Changes In Heat Load Research Articles

Transformation of Planktonic Assemblages in a Severely Stressed Cooling Reservoir

The results of long-term studies in the cooling reservoir of the Kharanorskaya SDPP (Transbaikalia) are presented, conventionally divided into four periods depending on the increase in power plant capacity. The stages of phyto- and zooplankton development determined by the influence of technogenic and biotic factors are determined. The response of plankton communities to changes in heat load is shown. Periods of intensive vegetation of algae and mass development of invertebrates alternate with a significant decline in the number and biomass of hydrobionts, which indicates an unstable state of the forming cooling pond technoecosystem.

Accounting for climate changes when constructing the Rossander graph

The temperature of the atmospheric air affects the design and indicators of energy efficiency of all elements of heat supply systems. An extremely important tool to develop heat sources that allows us to assess changes in consumer heat loads and model algorithms for heat source operation, taking into account the variability of outdoor air temperature in the geographical conditions of the design objects, is a graph of the duration of heat loads during the heating period (Rossander’s graph). It is impossible to construct the Rossander’s graph without data on the duration of the outdoor temperature standing during the heating period. In this paper, the problem of the lack of temperature data necessary for the construction of the Rossander’s graph in the current regulatory documents is revealed. The analysis of previous studies that produced temperature data with the duration of temperature standing is carried out, and the need for their refinement is substantiated. The arrays of hourly outdoor air temperatures were processed according to two weather models, as well as the array of average daily temperatures obtained as a result of measurements from the weather station for the geographical location of the main building of KNUCA. As a result of the comparative analysis, a model closer to reality was identified and, on its basis, actual data on the duration of outdoor temperatures standing for the city of Kyiv with a temperature step of 1℃ were developed. The obtained temperature data were compared with those that were developed in previous studies, as well as with the temperature data that are contained in the cancelled standard. The curve of the long-term run of the moving average outdoor air temperatures for the winter periods of 1973-2023 and its polynomial trend are constructed and compared with the curve that characterizes the run of the moving average five-year temperatures for the winter periods of 1861-1970 and its polynomial trend.

Predicting hourly heating load in district heating system based on the hybrid Bi-directional long short-term memory and temporal convolutional network model

Accurate heating load prediction is essential to supply-demand collaboration in district heating systems and energy sustainability. With the development of the Internet of Things technology, massive monitoring data is collected that provides abundant data sources for the prediction models. However, the missing data from equipment anomalies, network transmissions and the complexity of heat load changing cause difficulty in realizing accurate heat load prediction. Therefore, the hybrid model based on bidirectional long short-term memory network and temporal convolutional network proposed in this paper to improve the accuracy of the heat load prediction from the aspects of reconstruction of missing values and extraction of complex features. The bidirectional long short-term memory algorithm imputes missing values based on bi-directional features of existing data and provides solid data foundation for subsequent training of predictive models. The temporal convolutional network achieves high-level feature extraction and parallel computation, which contributes to the effective modeling of complex changes in heat load and the realization of accurate heat load prediction. Comparative study was conducted with four heat exchange stations of actual environment to evaluate the performance of the prediction model. The results showed the mean absolute percentage error of the hybrid model decreased to 2.47% which is lower than the State-of-the-Art models, such as long short-term memory, temporal convolutional network, and support vector regression etc. The superior results further validated the feasibility of this hybrid model in heat load prediction.

Impact of future climate change on energy consumption in residential buildings: A case study for representative cities in Japan

This study examines the impact of future climate change on energy consumption in residential buildings in Japan, taking into account both the current and future typical meteorological year (TMY) database. TMY data is widely used in the building sector for energy performance assessments, system sizing, and optimization. To investigate the impact of current and future TMY databases on energy consumption of buildings, the study predicts the cooling and heating loads of residential buildings in four cities of Japan under the current (2020 ver.) and future (2086 ver.) TMY databases. Results show that the use of future TMY database leads to significant changes in air-conditioning heat loads of residential buildings in Japan. It finds that the annual cooling load in residential buildings of four cites of Japan increases by approximately 12% for Tokyo, approximately 9% for Toyohashi, approximately 8% for Osaka, and approximately 7% for Nagoya, respectively, however the annual heating load decreases by approximately 8% for Tokyo, approximately 9% for Toyohashi, approximately 6% for Osaka, and approximately 5% for Nagoya, respectively, compared to the current TMY database. This finding suggests that climate change will have a significant impact on future building energy consumption, and proposes energy-efficient building design as a solution to mitigate the impact of climate change on building energy consumption.

STUDY OF A DISTRICT HEATING SYSTEM WATER BOILER AS A OBJECT OF CONTROL


 
 The analysis of the operating conditions of a typical district heating system, in particular, a hot water gas boiler, was carried out. It is shown that the boiler, as the main control object, operates under conditions of constant change in external heat load, which, due to their random nature, leads to a number of uncertainties. The expediency of the mathematical description of uncertainties using the stochastic method as the most tested in practical conditions is substantiated. According to the results of the passive experiment on the hot water gas boiler KVG6.5-150 of the district heating system of one of the districts of Kharkov, an array of hourly experimental data was obtained, reflecting the main performance indicators of the hot water boiler. As a result of data processing by the least squares method, a mathematical model of the boiler was obtained in the form of a linear regression equation, reflecting the relationship between the temperature of the coolant at the boiler outlet and the ambient air temperature, the temperature of the coolant at the inlet to the boiler and with the flow rates of natural gas and coolant to the boiler. The obtained regression equation was verified by Student's t-test, which confirmed the significance of all coefficients of the regression model. The practical significance of the multiple regression equation was assessed using the coefficient of determination. The quality of the multiple regression equation as a whole was assessed using Fisher's F-test. Since parallel surveys were not conducted, instead of checking the adequacy, the quality of the approximation of the experimental points by the accepted regression equation was assessed, that is, it was checked whether this equation makes sense. Such a test was carried out by comparing the residual variance and the variance relative to the mean. The calculation results showed that the value of the coefficient of determination significantly exceeds the allowable value, and the actual value of the Fisher criterion significantly exceeds the table value. The obtained indicators led to the conclusion that the relationship between the variables in the regression model is significant, and the proposed stochastic method and the multiple linear regression equation can be used to make decisions in the process of synthesizing the technical structure of a computer-integrated control system for objects of a district heating system.
 
 
 
 
 

Modeling the relationship between heat stress, feed intake, and day relative to calving in nonlactating dairy cows

Heat stress (HS) during the dry period can affect animal welfare, health, dry matter intake (DMI), and milk production in the subsequent lactation, which will negatively affect the profitability of dairy farms. In this study, the objective was to model the changes in DMI in pregnant nonlactating heat-stressed dairy cows with or without access to evaporative cooling systems. A database composed of individual DMI records from 244 pregnant nonlactating heat-stressed dairy cows from 7 experiments averaging from -35 (-42 to -21 d) to -1 d relative to calving (DRC) and housed in environmental conditions in which temperature-humidity index (THI) ranged from 58.4 to 83.3, with or without access to evaporative cooling systems was built. Generalized additive mixed-effects models were used to describe the relationships of DMI with HS and DRC. Changes in DMI with the increase in THI and the progression of pregnancy in cows with or without evaporative cooling systems were estimated using differential equations. On average, cows housed in barns without evaporative cooling systems had a reduction in DMI of 1.30 kg/d and increased rectal temperature in 0.22°C in relation to those housed in barns with evaporative cooling systems. Dry matter intake decreased as THI increased, but the reduction was greater for non-cooled cows as THI values increased. In addition, regardless of the THI, DMI started to decrease at DRC = -14 for cooled cows, while for non-cooled cows it already started at DRC = -30 relative to the previous days evaluated. The intensity of the reduction was lesser for cows that had access to evaporative cooling systems and/or were in the dry period in May-June as compared with those that were in the dry period in July-August or September-October. The models generated in this study, which include environmental variables, should lead to more accurate predictions of DMI during heat stress that can be used to formulate diets to meet the needs of the late pregnant cow because it is possible to predict changes in DMI as the heat load and DRC change. Such models are also expected to help dairy nutritionists to decide when and how to apply the dietary strategies available to attenuate the reductions in DMI with the intensity of heat stress and progression of pregnancy.

A new hybrid optimization prediction strategy based on SH-Informer for district heating system

The district heating system (DHS) is an essential social service. Heat load forecasting is one of the critical steps in DHS. However, the manual and empirical operation in the dispatch process may exhibit some deviations which will cause the irrationality of historical data. This paper proposes a new hybrid optimization prediction strategy, which consists of the similar hour (SH) method and a prediction model namely Informer. In the SH approach module, light gradient boost machine (LightGBM) and Euclidean norm (EN) is used to select the SH dataset. In the prediction module, Informer and other four popular models are constructed. The evaluation module contain four frequently-used evaluation criteria and energy-saving rate. Especially, the energy-saving rate is defined for the new strategy. The historical operation data of a DHS in Tianjin is studied as the case for model training. Experimental results indicate that: (a) Informer can effectively sense the change of heat load and performs excellent in the prediction task; (b) The hybrid models based on SH can improve the prediction performance; (c) SH_Informer achieves the highest energy-saving rate, reaching 11.09%, 10.05% and 10.36% in the prediction length of 24, 48 and 168 h, which demonstrate the feasibility of the new prediction strategy.

Model Predictive Evolutionary Temperature Control via Neural-Network-Based Digital Twins

In this study, we propose a population-based, data-driven intelligent controller that leverages neural-network-based digital twins for hypothesis testing. Initially, a diverse set of control laws is generated using genetic programming with the digital twin of the system, facilitating a robust response to unknown disturbances. During inference, the trained digital twin is utilized to virtually test alternative control actions for a multi-objective optimization task associated with each control action. Subsequently, the best policy is applied to the system. To evaluate the proposed model predictive control pipeline, experiments are conducted on a multi-mode heat transfer test rig. The objective is to achieve homogeneous cooling over the surface, minimizing the occurrence of hot spots and energy consumption. The measured variable vector comprises high dimensional infrared camera measurements arranged as a sequence (655,360 inputs), while the control variable includes power settings for fans responsible for convective cooling (3 outputs). Disturbances are induced by randomly altering the local heat loads. The findings reveal that by utilizing an evolutionary algorithm on measured data, a population of control laws can be effectively learned in the virtual space. This empowers the system to deliver robust performance. Significantly, the digital twin-assisted, population-based model predictive control (MPC) pipeline emerges as a superior approach compared to individual control models, especially when facing sudden and random changes in local heat loads. Leveraging the digital twin to virtually test alternative control policies leads to substantial improvements in the controller’s performance, even with limited training data.

Model predictive temperature control of a closed-loop spray cooling system

A dynamic model of a closed-loop spray cooling system was proposed, and a model predictive temperature control algorithm was presented. The presented algorithm could quantitively estimate sudden changes in heat load, and then plan an optimized control path along which the temperature trajectory was numerically predicted to be the most stable. Then, the presented algorithm was integrated into a closed-loop spray cooling system, and its control performance was numerically studied. The results showed that, following a 20 W downward step change in heat load, the temperature was re-stabilized in 4 s, with its oscillation less than 0.14 K. Under identical conditions, the presented algorithm outperformed PID in terms of temperature stability, with its peak time shorter by 25–55%, settling time shorter by 38–51%, and average temperature offset smaller by 50–60%. This advantage was mainly because the presented algorithm compensated for hydraulic and thermal lags, two sources of control nonlinearity, by excessive regulation in advance. Unexpectedly, temperature overshoots of the presented algorithm and PID did not differ significantly, seemingly due to the algorithm-inherent estimation lag. From a system design perspective, the length of pump pipeline should be as short as possible, which proved to help reduce overshoot and settling time. Similarly, addition in heat load’s mass also helped reduce overshoot, but would result in an unfavorable long settling time, and vice versa. The simulation results were validated by experimental data, with error less than 10%.

Study on thermodynamic system characteristics of thermoelectric units under variable operating conditions

The variable working condition of thermal system refers to that the working condition in the system changes, deviates from the design working condition or deviates from a certain reference working condition. There are various reasons for the change of thermal system’s off design condition, including the change of unit heat load, the change of thermal system and equipment, and the change of steam parameters and reheat parameters. The purpose of variable condition calculation of thermodynamic system is to determine the steam parameters of each extraction port and exhaust end of the turbine and the corresponding parameters of the regenerative system. Its essence is to determine the new expansion process line and system parameters of the turbine. This is the basis for the safety and reliability analysis of the system under off design conditions and the calculation and analysis of economic indicators. Through the research on the electrothermal coupling characteristics of thermoelectric units under variable operating conditions, it can provide data support for the power grid dispatching department to master the electrical output characteristics of thermoelectric units in heating seasons.

The contribution of urbanisation and climate conditions to increased urban heat load in Zagreb (Croatia) since the 1960s

Urban climate is affected by weather, global climate change and urban development. However, climate change and urbanisation take place simultaneously with intertwined impacts. To analyse their relative contribution to the heat load of Zagreb, a modelling approach is applied to two land-use/land-cover (LULC) situations and corresponding climate conditions. The results indicate that the change in total heat load is dominantly affected by climate change (∼88%) with an average increase in the summer days for 35 days. LULC alterations have a weaker impact (∼12%), but they strongly affect heat load spatial variability. The sign of LULC related heat load change depends on the type of the change (e.g. an increase is detected in areas that have turned from green into built-up classes). Generally, LULC effect is limited to the area with the modification, however it can spread to adjacent areas due to the processes like advection and evapotranspiration. In areas with considerable LULC alterations, their impact on the heat load is comparable to that of climate change. These results highlight the potential of change in the city infrastructure for climate adaptation, as well as emphasise the importance of considering future climate conditions when assessing efficiency of climate adaptation measures.

A hybrid deep reinforcement learning ensemble optimization model for heat load energy-saving prediction

Accurate heat load forecasting is crucial to achieving feed-forward control and on-demand heat supply in the district heating system (DHS). However, accurate forecasting is difficult to achieve effective energy-saving because experimental data are often not optimal or the most energy-efficient. In this study, a hybrid heat load forecasting model with energy-saving consideration is proposed, which consists of similar sample selection approach, short-term forecasting model pool and deep reinforcement learning ensemble strategy. In similar sample selection module, a novel weighted Euclidean norm (EN) is used to select suitable similar samples set for the training samples set. In model pool module, six popular deterministic prediction models are constructed. For energy-saving consideration, the average of minimum and actual heat load is selected as the training target in the training samples set and similar samples set. In ensemble module, deep deterministic policy gradient (DDPG) is used to integrate the prediction results of the base predictors. In the case study, real data from a heat exchange station in Tianjin are used to perform the prediction of heat load 24 h, 72 h and 168 h, respectively. Experimental results show that: (a) The proposed hybrid model is able to capture the change of heat load. The average root mean square error for different prediction periods are 0.0825 MW, 0.1007 MW and 0.1152 MW, respectively; (b) The proposed hybrid model can reduce energy consumption. The energy-saving rate for different periods are 5.33%, 5.31% and 5.07%, respectively.

Experimental investigations on transient flow and heat transfer characteristics of RP-3 at supercritical pressure

Variable operation conditions due to the wide speed range of hypersonic vehicles are complicated and are often related to the heat load change of the chamber wall. Thermal and flow response characteristics during flight state change are investigated in this research experimentally by utilizing the electrically heating experiment system. It is revealed that the response time of flow and heat transfer due to step perturbation is longer than that of perturbation. The response time decreases as the initial temperature increases when the fuel temperature is lower than the critical temperature. Once the temperature is higher than critical temperature, the response time begins to increase as the initial temperature increases. A 3D transient model is adopted to help to explain this phenomenon. The results indicate that the reason for the characteristics is the weakening of heat diffusion near the wall due to heat transfer deterioration. This conclusion is beneficial to the regulation of the coolant.

Experimental study on the thermal performance of an ammonia loop heat pipe using a rectangular evaporator with longitudinal replenishment

• An ammonia LHP with a rectangular evaporator was designed and fabricated. • The LHP can successfully realize the startup at small heat loads as low as 2 W. • The LHP responds quickly to the heat load change and achieves a smooth transition. • The LHP can reach a heat transfer limit up to 110 W restricted by capillary limit. • Heater area and position play an important role in the heat transfer limit. In this work, a stainless steel-ammonia loop heat pipe (LHP) using a rectangular evaporator with longitudinal replenishment was designed and fabricated. Extensive experiments have been implemented to investigate its startup characteristics, dynamic operation, heat transfer limit and thermal resistance. In particular, the effect of heat load on the startup performance was evaluated, and the effects of heater area and position on the heat transfer limit were studied. Experimental results showed that the LHP exhibited excellent startup performance. It could realize the startup successfully at a small heat load as low as 2 W. In most cases, it started up in only one situation. The temperature overshoot decreased with the increase of the heat load in the startup. In the power step change process, the LHP responded quickly to the changes of the heat load, and achieved a smooth transition. The LHP could reach a heat transfer limit up to 110 W for all the three heaters, restricted by the capillary limit. The heater area and position played an important role in the heat transfer limit, which became larger when the heater was placed closer to the compensation chamber (CC), due to reduced flow resistance of liquid replenishment in the capillary wick. It was found that the closer the heater was located to the CC, the smaller the thermal resistance of the LHP system. This work contributes to a comprehensive understanding of the thermal performance of the LHP using a rectangular evaporator, providing good guidance and reference for its future applications.

Experimental study on a hydrogen pulsating heat pipe in different heating modes

In practical applications, the heat load changes caused by various factors require the pulsating heat pipe (PHP) to have good heat transfer performance and temperature response characteristics in different heating modes. In order to understand the heat transfer performance of a hydrogen PHP in different heating modes, the temperature curves of the PHP in two heating modes (stepwise heating and sudden heating) are obtained experimentally. The experimental results show that for a given heat load, the differences of the quasi-steady-state temperatures and the effective thermal conductivities between two heating modes are negligible. It’s concluded that the stable heat transfer performance of the PHP is reproducible in the two different heating modes.

Comparative study on pump wavelength dependent efficiency in Nd:YVO4

The influence of the pump wavelength on the heat load and efficiency of Nd:YVO4 crystals is investigated with a specially designed crystal mount. The measurements indicate that the change in heat load in the crystal can be solely ascribed to the difference of quantum defects and no further non-radiative effects.

Experimental parameter studies on a two-phase loop thermosyphon cooling system with R1233zd(E) and R1224yd(Z)

• Experiments on Two-phase loop thermosyphon (TPLT) studying influencing parameters. • Self-regulation compensates changes in heat load, height difference, mass flow rate. • Identification of optimal charge avoiding instabilities and critical temperatures. • Low-GWP refrigerants R1233zd(E) and R1224yd(Z) are suitable for thermosyphons. Two-phase loop thermosyphon (TPLT) is a promising technology looking at highly effective electronics cooling. Due to strong coupling between the internal and external parameters, in this study experimental tests in steady-state are carried out using R1233zd(E) and R1224yd(Z) as a working fluid to investigate the respective influences and resulting design requirements. The relationship between the governing thermal and flow equations is presented to facilitate the interpretation of the test results. The study shows a stable flow and cooling performance over a wide range of heat loads and recooling temperatures. The refrigerant charge is identified as one of the main influencing factors, with an optimum being between excessive subcooling and beginning dry-out. Both tested refrigerants lead to basically similar results, showing minor differences regarding thermal performance and system stability.

Numerical study of the thermal performance of a hydrogen pulsating heat pipe

The pulsating heat pipe (PHP) has the characteristics of high thermal conductivity, simple structure, and light weight. It can meet the industry's needs for high heat transfer efficiency, flexibility, and low cost. Many attempts have been made to simulate their complex thermal behavior, but existing models have not been validated for cryogenic PHPs. In this study, a one-dimensional numerical model based on slug flow has been developed to predict the thermal performance of cryogenic PHPs. Vapor is considered a real gas. The RKS (Redlich-Kwong-Soave) equation of state is used to determine the thermodynamic properties of vapor bubbles such as pressure and internal energy. Hydrogen is the working fluid in this study. The comparison shows the consistency between the experiment and the simulation, indicating the good predictive ability of the model. Numerical results show that the response time of the hydrogen PHP to heat load changes is less than 5 s. The temperature of the vapor bubbles in the evaporator can be higher than their saturation temperature, showing a superheated state. The proportions of sensible heat and latent heat in heat transfer are similar, and the contribution of latent heat is between 45% and 51%.

Dynamic characteristics of an integrated cooling system comprising vapor compression and thermosyphon loop for electronics cooling

An integrated cooling system comprising passive cooling-thermosyphon loop and active cooling-vapor compression was proposed for the cooling of electronics, especially avionics, under a wide range of heat loads and ambient temperatures. A prototype of the integrated system with the weight of 2.8 kg was developed by microchannel heat exchangers and a micro rotary compressor. The dynamic characteristics of the thermosyphon loop mode and vapor compression mode, and the switching mode were investigated experimentally, with second as time scale. Under the premise that the average wall temperature does not exceed 50 °C, the thermosyphon loop mode can handle a heat load of 600 W with COP of 35.7, and the vapor compression mode can handle a heat load of about 1000 W with COP of 3.1, at the ambient temperature of 20 °C. The developed integrated cooling system can effectively handle the sharp change in heat load (two heat loads of 400 W and 800 W like square wave) and ambient temperature (from 10 °C to 32 °C) by switching working modes. It automatically switched to TL mode at low heat load and ambient temperature for energy conservation, and switched to VC mode at high heat load and ambient temperature for safety.

Experimental Study of a Loop Heat Pipe with Direct Pouring Porous Wick for Cooling Electronics

A pouring silicate wick was manufactured to explore the influence of process and physical properties on the production and performance of loop heat pipes (LHP). This paper theoretically analyzed the advantages of pouring porous wick and introduced the technology of pouring silicate directly on evaporator. Based on this, the heat transfer performance of copper-methanol LHP system with pouring porous wick was tested under different positions. The results showed that with the input of multiple heat sources, the LHP could start up and maintain a stable temperature from 40 W to 160 W. When the vapor grooves were located above the compensation chamber, it was difficult to start up positively. By adding gravity assistance, the system could obtain more stable liquid supply and vapor flow, so as to realize start up. In the variable heat load test, the LHP showed good adaptability to the change of heat load. The thermal resistance of the system decreased with the increase of heat load. The thermal resistance of the evaporator almost unchanged and was always lower than 0.05 °C/W, which indicated that the pouring porous wick in the evaporator had good heat load matching.