Air Conditioning Energy Consumption Research Articles

The operation strategy of river water source heat pump cold source system in a chemical industrial park in a region with hot summers and cold winters

At present, the energy consumption of the whole process of buildings in China accounts for 45 % of the total energy consumption of the country, and the carbon emissions account for 50.6 % of the total emissions of the country. Among the energy consumption of buildings, air conditioning energy consumption occupies a major proportion, about 2/3. Traditional air conditioning cooling mainly uses refrigerants such as Freon to circulate and cool under high temperature and high pressure, which not only has high energy consumption but also can cause the external environment temperature to be too high. River water source heat pump is a renewable energy technology that can use water bodies including groundwater, surface water such as rivers, lakes, reservoirs and oceans. This project mainly studies the operation strategy of related units using river water as the cold source in a chemical industrial park in Chongqing, from unit selection, establishment of energy consumption model to unit operation strategy analysis and research, to achieve the best state of energy utilization.

Research on quantitative assessment method of multi-time scale regulation capability of heat source tower heat pump for grid regulation demand

Abstract In the context of power saving, the increasing energy consumption of air conditioning and the limited energy demand has become an urgent problem. Therefore, according to the feature that the accuracy of grid load forecasting improves gradually with the shortening of time scale and the flexible intra-day regulation characteristics of heat pump units, a multi-timescale regulation model of a heat pump system is developed. Aiming for the lowest operating costs and best performance, three system scheduling scenarios were developed: day-ahead, mid-day, and real-time, respectively. Through the coordination of multiple time scales, it is ensured that the output of the system meets the requirements of the grid. Taking the Wuhan area with four heat source tower units as an example, a simulation experiment comparing the performance of the multi-timescale scheduling method with the day-ahead scheduling method was conducted in the same system, which showed that compared to the day-ahead scheduling method, the multi-timescale scheduling method can reduce the system energy consumption by 13.1% and improve the system performance factor by 12.4%.

Comparative analysis of energy efficiency for three heating and cooling supply schemes in a region with hot summers and cold winters in a chemical industrial park

Building energy consumption in China accounts for 45% of the total national energy consumption, with air conditioning energy consumption representing approximately two-thirds of that. Therefore, energy efficiency in buildings is of utmost importance. This study focuses on a chemical industrial park located along the Fujiang River and compares three heating and cooling supply schemes: the river water source heat pump system, which utilizes river water as the heat source and heat sink; the water cooling unit and boiler system, which uses water-cooled electric compression chillers for cooling and an oil-fired boiler system for heating; and the split air conditioning and gas water heater scheme, which relies on refrigerants such as fluorine-containing compounds for cooling and a gas water heater for heating. By calculating the energy consumption of the above three schemes and conducting a comparative analysis, it is found that the river water source heat pump system exhibits significantly higher energy efficiency throughout the year compared to the water cooling unit and boiler system and the split air conditioning and gas water heater scheme. This highlights the notable energy efficiency advantage of the river water source heat pump system.

A systematic analysis of energy-saving potential of spectrum-selective radiative cooling materials in buildings

Passive cooling of buildings through radiative cooling (RC) is considered an effective method for reducing the energy consumption of air conditioning. In recent years, spectrum-selective RC materials (RCMs) have received extensive attention owing to their low solar absorptivity and high thermal emissivity in the atmospheric window. The energy-saving performance of RCMs is related to their own properties and local meteorological conditions, building type, building form, and energy use patterns. Although several studies have explored the performance of RCMs, most existing studies have considered a single building type and meteorological condition, and simple building forms that differ significantly from real buildings. Hence, the application analyses of RCMs to buildings are not sufficiently comprehensive. This study focused on the energy-saving potential of RCMs for building applications, and presented a systematic framework to analyze the energy-saving potential of RCMs under different conditions. DeST, which is embedded with a long-wave radiative heat transfer calculation module based on the equivalent sky temperature, was adopted as the simulation software. It can accurately calculate the radiative heat transfer in different wavelength bands, thus making the simulation results more accurate. Based on the calculation results of large-scale cases considering four major factors, namely climate, building type, construction year, and installation location of RCMs, the energy-saving performance of RCMs in different cases was analyzed, and the return on investment is performed, and more comprehensive suggestions were provided for applying RCMs in future buildings.

Kitchen Gardening: A Dual Solution for Urban Heat Islands and Nutritional Security in India

Urbanization has led to significant environmental and societal challenges, including the Urban Heat Island (UHI) effect and nutritional insecurity. Kitchen gardening, also known as urban horticulture, emerges as a promising solution to these pressing issues. By cultivating food in urban settings, individuals and families contribute to a more sustainable and resilient ecosystem. The practice of kitchen gardening plays a pivotal role in managing the UHI effect. Vegetation in urban areas helps moderate temperature extremes, reducing the heat retained by concrete and asphalt. This cooling effect contributes to lower energy consumption for air conditioning, mitigating urban pollution and reducing greenhouse gas emissions. Additionally, the proximity of urban gardens to residential areas decreases the need for transportation of produce, further cutting down on pollution and energy usage associated with food distribution. From a nutritional standpoint, kitchen gardening ensures food security by providing a direct source of fresh, healthy produce. This practice aligns with several Sustainable Development Goals (SDGs), including zero hunger (SDG2), good health and well-being (SDG3), and responsible consumption and production (SDG12). Urban horticulture empowers individuals to take control of their food sources, promoting a balanced diet and reducing dependence on industrial-scale farming. Furthermore, it creates opportunities for community engagement and economic growth, supporting decent work and economic growth (SDG8) and sustainable cities and communities (SDG11). Kitchen gardening is a multifaceted approach that addresses both environmental and nutritional challenges. Its benefits extend beyond individual households, contributing to broader sustainability goals and fostering a more harmonious relationship between urban development and the environment.

Moisture buffer value for hygroscopic materials with different thicknesses

Moisture buffer value (MBV) is a critical parameter for assessing hygroscopic material's ability to moderate indoor humidity variation. The original MBV theory is strictly valid only for a semi-infinite (or “very thick”) material. When the material is thinner than semi-infinite, the material's thickness will affect its moisture buffering ability. The existing MBV theory is inapplicable. This study proposed a new numerical method to calculate a material's MBV at different thicknesses. The proposed model is simple and efficient. The relation between a material's MBV and thickness and the optimal thickness can be obtained without extensive experimental measurement. What's more, the material's adsorption and desorption isotherms, as well as the material's hysteresis loop and scanning isotherms, are incorporated in the proposed model, making it applicable to advanced desiccant materials like Metal-Organic Frameworks (MOFs). MIL-100(Fe), one of the most promising MOF candidates for indoor humidity control, was used to validate the newly developed model. MBVs of MIL-100(Fe) samples with different thicknesses were measured, and the experimental data closely matched the simulated results. Finally, a building energy consumption simulation model was developed based on the proposed numerical model. A MOF panel with its optimal thickness was placed in the BESTEST typical office room located in Copenhagen. The results show that MOF can reduce about 30 % of the energy consumption of air conditioning in a purely passive way.

Transfer learning integrating similarity analysis for short-term and long-term building energy consumption prediction

Currently, building energy consumption prediction models are usually based on a large amount of historical operational data in high demands of building operating hours and monitoring systems. However, many buildings may lack operational data due to relatively limited monitoring systems, causing the failure to use data-driven methods to characterize the energy profile. In this context, transfer learning is a promising method to establish the knowledge transfer between many high-quality building operation datasets and a small amount of target building data, and to help predict energy consumption in the target building. This paper studies the possibility of employing transfer learning to achieve both short and long-term building energy consumption prediction. Firstly, a similarity analysis method, based on variable modal decomposition and dynamic time warping, is proposed for identifying the source buildings with the most similar energy features to the target building. Then, transfer learning for long-term prediction air-conditioning energy consumption is developed with weather parameters generated by the Morphing method as inputs. For the short-term single-step prediction, the proposed model CV-RMSE improves 81.3% (AEC) and 77.4% (EEC), respectively, compared to the prediction model that does not implement the transfer learning strategy and directly uses the target BEC data. As for the short-term multi-step prediction, the proposed model CV-RMSE improves 62.0% (AEC) and 65.5% (EEC), respectively. For the long-term prediction, the average CV-RMSE for the whole year is 6.62% and 11.15% for the proposed and directly target domain-based model, respectively. The proposed method explores the practicality of transfer learning in building energy forecasting, contributing to the use of existing building operation data for energy management at different timespan.

Influence of the shading nets on indoor thermal environment and air-conditioning energy consumption in lightweight buildings

Lightweight envelopes are increasingly utilized in temporary relief and shelter buildings, due to their cost-effectiveness and efficient construction process. However, these envelopes often result in inadequate indoor thermal conditions during the summer months, which can negatively impact the physical and psychological well-being of occupants, particularly victims and patients in disaster or epidemic situations. Addressing this challenge necessitates the use of simple yet effective materials and technologies to improve indoor thermal environments even with limited resources. This study explores the potential of shading nets to enhance indoor thermal conditions in lightweight buildings by mitigating solar radiation gain during the summer period. A comparative experiment was conducted on two lightweight buildings, one of which was equipped with standard six-needle black shading nets, to assess the impact of shading nets on the indoor thermal environment and air-conditioning energy consumption. The findings reveal that shading nets can reduce solar radiation intensity by approximately 57.86%, resulting in a significant decrease in peak indoor air temperatures by 2.3°C to 3.4°C under natural ventilation and a reduction in air-conditioning energy consumption by up to 23% under air-conditioned conditions. These findings demonstrate that shading nets are effective in improving indoor comfort and reducing energy usage, providing a practical solution for enhancing living conditions in lightweight structures during hot weather.

Machine learning-based predictive model for thermal comfort and energy optimization in smart buildings

In the current context of energy transition and increasing climate change, optimizing building performance has become a critical objective. Efficient energy use and occupant comfort are paramount considerations in building design and operation. To address these challenges, this study introduces a predictive model leveraging Machine Learning (ML) algorithms. The model aims to predict thermal comfort levels and optimize energy consumption in Heating, Ventilation, and Air Conditioning (HVAC) systems. Four distinct ML algorithms Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), and EXtreme Gradient Boosting (XGBOOST) are employed for this purpose. Data for the model is collected using a network of Raspberry Pi boards equipped with multiple sensors. Performance evaluation of the ML algorithms is conducted using statistical error metrics, including, Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R2). Results reveal that the RF and XGBOOST algorithms exhibit superior performance, achieving accuracies of 96.7 % and 9.64 % respectively. In contrast, the SVM algorithm demonstrates inferior performance with a R2 of 81.1 %. These findings underscore the predictive capability of the RF and XGBOOST model in forecasting Predicted Mean Vote (PMV) values. The proposed model holds promise for enhancing occupant thermal comfort in buildings while simultaneously optimizing energy consumption in HVAC systems. Further research could explore the practical applications of these findings in building design and operation.

Thermochromic Hydrogels with Adjustable Transition Behavior for Smart Windows.

With the fast economic development and accelerating urbanization, more and more skyscrapers made entirely of concrete and glass are being constructed. To keep a comfortable indoor environment, massive energy for air conditioning or heating appliances is consumed. A huge amount of heat (>30%) is gained or released through glass windows. Using smart windows with the capability to modulate light is an effective way to reduce building energy consumption. Thermochromic hydrogel is one of the potential smart window materials due to its excellent thermal response, high radiation-blocking efficiency, cost-effectiveness, biocompatibility, and good uniformity. In this work, polyhydroxypropyl acrylate (PHPA) hydrogels with controllable lower critical solution temperature (LCST) were prepared by photopolymerization. The transition temperature and transition rate under "static transition" conditions were investigated. Unlike "static" conditions in which the transition temperature was not affected by the initial and final temperature and heating/cooling ramp, the transition temperature varied with the rate of temperature change under dynamic conditions. The "dynamic" transition temperature of the PHPA hydrogel gradually increased with the increase of the heating rate. It was the result of the movement of the molecular chains lagging behind the temperature change when the temperature change was too fast. The results of the solar irradiation experiment by filling PHPA hydrogels into double glazing windows showed that the indoor temperature was about 15 °C lower than that of ordinary glass windows, indicating that it can significantly reduce the energy consumption of air conditioning. In addition, a wide range of adjustable transition temperatures and fast optical response make PHPA hydrogels potentially applicable to smart windows.

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.

Enhancing building envelopes: Parametric analysis of shading systems for opaque facades and their comparison with cool paints

Heat gain through the buildings opaque facades significantly contributes to the energy consumption of Heating, Ventilation, and Air Conditioning (HVAC) systems. In the post-construction phase, retrofitting options for reducing façade heat gain are limited, with cool paints being the prevalent strategy. However, the efficacy of shading systems as an alternative strategy remains underexplored as existing research predominantly focuses on proof-of-concept validation, often overlooking a comprehensive assessment of shading system configurations across diverse climates and building typologies. Moreover, a comparative analysis of the performance and potential synergies between cool paints and shading systems on opaque facades is crucial to understand their actual effectiveness in real-world applications. To address these gaps, our study undertakes an extensive parametric simulation, taking into account variables such as shading configurations, cool paints with varying facade solar absorbance values, facade orientation, diverse climates, and different building typologies. The results demonstrate that the use of shading on opaque facades alone could result in a HVAC energy saving of 8–28 %, while the application of cool paints (façade absorptance value of 0.2) alone could reduce the HVAC energy consumption by 10–35 %. By combining the use of shading and cool paints, the HVAC energy savings are further increased by 2–5 %. The findings of this study offer a novel perspective on the selection of opaque façade technologies, broadening the sustainable design and retrofit options.

The emission reduction potential and cost-effectiveness of low-GWP refrigerants in electric vehicle air conditionings

Electric vehicles play a crucial role in the carbon neutrality transformation of urban transportation, provided that they are powered by electricity generated from renewable (rather than fossil-based) generation sources. However, the substantial indirect emissions from electric vehicle air conditioning energy consumption and the significant direct emissions from HFCs (hydrofluorocarbons) refrigerants pose considerable challenges. In order to identify low-GWP (global warming potential) refrigerants -such as R1234yf, R744, and R290 - that can effectively minimize carbon emissions while maintaining certain cost-effectiveness, this paper establishes the relevant life-cycle analysis and life-cycle cost analysis models for electric vehicle air conditioning. The results obtained show that, in 2022, the total carbon emissions of China’s automotive air conditioning fleet were approximately 162 million tons CO2-eq. The nationwide average carbon emissions ranking of various refrigerant heat pumps is R290 < R1234yf < R744 < R134a. The Net Present Value (NPV) of the life cycle cost for R134a electric vehicle heat pump is estimated to be around 11,500 yuan. Among the three low-GWP refrigerants, the life cycle cost of R290 is significantly lower than that of R134a under nationwide average conditions, while R744 exhibits the best life cycle performance in certain cold cities/regions.

One-dimensional photonic crystal with tilted termination and its angular filtering properties for radiative cooling.

Photonic crystals are known for their band-gap structures. Due to their band-gaps, they can act as filters in both temporal and spatial domains. However, in most cases, due to their physical symmetry, their angular responses are symmetrical. Here, a structure based on a 1D photonic crystal is introduced and analyzed, which has an asymmetric angular selectivity. The structure is analyzed using the plane wave expansion method. The properties of the structure are expressed and verified by a commercial full-wave simulator software. Based on the analysis and its results, some simple design rules are derived. By using the extracted rules and some approximations, the potential of the structure to be used in radiative coolers, which are not completely toward the sky, is introduced. It is shown that if the structure is used as windows in buildings, it can save up to tens of watts per square meter in energy consumption for air conditioning. Finally, the whole structure including the radiative cooler is simulated, and the results support the calculations and approximations.

Irrigation and Thermal Buffering Using Mathematical Modeling

Two methods of irrigation, drip, and sprinkler were studied to determine the response of the Javits green roof to irrigation. The control study was dry unirrigated plots. Drip irrigation consisted of irrigation tubes running through the green roof that would water the soil throughout and sprinkler irrigation used a sprinkler system to irrigate the green roof from above. In all cases, the irrigated roofs had increased the soil moisture, reduced temperatures of both the upper and lower surfaces, reduced growing medium temperatures and reduced air temperatures above the green roof relative to the unirrigated roof. The buffered temperature fluctuations were also studied via air conditioner energy consumption. There was a 28% reduction in air conditioner energy consumption and a 33% reduction in overall energy consumption between dry and irrigated plots. Values of thermal resistance or S were determined for accuracy and for this study, there was little change which is ideal. A series of infra-red and thermal probe measurements were used to determine temperatures in the air and sedum. It was determined that the sprinkler irrigation did a better job than the drip irrigation in keeping cooler temperatures within the green roof. A Mann-Whitney U test was performed to verify the variation in moisture temperatures buffering energy consumption. By getting a p-value < 0.05, it indicates that the model is accurate for prediction and medium temperatures were statistically different.

Annual analysis and comparison of the comprehensive performance of a CdTe PV ventilated window integrated with vacuum glazing in different climate regions

In this paper, a CdTe photovoltaic double-skin ventilated window integrated with vacuum glazing (VPV-DSV) is proposed. The mathematical model of VPV-DSV was developed and validated through tests in Hefei, China. Annual energy performance and the economic analysis of the VPV-DSV was evaluated and compared with the other two PV-DSVs and an insulating glazed window (IG) under climate conditions of five selected cities, including Changchun, Hefei, Kunming, Shenzhen, and Shijiazhuang. Moreover, effects of window design factors, including the window-to-wall ratio, PV coverage, and pillar spacing of the VG, were explored. Results indicated that: (1) the VPV-DSV produced the best energy saving results and the least energy consumption. (2) NECs of the VPV-DSV in the five cities above was 955.05 kW•h, 464.31 kW•h, 110.66 kW•h, 53.71 kW•h, and 443.14 kW•h, respectively. (3) Due to high cost of the VG, the VPV-DSV only had the best economic performance in Shenzhen and the NPV was 3931.47 CNY. (4) The WWR and PV coverage had obvious impacts on the overall performance of the VPV-DSV, while the pillar spacing only had a more significant impact on the air conditioning energy consumption.

Trade-Off Judgement for Daylighting and Energy Consumption in the High and Large Space of the University Gymnasium in Beijing

Taking the high and large space of the University of Science and Technology Beijing Gymnasium as this research object, this paper analyzes the influence of different window positions, window-to-wall ratio (WWR), solar heat gain coefficient (SHGC), heat transfer coefficient (K), and visible light transmittance (VT) on the total indoor energy consumption in winter and summer and obtains the relationship between the daylight factor and VT formed when the window is opened per unit area. Through energy consumption simulation, the variation law and calculation formula for indoor total energy consumption are obtained. The results show that the SHGC and K of the exterior window have a significant influence on the total energy consumption. By using the energy consumption simulation of different types of exterior windows, it is concluded that the SHGC of the south-facing window is negatively correlated with the variation of air conditioning energy consumption per unit area Δe1,w, while the others are positively correlated. Moreover, the SHGC and K of the skylight have the most significant influence on the Δe1,w. The total energy consumption decreases and then increases with the increase in the window area, and there is a lowest point, so the right side of the lowest point is less than or equal to 105% of the lowest total energy consumption as a reasonable window area zone. Finally, a progressive optimization method for weighing daylighting and energy consumption in university gymnasiums in Beijing is proposed.

Daylight and energy performance of side lighting systems in an office room in a subtropical climate

In office buildings, daylight is an important natural resource, as it is profusely available during occupied hours. However, its use can increase energy consumption for air conditioning. Therefore, combining this resource with side lighting systems and promoting its integration with electric lighting is essential to obtain an energy balance. This paper aims to analyze daylight performance and the energy consumption for lighting and air conditioning considering four types of glazing, four orientations, from window-to-wall ratios varying between 40% to 100% for bare and shaded window models in an office room located in a subtropical city in southern Brazil. The methodology was based on Useful Daylight Illuminance levels of 500 to 2,500 lx, Daylight Autonomy levels of 500 lx, and total energy consumption through simulation in DesignBuilder software. The results showed that L13 glazing is not recommended for bare and shaded windows, regardless of window orientation. M76 presented the best performance for energy consumption for West shaded windows. For the West, shading is necessary irrespective of the glazing type (except L13, whose best performance is for bare windows) from WWR 50%. M76 and M52 had the lowest total energy consumption. The findings of this study add to an understanding of the energy savings and lighting performance of different types of glazing, combined with window apertures, and solar orientations for a subtropical climate. Furthermore, the study shows that the choice of glazing depends not only on the presence of shading but also on the orientation and WWR, without a linear behavior.

Research on Energy Consumption Model of Heat Pump Air Conditioning System for New Energy Vehicles Based on Digital Technology

Energy shortages and environmental degradation are issues that are getting more and more significant globally. New energy vehicles are being promoted by the state due to the advantages of low pollution and low fuel consumption. However, due to battery technology, the range of new energy vehicles cannot meet the needs of users. As the most energy-efficient auxiliary device, the energy consumption of air conditioning will significantly reduce the range of new energy vehicles. In low temperature environments, heating energy consumption will reduce the range of vehicles by more than 50%. Therefore, the research aims to reduce the energy consumption of air conditioning systems in new energy vehicles by reducing load demand and improving operating efficiency. The study designs a low-temperature heat pump air conditioning system based on digital technology and then uses a computational algorithm to construct an energy consumption model for the heat pump air conditioning system of a new energy vehicle. According to the test results, the system’s average increase in heat production after activating the enthalpy charge is 35% and its average COP is 0.14% lower than when switched off. At -5oC, the air outlet temperature of the system reaches up to 50.0oC. Summer cooling energy consumption increases exponentially with temperature, while winter heating energy consumption decreases linearly with temperature. In addition, the range decreases significantly as the ambient temperature deviates from the human comfort zone. The decline in the winter range is more severe than that in summer, moreover, the range of modern energy vehicles is reduced by 30% at an average winter temperature of -10oC. In summary, the low-temperature heat pump system offers greater performance. It is more useful in real-world applications and can offer a rational alternative to air conditioning’s energy-saving tactics.

Optimization control strategy for mixed-mode buildings based on thermal comfort model: A case study of office buildings

Mixed-mode (MM) buildings reduce air conditioning (AC) energy consumption while maintaining indoor thermal comfort through the appropriate use of natural ventilation (NV). The objective of this investigation was to propose a method to determine the best NV operation range suitable for MM buildings and further to propose a change-over control strategy. First, the usual natural ventilation operating range (NV-range) was obtained based on the upper and lower comfort temperature limits of the adaptive comfort model. The usual NV-range was extended by adding threshold conditions, and then, it was divided into nine natural ventilation operation subranges (NVOSs). Second, the comfort and energy performance of each NVOS were analyzed through a co-simulation for an MM office building in Xi'an, China, as an example to obtain the optimal NV-range for the local climate. The results showed that the proposed optimal NV-range reduced the number of discomfort hours by 248.33 h while increasing the energy savings by 13.29% compared to those of the commonly used NV-ranges. Finally, the control scheme with the adaptive comfort model changed to the PMV model (ACM-PMV-CS) with the addition of a 1.5-h transition period was proposed in order to solve the problem of using the steady-state PMV model directly in the AC mode under the frequent switching conditions between the NV and AC modes. The results showed that ACM-PMV-1.5 h transition period resulted in a reduction in the number of discomfort hours (248.33 h) and a 35.46% increase in the energy savings compared to those of ACM-PMV-CS without a transition period.