Energy-saving Operation Strategy Research Articles

Study on Airflow Distribution and Energy Conservation in a BSL-4 Laboratory Involved in Aerosol Infection Risk

In recent years, COVID-19 has occurred frequently in the world. The biosafety level 4 (BSL-4) laboratory personnel are at risk of being infected by bioaerosols. The high demand for fresh air makes the energy consumption of the laboratory far greater than that of ordinary buildings. This study aimed to propose a suitable air distribution design and reduce the energy consumption of the BSL-4 laboratory, which is beneficial for creating a healthy and green built environment. Firstly, the diffusion characteristics of aerosols, infection risk under different air distributions, and ventilation parameters were analyzed in depth. Secondly, from the perspective of negative pressure control, the influence of parameters such as air tightness and air changes on the airflow in multizone was discussed. The results indicated that the aerosol concentration under the same conditions of the upper supply-upper exhaust is 1.4 times higher than that of the upper supply-bottom exhaust after the airflow stabilizes. The impact of eddy currents on pollutant diffusion is weakened when the air supply velocity reduced from 1m/s to 0.8m/s. Finally, the energy-saving operation strategy was proposed with the optimized ventilation parameters. The results showed that this operation scheme reduced the energy consumption of the laboratory by 15-30%.

Joint optimization of energy conservation and transfer passenger service quality in rail transit system

ABSTRACT The complex electricity transmission process and transfer passenger demand in the rail transit system make it challenging to formulate optimal timetables and train speed profiles to meet the needs of the system. This study optimizes train timetable to meet energy conservation and passenger service quality of cross-mode rail transit system during different operation periods. Firstly, based on the spatiotemporal travel data of transfer passengers, the train-time matrix is proposed to construct a bi-objective optimization model (BOOM) that incorporates the total energy consumption optimization model (TECOM) and total waiting time optimization model of transfer passenger (TWTOM). It can better combine the passenger transport scheme and the train energy-saving operation strategy, thus improving energy-saving performance and passenger transport efficiency and simplifying the difficulty of mathematical modelling of such BOOM. Then, a method for determining the appropriate weight coefficient ratio and the improved non-dominated sorting genetic algorithm II (NSGA-II) are applied to obtain the efficient Pareto front solutions. Taking the numerical experiments as test cases, the improved NSGA-II can get a efficient solution faster than the traditional NSGA-II. Finally, two numerical experiments using real-world data are conducted to verify the practicability of the optimization model and the effectiveness of improved NSGA-II. The optimization results can reduce energy consumption by up to 11.02% and passenger waiting time by 137,320 s, respectively. This study helps to improve the energy efficiency and passenger service quality of cross-mode rail transit systems, and also provides a reference for dispatchers to optimize train timetable.

Energy-Saving Operation Strategy for Hotels Considering the Impact of COVID-19 in the Context of Carbon Neutrality

With the advent of the post-epidemic era, the energy consumption characteristics of hotels have changed, which has an important impact on urban energy conservation. In order to contribute to the goal of carbon neutrality, this study discusses the energy-saving operation strategy of hotels considering the impact of the COVID-19 epidemic. Based on the energy consumption characteristics of large public buildings, this paper analyzes the energy consumption distribution and operation characteristics of hotel buildings in detail. By collecting energy consumption data from five typical large hotel buildings in a tourist city in southern China from 2018 to 2022, the impact of COVID-19 on hotel energy consumption and hotel business characteristics was discussed in detail. Combined with the economic development characteristic in the post-epidemic era, this paper explores the energy-saving strategies that hotels can adopt in the context of normalized epidemic prevention and control and obtains the optimal path of low-carbon economic operation of hotel buildings. This study reveals the energy consumption characteristics and energy-saving potential of hotel buildings, and provides enlightenment for hotel management and low-carbon development in the post-epidemic era.

Real-time energy saving optimization method for urban rail transit train timetable under delay condition

The global energy crunch and rising demand for electricity make it all the more important to develop energy-efficient timetable for urban rail transit trains. Under normal circumstances, the train can operate normally according to the energy-saving timetable that has been formulated. However, trains may deviate from the original schedule and increase energy consumption due to station delays. For this, how to quickly restore the train to an efficient state and effectively transport the delayed passengers to the destination as soon as possible is a challenging problem. Therefore, this paper proposed a two-stage optimization method to solve the above problem. In the first stage, an improved differential evolution algorithm was used to optimize the energy-saving operation strategy of the train without delay, and the optimal running time-energy consumption solution set of the train in the redundant running time of each section on the entire line was obtained. Then, based on this, the second stage proposed a rapid iterative method to optimize and reschedule the timetable of the delayed train in the remaining sections, and an efficient solution was obtained. Finally, Nanning Rail Transit (NNRT) Line 5 is selected for a case study, and the proposed model and method are verified. Compared with the existing solution that temporarily shortens the running time of the next section in the delayed station, the proposed method reduces the energy consumption by 3.32% on average, and the average calculation time is about 0.36 s, which showed that the method is effective and meets the real-time requirements.

Energy consumption optimization of tramway operation based on improved PSO algorithm

Tramway has the advantages of reliable operation, energy-saving, and environmental protection, which is an important way to alleviate traffic pressure. Energy consumption optimization of tramway operation is significant in reducing the operation cost. Therefore, the energy consumption optimization model of tramway operation based on the improved PSO algorithm is developed. Firstly, the energy consumption model of the tramway is established based on the energy-saving operation strategy. Then, the competition mechanism-based particle swarm optimization (CM-PSO) algorithm is developed to improve energy-saving performance. Finally, the Guangzhou Haizhu tramway is taken as an example to illustrate the effectiveness of the developed method. The results show that the developed model effectively reduces the tramway operation energy consumption and performs better than the previous methods.

Energy-efficient train trajectory optimization based on improved differential evolution algorithm and multi-particle model

Urban rail transit is an efficient public transport, and reducing their energy consumption is beneficial to climate change and sustainable development. Current researches in metro train trajectory optimization are mainly based on the single-particle train operation model, and the selection of energy-saving operation strategy under time-varying passenger flow is not taken into consideration. Therefore, considering the practical line environment and uncertain trainload simultaneously, this paper establishes a multi-particle operation model and develops a new optimization method based on mutated dichotomy and differential evolutionary algorithm to solve the model. Then, the influence of various passenger flow and line information on the train trajectory optimization is analyzed from the perspective of trainload capacity based on the proposed method, and the selection basis of the optimal energy-saving train operation strategy was determined. Finally, a case study was conducted in the Nanning Rail Transit Line 1 and Line 5, respectively. The results show that the proposed method has strong efficiency for energy conservation and better optimization performance than the conventional differential evolution algorithm in solving train trajectory optimization problem. And the simulation results of the Line 5, which is a fully automatic operation line, also verified the reliability of the selection basis.

A multi-objective operation strategy optimization for ice storage systems based on decentralized control structure

Improving the operational efficiency of chillers and science-based planning the cooling load distribution between the chillers and ice tank are core issues to achieve low-cost and energy-saving operations of ice storage air-conditioning systems. In view of the problems existing in centralized control architecture applied in heating, ventilation, and air conditioning, a distributed multi-objective particle swarm optimization improved by differential evolution algorithm based on a decentralized control structure was proposed. The energy consumption, operating cost, and energy loss were taken as the objectives to solve the chiller’s hourly partial load ratio and the cooling ratio of ice tank. A large-scale shopping mall in Xi’an was used as a case study. The results show that the proposed algorithm was efficient and provided significantly higher energy-savings than the traditional control strategy and particle swarm optimization algorithm, which has the advantages of good convergence, high stability, strong robustness, and high accuracy. Practical application: The end equipment of the electromechanical system is the basic component through the building operation. Based on this characteristic, taken electromechanical equipment as the computing unit, this paper proposes a distributed multi-objective optimization control strategy. In order to fully explore the economic and energy-saving effect of ice storage system, the optimization algorithm solves the chillers operation status and the load distribution. The improved optimization algorithm ensures the diversity of particles, gains fast optimization speed and higher accuracy, and also provides a better economic and energy-saving operation strategy for ice storage air-conditioning projects.

One-point method for speed strategy optimization based on slope simplification and speed limit prediction

The automatic driving of trains is an inevitable trend of the modern development of railway transportation, and it is also a necessary requirement for energy conservation and emission reduction. A train automatic driving speed planning scheme with only one operation state transition point in the simplified slope section is proposed based on slope simplification principle and speed limit regulation on an interval line, which reduces the control complexity and energy consumption for automatic driving. An improved fitness function of genetic algorithm (GA) is explored to solve an operation state transition point position of the train, then train energy-saving operation strategy is presented. Practical energy costing experiment for freight train (HXD3) with 2,800 tons for a 33.7km line on Bin-Zhou railway line is obtained and compared with the proposed algorithm. Results show that energy consumption is saved by 15.2% for the speed strategy from the proposed method. So operation strategy is simplified greatly because of only one state transition point in a simplified interval which is more suitable for automatic driving. On the other hand, one point operation strategy is also more energy efficient than manual manipulation. Therefore, the proposed method provides a simple and efficient control strategy for train automatic driving.

A Novel Energy Saving Operation Strategy of Multiparameter Coupling Coordinated Speed Regulation for Crushing

A Novel Energy Saving Operation Strategy of Multiparameter Coupling Coordinated Speed Regulation for Crushing

Energy-saving operation strategy of air conditioning system in tea brick fermentation room under different outdoor meteorological parameters

In the process of tea brick production, the major energy consumption lies in the air-conditioning system of the tea fermentation chamber. Under the condition of satisfying the fermentation process, the energy-saving operation of the air-conditioning system is an effective method to reduce the energy consumption and to improve the economic benefit of the tea brick. However, due to lack of quantitative calculation of the indoor heat and moisture load during the fermentation process, the air conditioning system of the tea brick fermentation chamber is mainly based on the CAS (circulating air system) or the ORCS (One return air conditioning system). Consequently, in this study, the heat and moisture transfer model of the tea brick was built based on the heat and moisture coupling transfer theory for porous media. The COMSOL Multiphysics was implemented to solve the heat and moisture exchange rate between tea bricks and the fermentation environment. Based on the rate and the heat transfer of the envelope structure, the heat and moisture load of the fermentation chamber was calculated under different meteorological parameters. According to the indoor heat and moisture load and outdoor weather parameters, the energy consumption and exergy loss of the two air conditioning systems were analyzed during the fermentation cycle. The results show that the ORCS energy efficiency is 30.8%–55.8% greater than that of the CAS, and the irreversible exergy loss is also reduced by 19.6%–57.0% when the residual heat Q inside the fermentation chamber is less than zero. On the other hand, when the residual heat Q is greater than zero, the CAS energy efficiency is 16.1%–22.3% greater than that of the ORCS, and the exergy loss is reduced by 37.8%–43.3%. According to the energy and exergy analyses of the two air-conditioning systems, an energy-saving operation strategies of air conditioning system for brick fermentation were determined in different tea brick production areas.

Explore energy saving operation strategy: Indoor VOCs removal performance of silica gel rotor in clean-air heat pump system at low regeneration air temperature

Clean air heat pump (CAHP) is a new technology that combines air cleaning with hygro-thermal control of ventilation air, which is competitive to vapor compression cooling technology from both energy and indoor air quality perspectives. In CAHP, a regenerative silica gel rotor is used for both moisture control and air cleaning, and a heat pump is used for providing thermal energy to regenerate the rotor. If the CAHP is applied in the mild climate area, the desired thermal conditions of ventilated air will be achieved without operating at high regeneration air temperature to save energy, however, whether air cleaning performance of the CAHP can be guaranteed is unknown. Therefore, this study experimentally investigated the air cleaning performance of the CAHP when it was regenerated by air at different low air temperatures. Five typical indoor pollutants-formaldehyde, acetone, ethanol, toluene and 1,2-dichloroethane were adopted as indoor pollutants. The results showed that air cleaning efficiency of the CAHP was normally decreased by 5%∼15% when regeneration air temperature was decreased by 10 °C. The air cleaning efficiency for all the pollutants could still maintain 50% when the regeneration air temperature dropped to 40 °C with low air humidity.

Research on Energy-Saving Operation Strategy for Multiple Trains on the Urban Subway Line

Energy consumption for multiple trains on the urban subway line is predominantly affected by the operation strategy. This paper proposed an energy-saving operation strategy for multiple trains, which is suitable for various line conditions and complex train schedules. The model and operation modes of the strategy are illustrated in detail, aiming to take full use of regenerative braking energy in complex multi-train systems with different departure intervals and dwell times. The computing method is proposed by means of the heuristic algorithm to obtain the optimum operation curve for each train. The simulation result based on a real urban subway line is provided to verify the correctness and effectiveness of the proposed energy-saving operation strategy.

Pressure Gradient Control and Energy-saving Operation Strategy Study on a Multi-zone Cleanroom

Pressure gradient control is an effective technical measure to prevent the external pollution and cross-contamination from different clean areas of a multi-zone cleanroom, which played a key role for the quality control of cleanroom. In this paper, modelling analysis combined with experimental investigations conducted on a multi-zone cleanroom experimental platform. A series of investigations were conducted on the experimental platform with supply air volume variation by electronic frequency conversion on air-supply fan unit. The characteristics of cleanroom such as cleanliness, ventilation rate, pressure gradient were all measured. An energy-saving operation strategy for multi-zone cleanroom has been gained. Experimental investigations proved that the determined principle of pressure gradient setting is feasible for reliable and energy-saving operation. It is also proved through experiments that about 24.5% energy consumption decreased when adopted the operation strategy.

Energy Saving Operation Strategy of an Existed Indoor Ice Rink

For the problems that operation energy consumption is large, lack of energy saving strategy existed in the speed skating ice rink in Harbin Ice Training Base, field investigation is conducted and the data measured schemes are put forward including the temperature distribution above ice surface in vertical direction, the indoor relative humidity, the refrigeration units power consumption, the inlet and outlet temperature of cooling water etc. Then select the data of general training days and typical match days for comparative analysis. The results show that the running cost of refrigeration units represents a significant proportion of the total running cost; lack of low energy consumption dehumidification method to solve the problem that fog above the ice surface; in winter, using the outdoor cold source can reduce energy consumption of the cooling tower. Based on them, energy saving operation strategy based on outdoor cold source and using the return secondary refrigerant from the ice rink for cooling dehumidification are put forward.

Application Analysis of Water Loop Heat Pump System Energy Conservation of a Sports Training Center

A sports training center training venues and office building adopting water loop heat pump system (WLHPS) are taken as examples, combined with the practical problems in design and operation, to analysis the operation characteristics of the air conditioning system and its advantages and disadvantages, and the energy saving operation strategy is put forward to further reduce energy consumption.

Research on the High-Speed Railway Energy-Saving Operation Strategy Based on Heuristic Algorithm

High-speed Railway Energy-saving Operation is a NP complete problem and it’s difficult to seek the optimal solution by tradition method. In this paper, considering the influence braking utilization to train operation, we established a high-speed railway minimum energy cost model, in which the optimization objective are maximizing the Interval efficiency and minimizing the total energy consumption. Then the model is solved by heuristic algorithm and the operation strategies are gotten. The simulation experiment result showed that when the braking utilization is equal to 0, the energy will be largely saved if the operation time is increased slightly; with the increasing of braking utilization, the percentage of saved energy will decrease correspondingly. So, the high-speed railway energy-saving operation strategy based on heuristic algorithm performed well.

FA-Based Optimal Strategy Study of Train's Energy Saving Operation under Disturbed Condition

Different from changeable chromosome length genetic algorithm, a new method based on firefly optimization algorithm is put forward to search a trains energy saving operation strategy under running disturbance condition in railway network. The algorithm is designed and validated using a referenced simulation case. Compared with other methods, it demonstrates this new FA-based algorithm has a better result in computation efficiency and may be considered to use in other energy efficient train operation models.

Study Platform for AC Transmission System of High-Speed Train

Demand for CRH (China Railways High-Speed) trains, both in quantity and types, is increasing because of the rapid development of high-speed railway in China. To support the improvement and development the AC transmission system of these trains, a study platform is proposed in this paper. Target of the platform is supporting the study which contains design, verification, display etc. in detail. Platform framework is described in this paper. And the results of study on transmission system temperature rise and energy-saving operation strategy of high-speed train based on the platform are displayed. Availability of the study platform is verified.