Energy-saving Method Research Articles

Improvement of Traditional Energy-Saving Cold Alley Spaces: Case Study of Shixiangyuan Garden Renovation and Expansion Project in Guangzhou

Traditional cold alleys have the ability to adapt to hot climates with cooling and insulation, which is a traditional design method that conforms to sustainable development. Due to the limited depth of space and the adoption of mechanical ventilation in most contemporary architectural design, this passive energy-saving method is gradually being ignored. In this study, we use ventilation measurement and simulation to explore the characteristics of ventilation performance in the cold alleys of the renovation and expansion project of Shixiangyuan Garden. The research, using anemometers and thermometers for measurement, aims to explore how Shixiangyuan Garden can utilize its existing environment and improve it to adapt to local conditions, and also discusses the methods of increasing the number of air vents to improve the overall ventilation performance of the alleys, as well as the effects of form changes caused by utilizing water and plants to supplement the soft interface. Although many studies have explored the mechanisms of cold alleys in traditional architecture, few have discussed the variance of cold alley forms that could adapt to the limited depths of newly constructed buildings. This study attempts to explore the potential for this through simulation. The purpose is to find new ways to inherit the sustainable advantages of cold alleys in new projects.

Field test of machine-learning based mean radiant temperature estimation methods for thermal comfort-integrated air-conditioning control improvement and energy savings

Advanced control strategies for heating, ventilation, and air-conditioning (HVAC) systems aim to enhance both buildings' energy efficiency and occupant thermal comfort. Despite their potential, real-world demonstration studies on such advanced technologies are still lacking. This study presents a field demonstration of a real-time predicted mean vote (PMV)-based HVAC control strategy in a typical residential building under hot and dry climate conditions. This study introduces an advanced thermal comfort-based controller (TCC) for the PMV-based HVAC control. TCC continually assesses indoor and outdoor thermal conditions and adjusts the HVAC setpoint temperature to optimize real-time energy use while ensuring satisfactory indoor thermal comfort. Machine learning models for the PMV-based HVAC control system are employed to estimate a mean radiant temperature (MRT) point, which is one of the variables used to calculate real-time PMV values. Three machine learning models (i.e., linear regression, regression trees, and artificial neural network) are adopted in this study with non-stationary real-time input values, including times, pre-determined setpoints, and indoor and outdoor temperatures. The developed TCC is installed in a full-scale experimental house in Kuwait, which is under hot and dry climate conditions, to assess the house's indoor thermal comfort and AC energy efficiency performance. Results indicate that the TCC provides better thermal comfort performance compared to the non-TCC case, including up to a 60% improvement in PMV. The proposed TCC controlled by the machine learning methods demonstrates HVAC energy savings potential of over 20% while meeting the desired thermal comfort levels in the experimental building. These findings are expected to be valuable, as they can contribute to reducing cooling energy in residential buildings in hot and dry climate conditions.

Impact of Economic Awareness on Sustainable Energy Consumption: Results of Research in a Segment of Polish Households

This manuscript explores the relationship between the economic awareness (as a part of energy awareness) of Polish households and their sustainable energy consumption practices. Sustainable consumption is measured by the frequency of behaviors such as turning off electrical devices when not in use, removing mobile device chargers from sockets, switching off lights when leaving a room, preferring showers over baths, using washing machines and dishwashers only when full, and purchasing energy-efficient appliances and light bulbs. Economic awareness is gauged through variables such as knowledge of electricity tariffs, understanding of electric bill components, awareness of electricity prices, exact knowledge of electricity expenses, electricity usage in kWh, knowledge of effective energy-saving methods, and familiarity with the energy efficiency classes of appliances and light bulbs. This study presents profiles of households with high and low economic awareness regarding their electricity expenditures and examines how these profiles differ in their sustainable energy consumption behaviors. This research is based on a survey of 1407 Polish households conducted online in 2023. Data collected from the survey were subjected to statistical analysis and are presented in tables and graphs. The findings are discussed in the context of the existing literature in the field, highlighting the implications of economic awareness on sustainable energy consumption practices. This research contributes to understanding how economic knowledge influences energy-saving behaviors among Polish households, providing insights for policymakers and energy conservation initiatives. One of the key findings of this paper is the significant association between economic awareness, energy-saving knowledge, and the adoption of sustainable energy consumption behaviors among Polish households. This study reveals that households with higher levels of economic awareness demonstrate a notably higher frequency of practices related to sustainable energy consumption compared to those with lower economic awareness. Similarly, households equipped with greater knowledge about energy-saving techniques exhibit a higher propensity to adopt energy-efficient behaviors. This underscores important roles of economic literacy and education in fostering behavioral changes towards more sustainable energy practices, highlighting the importance of targeted interventions and educational campaigns aimed at enhancing economic awareness and promoting energy-saving knowledge among consumers.

Analysis and Reflection on the Green, Low-Carbon, and Energy-Saving Design of the Super High-Rise Building

Shanghai Tower has become a new landmark of Shanghai. In the current trend advocating green building and energy efficiency, considerations of wind loads and thermal characteristics of the perimeter structure of Shanghai Tower are crucial. This paper conducts comparative simulation studies on the wind environment of Shanghai Tower using Ecotect software, and stress analyses and thermal simulations of the perimeter structure using ANSYS software. The study compared three buildings’ surface wind pressure distributions using models with equal-volume and circular cross-sections. We found that the unique exterior design of the Shanghai Tower results in a more regular and uniform distribution of wind pressure on its surface compared to both circular and square planar models, with a lower average wind pressure value. In addition, the stress analysis results indicate significant differences in deformation and stress distribution between the windward and leeward sides. Enhancing the bending moment detection of the peripheral structure and optimizing the layout of detection points are recommended. Thermal simulation results show excessive heat conduction flux in winter conditions, suggesting optimization using passive energy-saving methods such as light-sensitive thermal insulation materials during winter. This research is a reference for designing other super-tall buildings prioritizing low-carbon energy efficiency and structural safety.

Using setpoint temperatures based on adaptive thermal comfort models: The case of an Australian model considering climate change

It has recently become clear that using adaptive thermal comfort models to determine setpoint temperatures is a successful energy-saving method. Global models like ASHRAE 55 and EN16798-1 have been used in recent experiments using adaptive setpoint temperatures. This work, however, has taken a different route by concentrating on a region-specific Australian adaptive comfort model. The goal is to compare the energy implications of the use of setpoint temperatures based on the Australian local comfort model compared to the worldwide adaptive ASHRAE 55 model to highlight the significance of choosing the most fitting comfort model for making accurate predictions. All of Australia's climate zones are taken into account, as well as mixed-mode building operation scenarios, current and future scenarios, namely the years 2050 and 2100 for Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. It has been found that the Australian-model-based adaptive setpoint temperatures taking into account mixed-mode significantly lowers energy demand when compared to the ASHRAE 55 adaptive model (average energy-saving value of 63 %). Considering climate change, the Australian model has an average energy demand of 13–26 kW h/m2·year, and an average increase of 1–13 kW h/m2·year. In the case of ASHRAE 55 model, energy demand decreases in future scenarios and average values range between 3 and 11 kW h/m2·year. Therefore, setting setpoint temperatures in accordance with the Australian regional adaptive comfort model is a very efficient method for energy conservation. These differences raise awareness on the importance of the selection of the appropriate adaptive thermal comfort model.

Multi-objective green vehicle scheduling problem considering time window and emission factors in ship block transportation

Logistics distribution is one of the main sources of carbon dioxide emissions at present, and there are also such distribution problems in the shipbuilding process. With the increasing attention paid to environmental problems, how to effectively reduce the energy consumption of block transportation and improve the utilization rate of resources in the factory is the key problem that China’s shipbuilding industry needs to solve at present. This article considers the time windows for block transportation tasks, as well as the self-loading constraints of different types of flat cars, and establishes an optimization model that minimizes the empty transport time and energy consumption of the flat cars as the optimization objective. Then, an Improved Genetic Whale Optimization Algorithm is designed, which combines the cross and mutation ideas of genetic algorithms and proposes a whale individual position updating mechanism under a mixed strategy. Furthermore, the performance and computational efficiency of the algorithm are verified through comparative analysis with other classical optimization algorithms on standard test examples. Finally, the shipyard’s block transportation example proves that the energy-saving ship block transportation scheduling method can effectively improve the efficiency of shipbuilding enterprise’s block transportation and reduce the energy consumption in the block transportation process. It proves the engineering practicality of the green dispatching method proposed in this paper, which can further provide a decision-making method for shipyard managers.

Synthesis of high quality green phosphors by co-precipitation and induction heating

With the development of light-emitting diodes (LEDs) display and lighting industry, new requirements have been put forward for phosphors. Traditional syntheses of phosphors face the problems of slow temperature increase, long holding time and corresponding larger particle size. In this work, a co-precipitation combined with induction heating method was developed for the fast and efficient synthesis of Lu2.97Al5O12:0.03Ce3+ (LuAG:0.03Ce) phosphors. The effects of calcination temperature and holding time on the morphology and luminescence properties were investigated. The phosphor synthesized at 1600 °C for 10 min (10 min@1600 °C) has an average particle size of 500 nm, and exhibits good luminescence properties and thermal stability (maintaining 92.04 % of room temperature light intensity at 200 °C). The luminescence intensity and the external quantum efficiency (EQE) of the phosphor (60 min@1500 °C) are higher than those of a commercial phosphor. The light source fabricated with phosphor ceramic prepared by the phosphor (10 min@1500 °C) shows a luminous efficacy (LE) of 193 lm/W. Therefore, co-precipitation combined with induction heating is an energy-saving and promising method for the synthesis of phosphor.

Efficient activation of periodate using MnFe2O4/BC composite for removal of organic contaminants: Performance and mechanism

The periodate (PI)-based advanced oxidation process (AOP) is an economical and energy-saving method for remediating water by degrading pollutants. An efficient system for PI activation was developed by loading manganese ferrite spinel (MnFe2O4) on biochar (BC) through a facile method, affording a metal-oxide MnFe2O4/BC composite catalyst. The developed system demonstrated significant effectiveness in eliminating various organic pollutants, particularly achieving high removal (5.26 and 2.83 times that of biochar and MnFe2O4, respectively) and mineralization (49.7 %) of the model pollutant tetracycline hydrochloride (TC) within 30 min. The system exhibited outstanding catalytic performance under various environmental conditions (pH, inorganic salts, humic acid, and real water bodies), as evidenced by quenching experiments and electron paramagnetic resonance (EPR) studies, proving that superoxide radicals (O2•-) are the main reactive species for TC degradation in the reaction system, in addition to singlet oxygen (1O2), iodyl radicals (IO3•) and hydroxyl radicals (•OH). Potential pathways for TC degradation in this system were revealed based on density functional theory (DFT) and the ecological toxicity of the intermediates was analyzed through quantitative structure–activity relationship (QSAR) assessment. Analysis of the magnetic hysteresis and cycling stability demonstrated that the composites were stable and could be recycled by applying a magnetic field. This work opens a new pathway for designing efficient PI activators for the selective oxidation of organic pollutants and highlights the potential application of this system in practical wastewater treatment.

A new approach for selecting and implementing phase change materials in Kuwaiti Buildings: Practical considerations

This study focuses on practical considerations regarding Phase Change Materials (PCMs) for energy-efficient buildings in Kuwait's hot climate. Its objective is to fill gaps in the existing literature by providing experimental validation, which has been lacking in previous research that heavily relies on numerical simulations. The selection of a PCM with an appropriate melting point is crucial to achieve balanced melting and solidification cycles. To address this, two identical portable cabins were constructed at the Australian University of Kuwait. One cabin served as the base case, while the other was used to investigate various energy-saving methods. Indoor weather and energy monitoring devices were installed, enabling the collection of wall and roof temperature data at 10-minute intervals. Analysis of the temperature distribution revealed that a PCM with a melting point of 24 °C remained in a melted state for approximately 8 h and solidified for 16 h within a 24-hour cycle, particularly on the hottest days in Kuwait. Furthermore, a TRNSYS Type399 PCM model was developed to examine the impact of PCM parameters on the annual energy performance index of the portable cabins. The results indicate that utilizing a PCM with a melting point of 24 °C on interior walls and ceilings can result in annual energy savings of up to 20 %, while the thickness of the PCM does not significantly affect performance. In a broader context, this research seeks to tackle the real-world challenges linked to the deployment of PCMs in energy-efficient buildings within Kuwait's hot climate. It highlights the significance of confirming findings through practical experimentation aimed at improving the utilization of PCMs.

Energy-saving regulation methods and energy consumption characteristics of office air-conditioning loads in hot summer and cold winter areas

The air-conditioning system of an office building may have much higher operational energy consumption than its designed value due to the actual use behavior which significantly deviates from the predicted one. To precisely analyze the actual air-conditioning energy consumption, in this paper, based on the impact of occupant air-conditioning behavior on the energy consumption of air-conditioning systems, a Supply-Side Cooling Load Regulation Method (SSRM) is proposed, and its air-conditioning energy consumption analysis model is established. The energy consumption characteristics of the air-conditioning system under SSRM were analyzed, with the assumption that the example office building is located in a hot summer and cold winter areas. The results indicate that the indoor air conditioning set temperature and the actual fresh air volume are important factors affecting the variation of the air conditioning system cooling load under the Demand-Side Cooling Load Regulation Method (DSRM) method, whereas under SSRM, the air conditioning system cooling load is not affected by the variation of the indoor set temperature and the fresh air volume; meanwhile, regulating human air-conditioning use behaviors is the key point of reducing air-conditioning cooling load. The increasing fresh air volume from 30 m3/(p∙h) to 90 m3/(p∙h) can result in about a 5°C increase in the average daily indoor air temperature in the rooms used by SSRM, and it also causes an increase in the total air-conditioning load in the rooms under DSRM by more than 45 kWh/day. Further, compared to the DSRM, the SSRM can well regulate occupant air-conditioning use behaviors, which reduces energy consumption by more than 35% in the summer.

Comparative analysis of energy saving effect of passive exoskeleton designs

Nowadays, exoskeletons have a wide range of application in many fields. Among various types of exoskeletons, passive exoskeletons have become a major development field in exoskeleton device due to their lightweight and simple structure characteristics. This study provides an analysis of an ankle passive exoskeleton and a full lower limb passive exoskeleton design on their respective energy-saving effect during walking. The two selected designs both represent common approaches within the fields of ankle and full lower limb exoskeleton. Through a comparative evaluation of the structures and energy-saving methods of the two designs, the study validates the effectiveness of both designs. Drawing from the characteristics of the designs and comparative analysis, the study discusses the performance and limitations of both designs and outlines potential improvement and applications of both designs. Base on the analysis and the findings, the study aims to contribute to further advancement of passive exoskeleton design and offers some suggestions for its development.

Effect of sintering mechanism on dielectric properties of Ba0.5Sr0.5TiO3-ZnAl2O4 composite ceramics synthesized by two-step sintering with low energy consumption

The application of Ba1-xSrxTiO3-based composites in microwave field has become a popular research topic. Ba0.5Sr0.5TiO3-ZnAl2O4 (BST-ZA) composite ceramics were successfully fabricated by both conventional sintering and two-step sintering process. The microstructure and dielectric properties of Ba0.5Sr0.5TiO3-ZnAl2O4 composite ceramics prepared by two sintering methods were compared. The samples prepared by the two-step sintering method have lower ion diffusion degree, shorter holding time and lower energy consumption, and it is easier to obtain samples with higher density and uniform grain size distribution, compared with those fabricated by the conventional sintering method. The dielectric permittivity and Curie temperature of two-step sintered samples are lower than those obtained by conventional sintering, while the dielectric tunability is almost unchanged (two-step sintering: 17.7 %, conventional sintering: 18.6 %). These results indicate that two-step sintering method is an efficient and energy-saving method in preparing BST-ZA composites.

Research on Boiler Energy Saving Technology Based on Internet of Things Data

This paper proposes a heat demand prediction model that analyzes the heat behavior of heat users, and analyzes the heat behavior data of heat users through a clustering algorithm to predict their heat demand. This paper is based on the supply-demand balance strategy to reduce the heat loss during the transmission of heat medium, and then improve the energy-saving efficiency of the boiler. The traditional boiler energy-saving and consumption reduction method is to optimize the boiler combustion parameters, improve the fuel combustion efficiency and waste heat recovery technology through the Internet of Things and big data technology. The method of balancing the heat-using end with the load of the boiler at low usage frequency is seldom considered. Therefore, this paper predicts the heat demand of the heat-using end by analyzing its thermal behavior, and balances the heat demand and boiler heat supply under the condition of meeting the heat demand. Finally, through simulation experiments, the validity of the model is verified, and the trend and data can be well predicted in the short-term heat demand prediction.

Ultrafast-adsorption-kinetics molecular sieving of propylene from propane

The separation of propylene (C3H6) and propane (C3H8) is very costly due to similar physical-chemical properties and has been listed as one of the seven chemical separations to change the world. High-purity C3H6 is an important raw material to produce polypropylene and acrylonitrile. However, C3H8 is produced as a by-product in the production process of C3H6, which has a similar structure and boiling point as those of C3H6. Traditionally, the separation of C3H6 and C3H8 by distillation has high energy consumption and an unremarkable separation effect. Therefore, there is an urgent need to develop more energy-saving and efficient methods for the separation of C3H6 and C3H8.

Modeling and multi-objective optimization for energy-aware scheduling of distributed hybrid flow-shop

With the development of economic globalization and sustainable manufacturing, energy-aware scheduling of distributed manufacturing systems has become a research hot topic. However, energy-aware scheduling of distributed hybrid flow-shop is rarely explored. Thus, this paper is the first attempt to study an energy-aware distributed hybrid flow-shop scheduling problem (DHFSP). We formulate a novel mathematical model of the DHFSP with minimizing makespan and total energy consumption (TEC) criteria. A hybrid multi-objective iterated greedy (HMOIG) approach is proposed to address this energy-aware DHFSP. In this proposed HMOIG, firstly, a new energy-saving method is presented and introduced into the model for reducing TEC criterion. Secondly, an integration initialization scheme is devised to produce initial solutions with high quality. Thirdly, two properties of DHFSP are used to invent a knowledge-based local search operator. Finally, we validate the effectiveness of each improvement component of HMOIG and compare it with other well-known multi-objective evolutionary algorithms on instances and a real-world case. Experimental results manifest that HMOIG is a promising method to solve this energy-aware DHFSP.

An efficient and environmentally-friendly extraction, characterization and activity prediction of polysaccharides from Rhizoma et Radix Notopterygii

Traditional hot water reflux extraction, ultrasonic-water extraction (UW), ultrasonic-natural deep eutectic solvent (NADES) extraction (U-NADES), ultrasonic-water and enzyme extraction (U-W-E) and ultrasonic-NADES and enzyme extraction (U-NADES-E) are employed for the extraction of Rhizoma et Radix Notopterygii polysaccharides (RNP), in which, the U-NADES-E has being proved as the most effective method. Response Surface Methodology (RSM) was utilized to optimize the conditions for U-NADES-E method. Using the optimal extraction conditions, the yield of RNP can be enhanced by nearly two-fold in comparison to the traditional extraction method, achieving a yield of 7.38 %, with a mere 30-min treatment and low ultrasonic power at 240 W. The RNP's composition included Rhamnose, Arabinose, Galactose, Glucose and Galacturonic Acid by high-performance anion-exchange chromatography. The polysaccharides from two different species of Rhizoma et Radix Notopterygii have also been characterized and identified. Network pharmacology and molecular docking predict that RNP may exert its effects in vivo through binding to PPARA, ACE and REN proteins, thereby potentially impacting diabetes outcomes. This study proposes a new, efficient, energy-saving and environmentally-friendly method for the extraction of RNP.

Energy-saving strategy and method of spindle deceleration during no-load operation of machine tools for energy lean management

Computer Numerical Control (CNC) machine tools undergo periods of no-load motion, such as tool feeding, tool withdrawing, and tool changing, during workpiece processing. These intervals result in energy wastage as the machine tools remain idle without performing cutting operations. To address this issue, we propose a novel energy-saving strategy and method involving spindle deceleration during the no-load operation of machine tools for energy lean management. Specifically, we conducted three tasks: (1) analyzed the energy consumption characteristics of the CNC machine tool during no-load operation; (2) established a theoretical decision-making model for the energy-saving method of spindle deceleration; (3) discussed the energy-saving critical time for energy savings and the energy-saving effect of the deceleration strategy for the machine tool spindle through three machining cases. Furthermore, we conducted a case study using the CK6153i lathe to verify the effectiveness and feasibility of the proposed method. The results demonstrated significant energy savings of 1826.65 J, 2948.85 J, and 7650.05 J, along with reductions in energy waste of 14.99 %, 20.43 %, and 53.01 %, respectively, in the three machining cases through the implementation of the spindle deceleration strategy. We believe that the outcomes of this research can better assist engineers in the energy lean management of machine tools.

Energy-saving robust control of active suspension system based on bioinspired reference model

This paper proposes an energy-saving robust tracking control method for active suspension systems with a bio-inspired reference model and nonlinear extended state observer (NLESO). According to the principle of cheetah running biology, a bionic structure with nonlinear quasi-zero stiffness is designed, which also has ideal Sky-hook damping and vibration-absorbing mass. An NLESO is designed to estimate the total uncertain disturbance and the state of sprung mass in the suspension system, and then an energy-saving robust tracking controller is proposed. The controller consumes less control energy while isolating the vibration of the sprung mass, thus improving the riding comfort of vehicles and saving energy. The simulation results show that, compared with the reference control method, the vertical acceleration of the sprung mass is reduced by 80.68% and 92.42% respectively in the class C road and bump road conditions and the control energy is decreased by 31.71% and 30.50%, respectively. The control effect of the proposed controller for the active suspension system is verified.

Evaluation Research on Energy-Saving Retrofitting of Roofs of Traditional Wood-Structured Dwellings Based on the Continuation of Historical Features: A Case Study of Guangdu Village No. 280 Dwelling in Zhejiang

China has numerous traditional wooden dwellings located in regions with hot summers and cold winters. The historic dwellings lack proper thermal insulation and have excessive energy consumption in the building structure, failing to suit the needs of modern people. Hence, it is crucial to enhance their energy efficiency through essential actions. Roofs, being the fifth side of the building envelope, are frequently neglected when it comes to enhancing their insulating capabilities. The study aimed to implement energy-efficient roof alterations while preserving the historical features of traditional structures. This study focuses on enhancing the energy efficiency of a traditional wood-structured dwelling in Guangdu Village, Zhejiang Province, China, by installing composite thermal insulation panels on the interior of the roof using an easy restoration approach. The actual risk of condensation and the impact of retrofit processes on historical features determine the choice and limitations of energy-saving retrofit materials and methods. This study evaluates the transformation using two indicators: energy efficiency and economic feasibility. The numerical simulation results indicate that traditional dwellings have an annual energy savings rate of 16.66% and an investment payback period of 7.25 years. This study demonstrates the feasibility of energy-saving roof renovation measures for these traditional wood-structured dwellings. The measures improve energy efficiency and are affordable for residents. This study can offer technical suggestions for enhancing the energy efficiency of traditional wood-structured dwellings.

Function optimization of ceramic firing process and reduction of energy consumption based on CFD simulation

Microwave sintering, as an efficient and energy-saving advanced sintering method, has advantages that traditional sintering methods cannot match, such as promoting ion diffusion and refining grains. This paper uses microwave heating equipment and solid-phase reaction method combined with microwave sintering technology to prepare ceramics. The treatment process of powders and the influence of microwave sintering parameters on the reduction of energy consumption in the ceramic firing process were studied, and the microwave sintering process was optimized. This article also uses computational fluid dynamics (CFD) as a tool to establish a numerical model of hydrodynamic sedimentation based on the Euler multiphase flow model, and it uses the established numerical model to conduct engineering scale research on the classification treatment process of processing waste. Finally, this article elaborates on the process of multi-process planning and optimizes relevant process parameters. This article builds on previous research by employing a BP neural network (BPNN) to determine the correlations between the many variables involved in the production of functional ceramics and their respective quality metrics. The experimental findings demonstrate the efficacy of the proposed methodology in performing intelligent tasks like process decision-making and optimizing process parameters.