Temperature Set Point Research Articles

스마트팜 적용 피복재의 시험을 통한 성능평가 및 냉방부하 분석

The thermal performance database of the covering material which can be used as input data for the smart farm cooling load simulation performance evaluation was analyzed through the test evaluation. Methods: The solar heat gain coefficient of the covering materials (PE, PMMA, PC double layer, woven film) was compared and analyzed through the Korean standard test method and input data was derived. Based on the thermal input data, the cooling load simulation of smart farm was conducted and the simulation performance evaluation of each case was performed to analyze how the indoor cooling load changes by covering materials. Results: The cooling load of the PC double layer was the lowest at 424 W/㎡, and the PE film was the highest at 559 W/㎡. The coefficient of heat transmission was 3.7 W/㎡ ·K~6.7 W/㎡ ·K for each covering materials, and the solar heat gain coefficient was evaluated as 54%~90% visible transmittance was 50%~88%. The cooling load of the PC double layer and PE film showed a difference of 135 W/m2(24%), indicating that the selection of the coating material greatly affects the cooling load. The cooling load was reduced by 25.3% when the cooling setpoint temperature was controlled, and the cooling load was reduced by 35.8% when the internal shading rate was applied by 60%.

A photovoltaic forced ventilated façade (PV-FVF) as heat source for a heat pump: Assessing its energetical profit in nZEB buildings

The European Union is changing its energy model towards a more efficient and sustainable one. In this new outlook, the Heat Pump (HP) has become a leading technology in the building energy sector. The use of the air source heat pump (ASHP) in the energy installations in the so-called nZEB low consumption buildings is currently on the increase. Furthermore, its performance improves when supported by solar energy, which can be achieved through the use of hybrid solar thermal photovoltaic elements (BIPV/T) integrated into the building’s façade, thus reducing consumption by 9 or 10%. However, the improvement can be even higher if a thermal storage system is incorporated.This research demonstrates the potential of one particular photovoltaic forced ventilated façade (PV-FVF) used as support for a heating and DHW system based on ASHPs, taking advantage of the entire building as a thermal accumulation system. For this, an “Adaptive Indoor Temperature Setpoint Strategy”, called Tadaptive, is proposed as one alternative mode of operation for the PV-FVF plus ASHP hybridisation. The objective is to transfer thermal energy to the building when the façade is obtaining a higher solar thermal gain. The PV-FVF was characterised experimentally in exterior conditions in a PASLINK test. It was modelled numerically and analysed on a whole building level using a thermal simulation programme into which the predictions of the numerical model were incorporated.Using as an example a residential building with underfloor heating in the city of Madrid, Spain, it was found that the use of the Tadaptive as the accumulation strategy could double the savings obtained with an ASHP supported by a PV-FVF, reducing heating consumption by 19.9%; while including the photovoltaic generation of the outer leaf reduces the total annual final energy for heat demand by 20.7%. The viability of this proposal is therefore demonstrated on the basis of existing technology as an alternative to reduce even further the energy consumption of nZEB type buildings for which the contribution of this hybridisation can be significant.

Analysis of indoor set-point temperature of split-type ACs on thermal comfort and energy savings for office buildings in hot-humid climates

In hot-humid climates, particularly in sub-Saharan Africa (SSA), ambient temperatures and relative humidity are as high as 35 °C and 84%, respectively, requiring the use of mechanical cooling systems for indoor thermal comfort. Split-type vapor-compression air-conditioners (SVAC) are mainly used for space cooling in SSA and consume 60–80% of total energy consumption in commercial and public buildings. Appropriate control strategy of the indoor set-point temperature of SVAC can result in significant energy savings in these buildings. In this study, modeling and dynamic simulation have been conducted using EnergyPlus to predict the energy saving potential and indoor thermal comfort of buildings in hot-humid climates by controlling set-point temperature of the SVAC. In a case study, climatic data for Ghana, was used to predict the energy saving potential and indoor thermal comfort. The study results revealed that, to ensure indoor thermal comfort at high outdoor temperature condition of 35 °C, the least and optimum set-point temperatures of the SVAC should be 21 °C and 25 °C, respectively. On the other hand, for low outdoor temperature condition, the least and optimum set-point temperatures were 22 °C and 26 °C, respectively. Considering 1-star and 2-star rated SVACs which are dominantly used in Ghana, operating at 21–25 °C in the case of high outdoor conditions, and 22–26 °C for low outdoor conditions relative to the least temperatures resulted in energy savings of 8–33% and 12-44%, respectively.

Room temperature and humidity decoupling control of common variable air volume air-conditioning system based on bilinear characteristics

Variable air volume (VAV) air-conditioning (AC) systems are widely employed to achieve a comfortable room thermal and humid environment depending on its better regulation performance and energy efficiency. In the single coil VAV AC system, conventional proportional-integral (PI) control algorithm is usually adopted to track the set-points of the room temperature and humidity by regulating the supply air flow rate and the chilled water flow rate, respectively. However, the control performance is usually not good due to the high coupling of the heat and mass transfer in the air-handling unit (AHU). A model-based control method is developed to realize the decoupling control of the room temperature and humidity according to the bilinear characteristics of the temperature and humidity variation. In this control method, a bilinear room temperature controller is used to track the room temperature set-point based on the real-time cooling load, while a room humidity controller is used to track the room humidity set-point depending on the real-time humidity load. The control performance was validated in a simulated VAV AC system. The test results show that comparing with the conventional PI control, the room temperature and humidity are controlled much more robustly and accurately by using the proposed model-based control method.

Practitioners’ Perspective on the Prevalent Water Quality Management Practices for Legionella Control in Large Buildings in the United States

Managing building water systems is complicated by the need to maintain hot water temperatures high enough to control the growth of Legionella spp. while minimizing the risk of scalding. This study assessed water quality management practices in large buildings in the United States. Surveys conducted with building water quality managers found that more than 85% of buildings have hot water temperatures that are consistent with scald risk mitigation guidelines (i.e., <122 °F/50 °C). However, nearly two thirds and three quarters of buildings do not comply with the common temperature guidance for opportunistic pathogen control, i.e., water heater setpoint > 140 °F (60 °C) and recirculation loop > 122 °F (50 °C), respectively; median values for both setpoint and recirculation loop temperatures are 10 °F (6 °C) or more below temperatures recommended for opportunistic pathogen control. These observations suggest that many buildings are prone to Legionella spp. risk. The study also found that 27% of buildings do not comply with guidelines for time to equilibrium hot water temperature, over 33% fail to monitor temperature in the recirculation loop, more than 70% fail to replace or disinfect showerheads, more than 40% lack a written management plan, and only a minority conduct any monitoring of residual disinfectant levels or microbiological quality. Given the rise in Legionellosis infections in recent years, coupled with highlighted water quality concerns because of prolonged water stagnation in plumbing, such as in buildings closed due to COVID-19, current management practices, which appear to be focused on scald risk, may need to be broadened to include greater attention to control of opportunistic pathogens. To accomplish this, there is a need for formal training and resources for facility managers.

Real-time data based thermal comfort prediction leading to temperature setpoint control

AbstractThe different thermal comfort indices such as Predictive Mean Vote (PMV), Standard Effective Temperature (SET), and Thermal Sensations (TS) have been used to predict occupants’ thermal comfort in a building. The advances in the machine learning approach help overcome the challenges of predicting current traditional thermal indices in a real-time environment. The different indices have different types of data samples (continuous/labelled). Therefore, while considering the machine learning technique in developing the models of the predictive thermal indices, it is essential to select the vital features, the proper learning type, the algorithm, and the evaluation method to establish the models of the predictive thermal comfort. The main focus of this paper is on the development of the ML model and the evaluation technique that helps in selecting the best model in predicting the thermal indices. This work proposes the new neighbourhood-component-analysis Bayesian-optimization-algorithm-based artificial-neural-network to develop a predictive model for the thermal indices. Here, we have proposed a regression-based model to predict PMV, SET and a classification-based model to predict 7-point TS. The statistical-testing results specify that the ANN model's performance is highly accurate and more reliable in predicting the thermal perception in a real-time environment. The performance of the selected model is validated using subjective measures. This prediction leads to the pre-emptive control of the setpoint temperature of the air-conditioning unit, hence resulting in energy efficiency and comfort.

Multi-objective optimization of setpoint temperature of thermostats in residential buildings

Determination of the optimum setpoint temperature of thermostats in various climates is a problem in air conditioning of residential buildings. In this paper, a new method is developed to optimize the setpoint temperature of thermostats in different climates of Iran. Design variables in the optimization process are heating setpoint, cooling setpoint, thickness, and thermal conductivity of insulations in the building envelopes. The optimization goals are minimizing energy consumption and cost of insulations in addition to maximizing thermal comfort of occupants. Thus, the static payback period (SPP) and the predicted percentage dissatisfied (PPD) indices are selected as objective functions which should be minimized in the optimization process. The methods applied to attain these objectives are numerical modeling by EnergyPlus software, Grouped Method of Data Handling (GMDH) type of Artificial Neural Network (ANN), and Non-Dominated Sorting Genetic Algorithm II (NSGA-II). Therefore in this process, first, EnergyPlus is used to train the neural network. Afterward, the GMDH-type neural network is applied to derive polynomials computing the objective functions from the design variables. Then, Pareto optimal points for the objective functions are obtained through using these polynomials and NSGA-II multi-objective optimization. Finally, the optimum design point is selected for different cities. According to the results, type and thickness of insulation integrated in the building envelopes affect the static payback period and thermal comfort of occupants. For all the climates of Iran, the most appropriate insulation is XPS and the optimum heating setpoint of thermostat is 22 °C. Also, the optimum value for the cooling setpoint pertains to the type of climate, so that this value for Bandar Abbas, Yazd, Tehran, Rasht and, Tabriz is, respectively, equal to 24.5, 24.7, 25.2, 25.3, and 25.6 °C. Moreover, thermal comfort of occupants increases with thickness of insulation, except for Bandar Abbas whose PPD is almost constant. The most value of PPD reduction with insulation thickness is related to Tehran where by increasing the insulation thickness from 1 cm to 5 cm, PPD decreases up to 53%.

Compromised Effectiveness of Thermal Inactivation of Legionella pneumophila in Water Heater Sediments and Water, and Influence of the Presence of Vermamoeba vermiformis.

Intermittent reduction of temperature set-points and periodic shutdowns of water heaters have been proposed to reduce energy consumption in buildings. However, the consequences of such measures on the occurrence and proliferation of Legionella pneumophila (Lp) in hot water systems have not been documented. The impact of single and repeated heat shocks was investigated using an environmental strain of L. pneumophila and a reference strain of V. vermiformis. Heat shocks at temperatures ranging from 50 °C to 70 °C were applied for 1 h and 4 h in water and water heaters loose deposits (sludge). The regrowth potential of heat-treated culturable L. pneumophila in presence of V. vermiformis in water heaters sludges was evaluated. A 2.5-log loss of culturability of L. pneumophila was observed in simulated drinking water at 60 °C while a 4-log reduction was reached in water heaters loose deposits. Persistence of Lp after 4 h at 55 °C was shown and the presence of V. vermiformis in water heater’s loose deposits resulted in a drastic amplification (5-log). Results show that thermal inactivation by heat shock is only efficient at elevated temperatures (50 °C) in both water and loose deposits. The few remaining organisms can rapidly proliferate during storage at lower temperature in the presence of hosts.

EXTREME COLD DISCOMFORT IN EXTREME HOT CLIMATES, A STUDY OF BUILDING OVERCOOLING IN OFFICE BUILDINGS IN QATAR

Indoor cold discomfort in Qatar due to “building overcooling” is increasing, as air-conditioning prevails, and global temperatures rise. Overcooling is not dependent only on the inappropriate design of cooling systems, but on “international” thermal comfort standards that are not customized for warm climates. International standards are unintentionally biased towards cooler climates and cultures, the application of which in warm climates result in colder indoor temperatures observed by building occupants and increased cooling energy demand. Overcooling is an over-expenditure of energy, resulting in uncomfortably cold indoor thermal conditions, and unnecessary carbon emissions. In this study, the analysis of field data from 6 office buildings in Doha in a range of indoor thermal conditions and investigation of overcooling on occupant comfort and building performance is conducted. The analysis uncovers over 35% of occupants state being uncomfortably cold and a consensus across the surveys highlight comfortable temperatures higher by 2°C from current setpoint temperatures. Greater occupant comfort and energy efficiency are found by increasing the indoor temperature setpoints investigated through thermal comfort analysis and energy simulation models. Around 50% decrease in occupant discomfort and a 15% decrease in cooling energy demand is found. Such an adjustment in Qatar would improve occupant comfort levels and reduce cooling energy demand throughout the existing office building stock.

Evaluating cascaded and tunable phase change materials for enhanced thermal energy storage utilization and effectiveness in building envelopes

The incorporation of phase change materials (PCMs) in envelope is considered an effective thermal energy storage (TES) method for energy savings and load flexibility in buildings. However, an important limitation of PCMs is their fixed and narrow transition temperature range. Because the interior temperature setpoints are typically different in summer versus winter, and the exterior temperature varies substantially above and below the setpoints during the year, PCMs with a fixed transition temperature are utilized only during part of the year. In this study, we provide an extensive numerical analysis of the performance of a lightweight building envelope containing three different types of PCMs: traditional single-layer PCM with a fixed transition temperature, novel cascaded two-layer PCM with different transition temperatures, and a “futuristic” tunable PCM whose transition temperature can be varied in-situ using external excitation. We compare their performances by evaluating the relationship between the PCM utilization and parameters such as latent heat, transition temperature range, PCM thickness, and PCM location. While traditional PCMs are mostly active during one season, properly designed cascaded and tunable PCMs can be active much longer, thereby allowing load shift and energy savings in both heating and cooling seasons. Under the operating conditions considered in this study, tunable PCMs performed best, providing the highest utilization (about 2 times the traditional PCMs) and enhanced effectiveness (up to 99% peak load reduction in cooling season and 34% peak load reduction in heating season) with the same amount of material as the traditional PCMs; however, cascaded PCMs can be a good alternative while tunable PCMs are unavailable.

The comfort and energy impact of overcooled buildings in warm climates

Around 18% of global carbon emissions can be attributed to building heating or cooling, driven by the adoption of “international” thermal comfort standards such as ASHRAE-55, which imply an homogenous indoor environment. We argue that the importation of such standards to warm climates results in indoor cold discomfort due to “overcooling”: a phenomenon anecdotally recognised worldwide but not studied or defined systematically. Unlike under- or over-heating, overcooling is the purposeful over-expenditure of energy, that creates conditions of cold thermal discomfort. We examine data for warm and temperate climates from a global thermal comfort database spanning 27 countries with over 90,000 occupant responses to investigate overcooling of air-conditioned buildings. We suggest that overcooling is best defined by taking the intersection of thermal sensation and preference and, using this definition, we find that 17% of building occupants in the examined data can be classed as being overcooled. We estimate the cooling energy demand of overcooling imposed through the adoption of the ASHRAE-55 standard using computer simulations that move building occupants from being overcooled to comfortable. The results suggest around 15% of cooling energy demand could be saved through a simple upward adjustment of set-point temperatures by 2 °C in warm climates. Such an adjustment in the Global South, which contains the majority of the warm regions of the Earth, could have a dramatic impact on the evolution of future cooling energy demand which is expected to triple by 2050.

Experimental investigation of heating pattern, energy requirement and electrical conductivity in a batch ohmic heating system for coffee fermentation

This study investigated the effect of voltage gradient (VG) and process capacity on the heating pattern and energy requirement during temperature conditioning by ohmic heating for coffee fermentation. Three levels of VG (8, 12 and 16 V/cm) and batch capacity (50, 75 and 100 g) were taken as independent variables using a full-factorial design. The setpoint temperature was 37 °C. Experimental research revealed that temperature conditioning for coffee fermentation can be performed properly using ohmic heating. The temperature distribution in coffee beans had a high level of uniformity, and the temperature could be maintained according to the setpoint temperature with a minimum deviation value. It was found that an increase in VG and batch capacity increased the electric current, power, and heating rate. Specific power at three levels of capacity was relatively the same and increased as the VG increased. As the VG and capacity increased, efficiency tended to increase while specific energy consumption (SEC) decreased. This result demonstrated that a high-capacity coffee fermentation was recommended for low SEC and high efficiency (minimum heat loss). Electrical conductivity (EC) of coffee beans was also studied during the test where VG affected the EC of coffee beans, also final EC at 37 °C always showed significantly higher (p-value<0.05) than the initial EC at 25–27 °C for all VG variations. Furthermore, the established mathematical models were found to be fit for estimating the amount of electrical current and power requirement with R2 > 0.97. Industrial relevanceIn the coffee fermentation, to maintain the consistency of the coffee produced, a controlled and consistent process is needed by using a fermenter (fermentation vessel). Ohmic heating is a promising technology to condition the optimum temperature in the fermentation process with high efficiency and uniform heating. To develop an industrial scale ohmic type fermenter for coffee fermentation and its energy requirements, an in-depth study of the heating pattern, energy requirement and electrical conductivity is essential. The present paper contributes to the disclosure of the heat generation process in Robusta coffee beans and investigate the heating pattern, energy requirement, and electrical conductivity during ohmic heating. Several empirical models generated from this investigation could be useful for the coffee industry regarding the development and scaling up of ohmic heating-based coffee fermenters.

A Demand Response Implementation with Building Energy Management System

The demand response (DR) program is one of the most promising components in the development of the Smart Grid. However, there are many challenges in practical operation to improve the existing and outdated system to comply with the DR programs. In Thailand, the major pain point of the office building owner in the DR program is the additional equipment, modification and operation cost of the existing equipment. Moreover, the sophisticated solution and control are other obstacles that need more measurements and data, and they make the operation difficult to work with. In this paper, we implemented a simple yet cost-effective hardware and software solution targeting an outdated air-conditioning system without voiding the warranty of the outdated equipment and without installing any additional measurements. In addition, the proposed operation is designed to be easy to operate under the equipment limitation and unskilled labor. More importantly, indoor temperature setpoint schedules during the DR event are forecasted with some public datasets to determine the capacity of the energy management system that can reduce the power consumption in the office building without an effect on the occupants’ comfort. To confirm the practicality of the proposed solution, the actual operation of the proposed solution can achieve the maximum power reduction at 19.80 kW (43.79% of the maximum power consumption) while keeping only 1 °C of difference from the typical room temperature (26–28 °C).

Analysis of the Potential of Decentralized Heating and Cooling Systems to Improve Thermal Comfort and Reduce Energy Consumption through an Adaptive Building Controller

Thermal comfort is one of the most important factors for occupant satisfaction and, as a result, for the building energy performance. Decentralized heating and cooling systems, also known as “Personal Environmental Comfort Systems” (PECS), have attracted significant interest in research and industry in recent years. While building simulation software is used in practice to improve the energy performance of buildings, most building simulation applications use the PMV approach for comfort calculations. This article presents a newly developed building controller that uses a holistic approach in the consideration of PECS within the framework of the building simulation software Esp-r. With PhySCo, a dynamic physiology, sensation, and comfort model, the presented building controller can adjust the setpoint temperatures of the central HVAC system as well as control the use of PECS based on the thermal sensation and comfort values of a virtual human. An adaptive building controller with a wide dead-band and adaptive setpoints between 18 to 26 °C (30 °C) was compared to a basic controller with a fixed and narrow setpoint range between 21 to 24 °C. The simulations were conducted for temperate western European climate (Mannheim, Germany), classified as Cfb climate according to Köppen-Geiger. With the adaptive controller, a 12.5% reduction in end-use energy was achieved in winter. For summer conditions, a variation between the adaptive controller, an office chair with a cooling function, and a fan increased the upper setpoint temperature to 30 °C while still maintaining comfortable conditions and reducing the end-use energy by 15.3%. In spring, the same variation led to a 9.3% reduction in the final energy. The combinations of other systems were studied with the newly presented controller.

A general approach to integrating compression heat pumps into biomass heating networks for heat recovery

Over the past few years, studies have shown that the efficiency issue of biomass heating has become increasingly important to enhance their competitiveness. The integration of a compression heat pump into the system to recover heat from exhaust gases could be a promising solution. However, the different ways of integrating heat pumps lead to highly variable techno-economic results over their lifetime. To find out how to integrate compression heat pumps into a biomass heating network more effectively, a general approach for the integration is presented in this paper, where the heat pumps can be integrated either into the flue gas condenser or into the network return flow. A detailed model for implementing the integration approach is proposed and validated against the measured data from two real biomass heating networks. The evaluation results show that both integration variants improved system efficiency by more than 17% in practice. For a techno-economic comparison and analysis of both variants, the proposed integration approach is also applied to a use case in Germany. In the studied case, the flue gas-side integration is more cost-effective than the network-side integration, and both concepts improve system efficiency by 12.6%. By analyzing the technical parameters, it is noticed that both integration concepts can be achieved cost-effectively in practice by finding the optimal setpoint of exhaust gas temperature under certain conditions. The analysis of electricity and fuel prices shows that the integration concepts are sensitive to the ratio of electricity price and biomass fuel price. If the fuel prices increase sharply in the future, both concepts will take on greater significance.

Achieving mid-rise NZEB offices in Brazilian urban centres: A control strategy with desk fans and extension of set point temperature

Positive energy buildings (PEB) are foreseen to help achieving global emissions reduction targets and decarbonisation. However, for vertical office spaces in urban centres the photovoltaic (PV) production area is restricted, so innovative strategies are needed. For cooling-dominated climates the extension of set point temperature associated to local control of air movement has the potential to increase the use of natural ventilation and generate a great amount energy savings. . Therefore, this study aims to identify to what extent adopting a mixed-mode operation with desk fans could help mid-rise office buildings to become NZEBs in warm climates. To verify the impact of this strategy, computer simulations were carried out with three building heights in four Brazilian cities. Results show this strategy can generate 20–40% energy savings and the set point could be extended up to 28 °C or 30 °C depending on the climate, without jeopardizing occupants’ thermal comfort. Thus, in warm climate cities, the strategy allows lower buildings to become PEBs and mid-rise buildings to become NZEBs. In addition, the demand for extra PV area is expressively reduced, increasing the viability of mid-rise PEBs. This study adds innovative knowledge for achieving PEB targets under suboptimal conditions and highlights multiple aspects that should be considered for applying this strategy.

Classification of Two Volatiles Using an eNose Composed by an Array of 16 Single-Type Miniature Micro-Machined Metal-Oxide Gas Sensors.

The artificial replication of an olfactory system is currently an open problem. The development of a portable and low-cost artificial olfactory system, also called electronic nose or eNose, is usually based on the use of an array of different gas sensors types, sensitive to different target gases. Low-cost Metal-Oxide semiconductor (MOX) gas sensors are widely used in such arrays. MOX sensors are based on a thin layer of silicon oxide with embedded heaters that can operate at different temperature set points, which usually have the disadvantages of different volatile sensitivity in each individual sensor unit and also different crossed sensitivity to different volatiles (unspecificity). This paper presents and eNose composed by an array of 16 low-cost BME680 digital miniature sensors embedding a miniature MOX gas sensor proposed to unspecifically evaluate air quality. In this paper, the inherent variability and unspecificity that must be expected from the 16 embedded MOX gas sensors, combined with signal processing, are exploited to classify two target volatiles: ethanol and acetone. The proposed eNose reads the resistance of the sensing layer of the 16 embedded MOX gas sensors, applies PCA for dimensional reduction and k-NN for classification. The validation results have shown an instantaneous classification success higher than 94% two days after the calibration and higher than 70% two weeks after, so the majority classification of a sequence of measures has been always successful in laboratory conditions. These first validation results and the low-power consumption of the eNose (0.9 W) enables its future improvement and its use in portable and battery-operated applications.

Modeling the Effect of Temperature on the Flower Development Rate of Hybrid Impatiens

The effect of average daily temperature (ADT) on flower bud development and subsequent time to flower was investigated on hybrid impatiens (Impatiens ×hybrida) cultivars Compact Electric Orange, Compact Hot Coral, and Compact Orchid Blush. Plants with a visible flower bud measuring 2 mm in width were placed in one of the four greenhouses with temperature setpoints ranging from 16 to 28 °C. Flower bud width was measured every 3 days in each ADT treatment until flowering. The subsequent days to flower (DTF) from the onset of a visible bud decreased from 36 to 27 days as the ADT increased from 17 to 28 °C. The DTF from visible bud varied by &lt;3 days among the three cultivars across all temperatures; therefore, cultivar data were pooled to create a stronger prediction model. A logistic formula was used to predict the remaining DTF as a function of flower bud width and ADT. The model accurately described the effect of bud width and ADT on flowering time within ±3 days for 87% of the actual DTF across all three cultivars. The resulting flower development model provides greenhouse growers with a guide for manipulating temperature to produce flowering plants for specific market dates based on flower bud width measurements.

유전알고리즘을 이용한 오피스 건물의 피크전력 감소를 위한 일일 예냉설정온도 최적화 연구

In this paper, the peak electric power of an office building was reduced with a precooling strategy. Precooling was conducted two hours before work time. Set-point temperatures for precooling were optimized using a genetic algorithm to minimize daily peak electric power. Searching for optimized set-point temperature was conducted with an objective function that was developed with a multiple regression model. The regression model used dry-bulb temperature, relative humidity, and the set-point temperature as the input parameters, and set daily peak power of the building as the output parameter. Model data were collected from ‘EnergyPlus’, a building energy simulation program. The applied building was ‘Medium Office’ provided by EnergyPlus. Based on our results, there was a 0.71~5.64% reduction in daily building peak power with the application of the optimized precooling setpoint temperature. In addition, the reduction of electricity cost due to the reduction of peak electric power was observed.

Detecting occupancy behaviour of buildings through environment monitoring sensing

The goal of this research is to produce a realistic occupancy forecast as well as an ideal occupancy-based controller for increasing the performance of Heating Ventilation and Air-Conditioning [HVAC] systems. Reliable occupancy prediction is a critical enabler for demand-based HVAC control since it ensures that the HVAC system is not running unnecessarily while a room or zone is empty. We present simple yet successful occupancy prediction methods, as well as an approach for automatically setting temperature set-points, in this work. We present three alternative occupancy prediction algorithms based on historical occupancy measurements. The proposed approach uses historical occupancy profile and environmental room data to establish an occupancy identity strategy that can provide a stochastic model based on uncertain basis functions as an alternative. According to the findings, the proposed occupancy prediction algorithms could reach an accuracy of approximately 85% reliable prediction with few negative predictions.