Air Conditioning Load Research Articles

Deviation of design air-conditioning load based on weather database of reference weather year and actual weather year

Abstract In Japan, in order to determine the capacity of air-conditioning equipment, designers usually use the weather database of Reference Weather Year (RWY) to obtain the design air-conditioning load by using software such as New HASP/ACLD and Building Energy Simulation Tool (BEST) that are often used in Japan. In recent years, with the global warming due to climate change, the weather database used to calculate air conditioning load also changes. Thus, in order to determine an appropriate capacity of air-conditioning equipment for energy conservation of buildings, the deviation of design air-conditioning load calculated using the weather database of RWY and Actual Weather Year (AWY) should be discussed. In this paper, New HASP/ACLD was used to calculate the building heat loads of eight major Japanese cities over 30 years (1981–2010) between RWY and AWY. The heat load at an exceedance probability of 2.5% is defined as the design air-conditioning load in this paper. Comparing the design air-conditioning load obtained from RWY and AWY, it is shown that it is not necessarily the most appropriate when using the RWY to calculate the design air-conditioning load, especially for heating load in winter. Additionally, it is also shown that the annual heating load time ratio has decreased and the annual cooling load time ratio has increased over the 30 years.

Improving power quality efficient in demand response: Aggregated heating, ventilation and air-conditioning systems

This study aims to identify the role of aggregated heating, ventilation, and air conditioning (HVAC) loads based on system characteristics using the lazy state switching control mode focusing on the overall power consumption rather individual response speed. This study is attempted to provide secondary frequency regulation using aggregated HVAC loads with more stable operation with the lazy state switching control mode based on conditional switching of the HVAC unit’s working state. The stability of power consumption improves power quality in smart grid design and operation. The aggregated HVAC must reach a stable condition before tracking the automatic generation control signal and fully developed smart grids complex structure. Still, HVAC slowed responses make inappropriate for faster demand response services. Unsuitable control algorithm leads to system instability and HVAC unit overuse. An extended command processing on the client side is proposed to deal with the adjusting command. The unique advantages of the proposed algorithm are three folds. (1) the control algorithm preserves its working state and has nothing conflicting with the lockout constraints for individual system units; (2) the control algorithm shows promising performance in smoothing the overall power consumption for the aggregated population; and (3) the control logic is fully compatible with other control algorithms. The proposed modeling and control strategy are validated against simulations of thousands of units, and the simulation result indicates that the proposed approach has promising performance in smoothing the power consumption of aggregate units’ population.

Occupant-centric miscellaneous electric loads prediction in buildings using state-of-the-art deep learning methods

Buildings have emerged as one of the dominant sectors when it comes to worldwide energy consumption. While a large portion of this consumption is due to the Heating, Ventilation, and Air Conditioning (HVAC) loads, a significant portion is contributed through the use of standard equipment, also known as Miscellaneous Electric Loads (MEL). It is necessary to understand the consumption patterns to optimize the MELs of the occupants using the building and conduct accurate forecasts for building energy management. One of the methods to achieve that purpose is the employment of Deep Learning (DL) methods. This study provides an analysis using Long Short-Term Memory (LSTM) model as a baseline for predicting MELs. The predictions were conducted for a day-ahead and a week-ahead period. Furthermore, the results from the baseline model were then used in a comparative analysis with two other state-of-the-art DL models; Bidirectional Long Short-Term Memory (Bi-LSTM) and Gated Recurrent Units (GRU).The results from this study showed that both the Bi-LSTM and GRU models were significantly better than the LSTM model, especially when the prediction horizon was longer. The conclusions obtained can help implement these models in building energy management systems to draft strategic responses and schedules for more efficient energy usage.

Thermal and energy performance of green roof and cool roof: A comparison study in Shanghai area

Green roofs and cool roofs are commonly used to improve indoor thermal environment, reduce air-conditioning load and mitigate the Urban Heat Island (UHI) effect. This study aimed to quantify the differences in thermal and energy performance between the two different roof types under the climate of Shanghai. Firstly, field experiment was conducted in the Shanghai area. Thermal performance of green roof, cool roof and common roof in summer and winter were measured. Results showed that, compared to common roof, the cool roof had an average cooling effect of 3.3 °C on the outer roof deck surface in summer, while the green roof only had a cooling effect of 2.9 °C. In winter, the green roof provided good insulation, and could improve outer surface temperature of the roof deck by an average of 3.3 °C compared to the cool roof. A hygrothermal transfer model for green roof was coupled with a dynamic building thermal performance simulation software (THERB) and validated using measured data. The coupled model was used to predict the effect of both roof types on energy performance of a public building. Simulation results showed that green roof could reduce the cooling and heating loads of the top floor by 3.6% and 6.2%, respectively. The cool roof could reduce cooling load by 3.6% and increase heating load by 10.4%. Finally, a parametric analysis was implemented. The functional mechanism of the main parameters of green and cool roof as well as their impacts on thermal and energy performance of public buildings were analyzed in detail. Conclusions drawn from this paper could provide guidance for the design optimization and application of green roof and cool roof in Shanghai area.

The Effect of Thermal Insulation on Cooling Load in Residential Buildings in Makkah, Saudi Arabia

Buildings consume huge amounts of electrical energy in the Kingdom of Saudi Arabia, particularly during the summer months, due to the enormous air conditioning demands created by very hot outdoor temperatures. Residential buildings consume more than half of the electricity used in Saudi Arabia, with the air conditioning load making up 70% of this use. The main aim of this study is to evaluate the thermal performance of two mid-rise residential buildings in Makkah, Saudi Arabia. These buildings are five floors in height and have the same orientation, but the first building is thermally insulated, while the second building is not. To investigate the indoor thermal performance of the two buildings, physical measurements were taken during May 2019. The data gathered included indoor air temperature values as recorded every fifteen minutes for a period of sixty-eight hours in two equivalent rooms in each building. Analysis of site monitoring data was conducted, and the results obtained offer a better idea of the effectiveness of the existing building fabric characteristics, in particular external walls and rooves, in relation to indoor thermal performance. These data were calibrated with simulated results taken from thermal analysis software (TAS) to validate them and to thus quantify the cooling load in the case study buildings. The outcomes illustrate the similarity between the measured and simulated results and as well as indicating that thermal insulation can decrease cooling loads by to up to 50%.

ToU Tariff Effect on Domestic Electricity Patterns- Australian Case Study

This article shows an evaluation of a ToU network tariff test on Australian domestic electricity customers. The test was with 444 domestic electricity customers in Tasmania, Australia. This Australian case has international implications for energy policy and regulation. Australia has the world’s highest domestic PV (photovoltaic system) adoption and combining this with high air-conditioning and water heating load leads to high diurnal variation and an emerging issue globally. Related issues include over-voltage. Thermal overload, frequency instability and voltage instability. The method was a statistical analysis of the energy use patterns using k-means clustering, and then stepwise regression to find drivers of energy reduction behaviour. There were also tests on the effect of weather and seasonal effect. The conclusions are that there was strong response from 4% of customers, and moderate response from 15%. There was a stronger response in households that were drawing more electricity and were wealthier than the average households.

Calculating the winter base load and AC load in Chongqing considering the correlation of temperature and power system load

The widely use of air conditioning (AC) equipment have brought a large amount of AC load to the power grid, which has an increasingly impact on the safe and economic operation of the power system. In order to correctly estimate the scale of AC load, this paper proposes a new winter AC load calculation method considering the correlation of temperature and load. Firstly, abnormal temperature days (ATD) are removed from the set of representative days (RD) by calculating the correlation coefficient of temperature and load in RD screening process. Secondly, taking into account the daily growth of the base load, the regression analysis is used to fit the base load curve for each day in winter. Then the spring festival (SF) coefficient is proposed to modify the system base load in SF because power system load decreases dramatically during SF. Finally, the winter AC load is equal to the difference between winter power system load and winter base load. The winter AC load in Chongqing 2018 is calculated using the pro-posed method and the result shows the effectiveness of this method.

Thermal behavior analysis of hollow bricks filled with phase-change material (PCM)

Light-weight materials are comprehensively used to reduce the building weight in high-rise or super high-rise buildings, but they will reduce building thermal inertia remarkably, which can increase the air-conditioning load fluctuation and reduce indoor thermal comfortable. According to this condition, phase-change material (PCM) is filled to hollow bricks to improve thermal behavior by latent thermal storage. A numerical model with the heat transfer process of melting-solidifying was built, and a full-scale experiment was done to verify this model. Due to the filled PCM, the thermal performance of hollow bricks was improved obviously from experimental and numerical results. Under suitable phase-change temperature, the filled PCM can reduce the attenuation rate from 13.07% to 0.92%–1.93% and increase the delay time from 3.83 h to 8.83h–9.83 h. Meanwhile, the filled PCM can reduce the peak heat flux from 45.26 W/m2 to 19.19 W/m2-21.4 W/m2, but cannot reduce the average value. In addition, inner cavities were the better choice for PCM and there was an extra phase-change extent of close to 90% in favor of the different outdoor thermal environment. Finally, influence rules of latent heat and thermal conductivity coefficient of PCM were analyzed on temperature and heat flux in inner surfaces.

Modeling and Forecasting End-Use Energy Consumption for Residential Buildings in Kuwait Using a Bottom-Up Approach

To meet the rapid-growing demand for electricity in Kuwait, utility planners need to be informed on the energy consumption to implement energy efficiency measures to manage sustainable load growth and avoid the high costs of increasing generation capacities. The first step of forecasting the future energy profile is to establish a baseline for Kuwait (i.e., a business-as-usual reference scenario where no energy efficiency incentives were given and the adoption of energy efficient equipment is purely market-driven). This paper presents an investigation of creating a baseline end-use energy profile until 2040 for the residential sector in Kuwait by using a bottom-up approach. The forecast consists of mainly two steps: (1) Forecasting the quantity of the residential energy-consuming equipment in the entire sector until 2040 where this paper used a stock-and-flow model that accounted for the income level, electrification, and urbanization rate to predict the quantify of the equipment over the years until 2040, and (2) calculate the unit energy consumption (UEC) for all equipment types using a variety of methods including EnergyPlus simulation models for cooling equipment. By combining the unit energy consumption and quantity of the equipment over the years, this paper established a baseline energy use profile for different end-use equipment for Kuwait until 2040. The results showed that the air conditioning loads accounted for 67% of residential electrical consumption and 72% of residential peak demand in Kuwait. The highest energy consuming appliances were refrigerators and freezers. Additionally, the air conditioning loads are expected to rise in the future, with an average annual growth rate of 2.9%, whereas the lighting and water heating loads are expected to rise at a much lower rate.

Based on Calculation and Analysis of the Influence of External Atmospheric Temperature on Air-conditioning System of Floating Nuclear Power Plant at Sea

External atmospheric temperature is the design input of air-conditioning system of the floating nuclear power plant at sea, which affects the calculation of heat load and air supply volume of air conditioner. The typical cabin A of the floating nuclear power plant is selected. The external atmospheric temperature selection range is obtained by comparing different standard specifications and references. The single variable method is adopted, and the external atmospheric temperature is used as the variable factor. The calculation and comparison of the air volume and cooling capacity of the typical cabin A should be made. The analysis and calculation results show that the external atmospheric temperature has little influence on the air volume of the cabin A air conditioning system, and has a great influence on the cooling influence of the external atmospheric temperature on the air conditioning system of the floating nuclear power plant and the variation of the energy consumption are obtained, along with eth external atmosphere. With the increase of temperature, the energy consumption of air conditioning system increases almost linearly. From the perspective of economics, it is concluded that the increase of energy consumption of air conditioning system will reduce the economic benefits of floating nuclear power plants at sea.

An Al2O3-cellulose acetate-coated textile for human body cooling

The development of a textile that cools skin both in sunshine and in room can not only protect the human body from a severely hot working environment but also save energy by lowering air conditioner load. Herein, we have developed a concept that combines solar energy reflection and “passive radiative cooling” for strengthening both solar energy blocking and heat dissipation through long-wave infrared (LWIR) radiation at wavelengths of 8–13 μm. The current technique is achieved by coating a textile with an Al2O3 dispersed-cellulose acetate. Cellulose acetate possesses high emissivity in the LWIR region, which can promote effective LWIR radiation (2.5–25 μm). Al2O3 has a high thermal conductivity (30–40 W m−1 K−1) and can enhance solar energy reflectivity. By coating Al2O3-cellulose acetate, solar energy reflectivity of the textile significantly increases from 62.6% to 80.1% (0.3–2.6 μm). A cooling performance experiment reveals that this modified textile can reduce the temperature of simulated skin by 2.3–8 °C compared to that of an unmodified reference. Furthermore, in a real-life cooling performance experiment, a modified T-shirt can avoid the overheating of actual human skin by 0.6–1.0 °C, corresponding to a temperature decrease by 1.9–3.3 °C for the internal surface of the textile. This work provides a method for the design and synthesis of radiative cooling textiles for personal thermal management.

Characterization of cooling loads in the wine industry and novel seasonal indicator for reliable assessment of energy saving through retrofit of chillers

The food sector is a major consumer of energy and growing efforts are being made in the search for solutions that will guarantee the efficient and sustainable use of energy resources. Among the different sectors, wineries are attracting particular interest due to the continuous growth of the global market and production. Surveys conducted in the winemaking sector have highlighted the importance of performing accurate energy audits and have identified the installation of efficient refrigeration systems as a promising solution in a variety of cases. Unfortunately, the savings achievable by efficient cooling technologies are often estimated using simplified approaches which do not take into consideration the actual operating conditions of the equipment typically variable on seasonal and daily bases. In this paper a novel bottom-up procedure is presented, aimed at developing reliable profiles for refrigeration and air-conditioning loads and at assessing the extent to which more efficient chilling units could contribute to reducing electricity consumption. The use of standard Seasonal Energy Efficiency Ratios is critically discussed and a novel customized indicator is proposed. The method is applied to a medium-scale winery producing still red and white wines and sparkling wines, for which only aggregated energy consumption data are available. After deriving detailed load profiles, it is proven that the use of standard seasonal indicators leads to 56.85% and 83.87% overestimation of potential energy savings, respectively, for low and medium temperature cooling energy uses, confirming the importance of adopting seasonal indicators customized on the actual operating conditions of chillers.

Warm climate performance of water-filled double-glazing with submerged heat exchanger

Water-filled double-glazing is a new design in water-flow window technology. With a horizontal heat-transfer tubing dipped at the top end of the water layer in the window cavity, the absorbed solar heat is directly passed onto the domestic water heating system. The design avoids water-tube insertion at the high-pressure region, and hence minimizes the water leakage risk. Its warm climate application helps to reduce the year-round domestic water heating and air-conditioning loads. This paper reports the application of the dynamic simulation model of this new design. The validated model was used to evaluate its energy performance at different tropical and subtropical cities worldwide. The numerical results show that the 24 -h thermal efficiency is in the range of 26%–51% in the selected cities, mainly depending on the seasonal variation in ambient temperature. The degree of electricity saving in air conditioning will depend on the actual site location and the building activity. This innovative technology has wide application potential in zero-energy buildings.

Matching Characteristic Research of Building Renewable Energy System Based on Virtual Energy Storage of Air Conditioning Load

Considering the huge power consumption, rapid response and the short-term heat reserving capacity of the air conditioning load in the building’s energy system, the air conditioning load and its system can be equivalent to the virtual energy storage device for the power grid. Therefore, to obtain a high matching building renewable energy system, a virtual energy storage system of the air conditioning load, accompanied by a storage battery, was built in the paper. Then, operating strategies for the virtual energy storage of the air conditioning load and storage battery were designed. Further, to quantize the contribution of the virtual energy storage to the improvement of matching characteristics, two indicators of the demand side and supply side in the energy system were adopted, including on-site energy fraction (OEFr) and on-site energy matching (OEMr). Lastly, matching characteristic research of the building’s renewable energy system based on virtual energy storage of the air conditioning load was established and analyzed by TRNSYS and MATLAB in Tianjin, China. The results revealed that a better matching characteristic performance of the building’s renewable energy systems driven by virtual energy storage was obtained. In the condition set out in the paper, compared with that without virtual energy storage, the average values of OEFr and OEMr after virtual energy storage were 0.66 and 0.77, which increased by 8.19% and 8.45% respectively. Simultaneously, the battery operation performance in the building renewable system was improved when the virtual energy storage was working. The times of charge and discharge cycles decreased after virtual energy storage, and the depth of discharge of the battery reduced by 23.37% on a specific day.

Vertical Temperature Profiles and Cooling Load in Large Spaces Ventilated by Stratified Air-Conditioning Systems: Scale-Model Experiment and Nodal Modeling

Abstract An improved heat balance nodal model is proposed to predict the inner wall temperature profiles and calculate the stratified air-conditioning load in large spaces. The model aims to weaken the correlation between load calculation methods and indoor airflow patterns, and to ensure the synchronization of each heat transfer process, so as to be closer to actual situations. The scale-model experiments were conducted in an enthalpy different laboratory in University of Shanghai for Science and Technology (USST) in Shanghai, China. This paper took the air distribution of nozzle air supply system as an example to calculate the inner wall temperatures and the stratified air-conditioning load by the nodal model and verified by the scale-model experiments. The results showed the maximum deviations of the experimental and theoretical values for the inner wall temperatures, the heat transfer load from the nonair-conditioned (NAC) area and the stratified air-conditioning load were all within 5%. The effects of the air temperature in the NAC area on the heat transfer load from the NAC area and the stratified air-conditioning load were analyzed, and the load nomogram was produced. It was found the heat transfer load from the NAC area accounted for 10–30% of the stratified air-conditioning load. The load nomogram compared two methods for determining the air temperature in the NAC area and gave the recommended one. The findings in this paper can be used to further develop load calculation models for non-uniform thermal environments.

State-shift priority based progressive load control of residential HVAC units for frequency regulation

The high penetration combined with the intermittent nature of large-scale distributed generation challenges the stability of power systems. Recently, it has been proposed that thermostatically controlled loads, such as heating, ventilation and air conditioner (HVAC) loads, can be controlled to provide efficient and effective frequency regulation (FR) service with a minimum impact on consumers’ comfort compared to the costly conventional spinning reserve. This paper proposes a progressive load control strategy which enables residential HVAC loads to implement primary and secondary frequency regulation. In particular, a state-shift priority approach is proposed to efficiently choose responsive loads and avoid frequent activations of load control. A state-shift time based random recovery approach is developed to mitigate load rebound after the control period. With the proposed load control strategy, the aggregation of HVAC units can behave like a synchronous generator to provide FR service. As a result, the required spinning reserve can be reduced. The dynamic simulation results indicate that HVAC units can provide a reliable and smooth FR service quickly via the proposed progressive load control strategy based on state-shift priority.

Virtual energy storage model of air conditioning loads for providing regulation service

As the pressure of supply–demand balance increases with the high penetration of renewable energy resources, it is widely accepted that demand side resources including air conditioners (ACs) play an important role in providing ancillary services to the grid. In this paper, air conditioning loads are modeled as a kind of virtual energy storage device based on their inherent thermal storage capacity. It is investigated that air conditioning loads can provide regulation service with certain storage power output and ramping rate limits as a result of minimum on/off time requirements. Simulation studies demonstrate the effectiveness of the proposed method by coordinating ACs to track a regulation signal.

Applicability of rotary thermal wheels to hot and humid climates

Buildings in hot and humid climates spend more than 60% of the total energy cost for Air Conditioning and Mechanical Ventilation Systems (ACMV) to maintain the required thermal comfort for occupants. The required air conditioning load drastically increases with the fresh air demand of the conditioned space which leads to excessive energy bills for central air conditioning systems of buildings, particularly in hot and humid climates. Therefore, this study mainly focuses to investigate and evaluate the applicability of rotary thermal wheel to recover the energy available on the return air of the air handling unit (AHU) of the central air conditioning systems in hot and humid climates. The results reveal that, the percentage energy saving due to the rotary thermal wheel increases when the temperature and the relative humidity of outdoor fresh air increases, and also when Coefficient of Performance (COP) of the central chiller decreases. Moreover, case studies show that the simple payback period of a building which is supplied with 20% fresh air varies from 1.1 years to 4 years depending on the fresh air mass flow rate. Results reveal that the use of rotary thermals in the hot and humid climates is highly recommended.

Air-Conditioning Load Forecasting for Prosumer Based on Meta Ensemble Learning

Accurate and reliable prediction of air-conditioning load plays a significant role in prosumer energy management system (EMS), because air-conditioning load accounts for a large proportion of the building's total energy consumption. This paper proposes a new meta ensemble learning method to realize short-term prediction of air-conditioning load for prosumers. This method is a hybrid of meta ensemble learning and stacked auto-encoder (SAE). First, we design multiple different forecasting structures based on SAE to achieve point prediction of air-conditioning loads. SAE is used to learn the deep features in air-conditioning load data. Second, a new meta ensemble learning prediction model is proposed. Meta ensemble learning is used to learn the nonlinear features and invariant structures in data, and determine the coefficients of each SAE-based point forecaster. Finally, the prediction results of each point forecaster are aggregated and integrated to estimate the final air-conditioning load prediction result. Air-conditioning load data from a commercial building in Singapore are used to validate the feasibility and effectiveness of the proposed method, demonstrating that the proposed meta ensemble learning method is attractive in prosumer energy management.

Fuzzy Logic-Based Direct Load Control Scheme for Air Conditioning Load to Reduce Energy Consumption

A huge body of research is concentrated on developing advance load control strategies for reducing energy consumption and ensuring smooth operation of power system. Air conditioning loads are considered major energy consuming electrical loads in residential and business buildings, and that may cause significant rise in energy consumption. This paper presents an implementation of fuzzy controller with different number and shapes of membership functions for smoothing energy consumption of an air conditioning load while dealing with thermal disturbances. Simulations are conducted in MATLAB Simulink and the results demonstrate that the fuzzy controller with triangular membership function gives the desired performance with an error of less than 1% and saves 25% energy consumption. The obtained results are found effective in terms of smoothing energy consumption pattern of an air conditioning load without compromising consumer' s comfort. Performance of the designed controller is also compared with different controllers including self-tuning adaptive fuzzy controller, linear quadratic regulator (LQR) and nonlinear controllers. The presented fuzzy controller stands-out in terms of desired performance, simplicity and implementation.