The thermal efficiency presented a different variation tendency with the heat losses, which is 2.45% as a minimum decline. In summary, this paper proposed an optimization method in the form of a bunch of fitting curves which could be applied to receiver design in different DNI regions, with comparatively appropriate thermal performances.
This paper proposes a powertrain controller for a solar photovoltaic battery powered hybrid electric vehicle (HEV). The main objective of the proposed controller is to ensure better battery management, load regulation, and maximum power extraction whenever possible from the photovoltaic panels. The powertrain controller consists of two levels of controllers named lower level controllers and a high-level control algorithm. The lower level controllers are designed to perform individual tasks such as maximum power point tracking, battery charging, and load regulation. The perturb and observe based maximum power point tracking algorithm is used for extracting maximum power from solar photovoltaic panels while the battery charging controller is designed using a PI controller. A high-level control algorithm is then designed to switch between the lower level controllers based on different operating conditions such as high state of charge, low state of charge, maximum battery current, and heavy load by respecting the constraints formulated. The developed algorithm is evaluated using theoretical simulation and experimental studies. The simulation and experimental results are presented to validate the proposed technique.
Coal-fired power industry has always been the major power source in China. As coal-fired power industry consumes around a half of China’s coal production, it is always thought to be a big air pollutant emission source. As more and more strict legislations in coal-fired power industry have been issued by the government, the emission performance in coal-fired power industry has been drastically reduced recently. Based on a brief review of the development of emission control in China’s coal-fired power industry, the affecting mechanism among the development of installed capacities of emission control device, pollutant emission, and emission performances in coal-fired power industry is studied. According to a systematic study on the development of emissions of classified categories, the role of coal-fired power industry as a pollutant source is reevaluated. It is found that, coal-fired power industry has contributed the most to China’s emission reduction, and the barycenter of air pollutant emission has been transformed to other high energy consumption industries, like heat, iron/steel, and cement. Then some development strategies are suggested, such as maintaining the current emission standard in coal-fired power industry; expending the coal-fired power emission standards to categories of heat generation and supply, nonmetallic mineral production and ferrous metals smelting and processing; and controlling other heavy metal by consulting the method of Hg control.
Sweeting natural gas processes are mainly focused on removing carbon dioxide (CO2) and hydrogen sulfide (H2S). The high-energy requirements and operational limitations make amine absorption process sensitive to any change in conditions. This paper presented a steady-state simulation using Hysys to reasonably predict removal amounts of carbon dioxide and hydrogen sulfide from natural gas with the diethanolamine (DEA) solvent. The product specifications are taken from the real plant (GASCO’S Habshan) which uses the methyldiethanolamine (MDEA) solvent, while this simulation uses DEA under the same operation conditions. First, the simulation validation has been checked with the data of the real plant. The results show accurate prediction for CO2 slippage and accepted agreement for H2S content compared with the data of the plant. A parametric analysis has been performed to test all possible parameters that affect the performance of the acid gases removal plant. The effects of operational parameters are examined in terms of carbon dioxide and hydrogen sulfide contents in clean gas and reboiler duty.
Polymer electrolyte membrane (PEM) fuel cell is the most promising among the various types of fuel cells. Though it has found its applications in numerous fields, the cost and durability are key barriers impeding the commercialization of PEM fuel cell stack. The crucial and expensive component involved in it is the gas diffusion electrode (GDE) and its degradation, which limits the performance and life of the fuel cell stack. A critical analysis and comprehensive understanding of the structural and functional properties of various materials involved in the GDE can help us to address the related durability and cost issues. This paper reviews the key GDE components, and in specific, the root causes influencing the durability. It also envisages the role of novel materials and provides a critical recommendation to improve the GDE durability.
Commercial buildings account for significant portions of the total building energy in South Korea and thus a variety of research on the boiler operation related to heating energy in office buildings has been carried out thus far. However, most of the researches have been conducted on the boiler itself, i.e., the part load ratio characteristics and the corresponding gas energy consumption patterns are not analyzed in the existing studies. In this study, the part load ratio and the operating characteristics of gas boiler have been analyzed within an office building equipped with the conventional variable air volume system. In addition, the gas consumption among different boiler staging schemes has been comparatively analyzed. As a result, significant portions of total operating hours, heating load and energy consumption has been found to be in a part load ratio range of 0 through 40% and thus energy consumption is significantly affected by boiler efficiency at low part load conditions. This suggests that boiler operation at the part load is an important factor in commercial buildings. In addition, utilizing sequential boiler staging scheme can save a gas usage of about 7%. For annual heating energy saving, applying the sequential control boiler with a 3:7 proportion staging is considered to be the optimal control algorithm for maximum efficiency of boilers.
A series of breakthroughs have been made in the understanding, evaluation, and exploration of shale gas from discovery, environmental protection to efficient exploration in the discovering of Fuling Gas Field. By revealing the positive correlation between organic carbon content and siliceous mineral content of shale deposited in deep shelf, dynamic preservation mechanism of “early retention and late deformation,” it is clarified that the shales deposited in deep shelf are the most favorable for shale gas generation, storage and fracturing. The preserving conditions determine the levels of shale gas accumulation, thus the evaluation concept of taking the quality of the shale as the base and the preserving conditions as key is proposed, the evaluation system for strategic selection of favorable zones is established for marine shale gas exploration in Southern China. Moreover, the “sweet point” seismic forecasting technologies for marine shale gas, the “six properties” logging technologies for evaluating shale gas layers, the technologies for quick and efficient drilling of horizontal well groups, and the fracturing technologies for composite fractures for horizontal wells are invented. The paper discussed the exploration prospect of shale gas in the shales of Wufeng-Longmaxi Formation in great depth in Sichuan Basin, shale gas exploration in the outer region of the south, and continental shale gas exploration in China.
It is difficult to predict the ignition delay times for fuels with the two-stage ignition tendency because of the existence of the nonlinear negative temperature coefficient (NTC) phenomenon at low temperature regimes. In this paper, the random sampling-high dimensional model representation (RS-HDMR) methods were employed to predict the ignition delay times of n-heptane/air mixtures, which exhibits the NTC phenomenon, over a range of initial conditions. A detailed n-heptane chemical mechanism was used to calculate the fuel ignition delay times in the adiabatic constant-pressure system, and two HDMR correlations, the global correlation and the stepwise correlations, were then constructed. Besides, the ignition delay times predicted by both types of correlations were validated against those calculated using the detailed chemical mechanism. The results showed that both correlations had a satisfactory prediction accuracy in general for the ignition delay times of the n-heptane/air mixtures and the stepwise correlations exhibited a better performance than the global correlation in each subdomain. Therefore, it is concluded that HDMR correlations are capable of predicting the ignition delay times for fuels with two-stage ignition behaviors at low-to-intermediate temperature conditions.
This paper deals with the errors of electric energy metering devices as a result of distortions in the shape of the curves of voltage and current load. It is shown and proved that the errors in energy measurements depend on the design and the algorithms used in electricity meters. There are three main types of metering devises having different principles: inductive (electro-mechanical), electronic static, and digital electronic (microprocessor). Each of these types has its measuring features. Some devices take into account all the harmonic distortions and the constant component which occur in the network while others measure the power and energy values of the fundamental harmonic only. Such traits lead to the discrepancies in the readings of commercial electric energy meters of different types. Hence, the violations in the measurement system unity occur, and a significant error can be observed in the balance of transmitted/consumed electric energy.
The potential to save energy in existing consumer electrical appliances is very high. One of the ways to achieve energy saving and improve energy use awareness is to recognize the energy consumption of individual electrical appliances. To recognize the energy consumption of consumer electrical appliances, the load disaggregation methodology is utilized. Non-intrusive appliance load monitoring (NIALM) is a load disaggregation methodology that disaggregates the sum of power consumption in a single point into the power consumption of individual electrical appliances. In this study, load disaggregation is performed through voltage and current waveform, known as the V-I trajectory. The classification algorithm performs cropping and image pyramid reduction of the V-I trajectory plot template images before utilizing the principal component analysis (PCA) and the k-nearest neighbor (k-NN) algorithm. The novelty of this paper is to establish a systematic approach of load disaggregation through V-I trajectory-based load signature images by utilizing a multi-stage classification algorithm methodology. The contribution of this paper is in utilizing the “k-value,” the number of closest data points to the nearest neighbor, in the k-NN algorithm to be effective in classification of electrical appliances. The results of the multi-stage classification algorithm implementation have been discussed and the idea on future work has also been proposed.
Owing to the energy demands and global warming issue, employing more effective power cycles has become a responsibility. This paper presents a thermodynamical study of an irreversible Brayton cycle with the aim of optimizing the performance of the Brayton cycle. Moreover, four different schemes in the process of multi-objective optimization were suggested, and the outcomes of each scheme are assessed separately. The power output, the concepts of entropy generation, the energy, the exergy output, and the exergy efficiencies for the irreversible Brayton cycle are considered in the analysis. In the first scheme, in order to maximize the exergy output, the ecological function and the ecological coefficient of performance, a multi-objective optimization algorithm (MOEA) is used. In the second scheme, three objective functions including the exergetic performance criteria, the ecological coefficient of performance, and the ecological function are maximized at the same time by employing MOEA. In the third scenario, in order to maximize the exergy output, the exergetic performance criteria and the ecological coefficient of performance, a MOEA is performed. In the last scheme, three objective functions containing the exergetic performance criteria, the ecological coefficient of performance, and the exergy-based ecological function are maximized at the same time by employing multi-objective optimization algorithms. All the strategies are implemented via multi-objective evolutionary algorithms based on the NSGAII method. Finally, to govern the final outcome in each scheme, three well-known decision makers were employed.
The oil-return system plays an important role in the variable refrigerant flow (VRF) systems because it ensures the reliable operation of the VRF systems. The oil-gas separator is the most essential component of the oil-return system, and the separation efficiency of the separator directly influences the performance of the VRF systems. Therefore, in this paper, a test rig was built to measure the oil discharge ratio of the compressor and the separation efficiency of the oil-gas separator. A sound velocity transducer was used to measure the oil mass concentration instantaneously, because the sound velocity was changed with the mass ratio of oil to refrigerant. The separation efficiency of the separator could be obtained by comparing the mass fraction of oil to refrigerant before and after the separator was connected to the system.