Heating Substations Research Articles

A hybrid control method for district heating substations based on time-based room temperature demand

A hybrid control method for district heating substations based on time-based room temperature demand

Data-driven analysis and prediction of indoor characteristic temperature in district heating systems

Many indoor temperature sensors have been installed in building rooms with district heating systems (DHSs) in China. To apply the collected indoor temperature data to district heating substation regulation, the indoor characteristic temperature of the heat substation (ICTS) should be calculated. However, previous calculation methods for ICTS cannot accurately evaluate their comprehensive characteristics. This study proposed a novel method to calculate the ICTS based on the entropy value and applied it to three actual DHSs in northern China. First, the variation trend and influencing factors of indoor temperature data were analyzed. Second, the ICTS was calculated and compared using various methods. Third, a correlation analysis of the ICTS and input features was performed. Finally, five typical machine learning models were used to predict the ICTS. The results demonstrated that the proposed method can better reflect the characteristics of the data and eliminate the impact of subjective preferences. The average mean absolute percentage errors of five models were less than 1%; the linear regression model performed best when denoising the original data, with a value of 0.12%. This study is helpful for better understanding the influencing factors on the ICTS and the strategies for adjusting feature values.

Determination of Heat Transfer Correlations for Fluids Flowing through Plate Heat Exchangers Needed for Online Monitoring of District Heat Exchanger Fouling

This article deals with the problem of estimating the degree of fouling of plate heat exchangers (PHEs) used in district heating substations (where the working medium is water). A method for calculating the thermal resistance of fouling is proposed based on a comparison of the thermal resistance of a fouled and clean heat exchanger. The thermal resistance of the heat exchanger for both fouled and clean apparatuses is determined as the inverse of their overall heat transfer coefficient. In the method, the heat transfer coefficients necessary to determine the overall heat transfer coefficient of the clean exchanger are calculated using a modified Wilson method. Moreover, the heat transfer coefficients on the clean heat exchanger plates’ cold water side are determined based on experimental tests. The computational algorithm presented in this paper will make it possible to develop software to monitor and thus optimise the operation of district heating substations.

New multi-energy sources coupling a low-temperature sustainable central heating system with a multifunctional relay energy station

Due to short cost-effective heat transportation distance, the existing geothermal heating technologies cannot be used to develop the deep hydrothermal type geothermal fields situated far away from urban area. To solve the problem, a new multi-energy source coupling a low-temperature sustainable central heating system with a multifunctional relay energy station is put forward. As for the proposed central heating system, a compression heat pump integrated with a heat exchanger in the heating substation and a gas-fired water/lithium bromide single-effect absorption heat pump in the multifunctional relay energy station are used to lower return temperature of the primary network step by step. The proposed central heating system is analyzed by using thermodynamics and economics, and matching relationships between design temperature of return water and main line length of the primary network are discussed. The studied results indicate that, as for the proposed central heating system, the cost-effective main line length of the primary network can approach 33.8 km, and the optimal design return temperature of the primary network is 23 ℃. Besides, annual coefficient of performance and annual exergy efficiency of the proposed central heating system are about 3.01 and 42.7%, respectively.

Fault and anomaly detection in district heating substations: A survey on methodology and data sets

Fault and anomaly detection in district heating substations: A survey on methodology and data sets

Potential for supply temperature reduction of existing district heating substations

Reducing operating temperatures is a crucial goal for transforming district heating networks into sustainable systems as it allows the integration of low exergy heat (e.g. renewable, waste heat). Many criticalities arise when reducing operating temperatures in existing networks that are not designed to operate in these conditions. The criticalities occur at different levels: in the building, in the thermal substations, in the pipelines and in the production plants. In this paper, the reduction of supply temperature in existing district heating substations is analyzed. A methodology including a model of the thermal substation and a data analysis software is developed to estimate the potential temperature reduction that could be applied to existing substations. The application of the model to an existing large-scale district heating network in Northern Italy shows that all the analyzed substations are currently able to shift their operation from 120 °C to 104 °C, and that district heating supply temperatures around 90 °C can be realistically achieved with few improvements on the system.

Identifying supply-demand mismatches in district heating system based on association rule mining

Supply-demand mismatches in district heating system (DHS) may affect system's safe and stable operation without reasonable regulation actions in time. The accurate identification of supply-demand matching states is the prerequisite for heat balance regulation. However, this job is quite difficult and time-consuming, as DHS is typically a large time delay system and operates under various conditions. This paper proposes an association rule mining-based method to identify supply-demand mismatch from DHS operation data. Considering DHS's thermal inertia and fault-tolerance, the supply-demand mismatch rate is firstly defined along with its quantitative evaluation model. Then the theoretical intervals of the heating parameters are obtained by establishing association rules and rules post-processing. And a reasonable error band is decided by comparing the occurrence times of mismatches to balance identification accuracy and sensitivity. The proposed method is tested and verified in a typical DHS. The rules between primary supply temperature and relevant operation parameters are mined. An error band of ±7.5% is determined by comparison with historical operation data. The supply-demand mismatch rate is calculated to be −10%–15%. The identification results are validated by analyzing the heat substations' operation data including supply and return temperature, flow rate, and valve opening.

Experimental Study of District Heating Substations in a Hardware-in-the-Loop Test Rig

This study compares two district heating substation systems for implementation in rural district heating networks with non-retrofitted single- and two-family houses. The aim is to determine which system has the potential to provide lower return temperatures and/or lower power peak demand. A hardware-in-the-loop-test rig was utilized to measure the two district heating substations under real operation conditions. This experimental study demonstrates that load balancing of the district heating network is attainable with the district heating substation with storage. This is especially advantageous when there is a high demand for domestic hot water. Overall, both systems yield comparable return temperatures.

A novel combined model for heat load prediction in district heating systems

Accurate heat load prediction is essential for improving the operational efficiency of district heating systems (DHSs). Numerous heat load prediction models have been proposed to improve the accuracy and stability. However, previous prediction models are limited by training data and hyperparameters and cannot obtain accurate and stable prediction results. This study proposed a combined prediction model to overcome the limitations of a single model. In the proposed model, four classical single models were selected as individual models for prediction. Subsequently, the minimum sum of squares of the combined prediction errors algorithm was used to calculate the weighting coefficient of each individual model. The final prediction results were obtained by combining the prediction results of the four models. The 1-h historical operation data from three heat substations in a DHS in northeast China were adopted to evaluate the performance of the proposed model. The multi-step prediction experiment results of the three datasets revealed that the average mean absolute percentage error values of the proposed model for the one-step, two-step, and three-step predictions reached 2.6%, 4.9%, and 7.0%, respectively; these percentages were significantly lower than those of the four individual models and three representative combined models. Therefore, the proposed model has better prediction performance than previous models in terms of accuracy and stability and can provide a theoretical basis for the precise regulation of DHSs.

Investigation of Predictive Regulation Strategy of Secondary Loop in District Heating Systems

The urban energy system is greatly dependent on the District Heating System (DHS). However, many difficulties with regulation and control are caused by its large scale and numerous coupling variables. Additionally, reliance on manual experience means it can be challenging to guarantee heating comfort and effectiveness in the regulation of DHS. This paper proposes a data-driven temperature response prediction model to predict secondary loop supply temperature based on the heating substation’s historical operating status, valve opening degree, weather conditions, etc. Further, the XGBoost model was established in this article with different input and prediction steps. The results show that the XGBoost model with 72 input steps and 24 prediction steps has better performance. As an application example, the model was applied to an urban central heating system. Based on this data-driven model, different operation strategies on primary loop valve opening are compared for temperature response analysis. Operators can check the temperature responses of different valve control strategies before being applied. This paper guides the regulation behavior of the DHS, which is of great significance for the operation of the actual DHS.

Design of a 5th Generation District Heating Substation Prototype for a Real Case Study

The evolution of district heating networks is moving toward low temperatures in heat distribution with so called 4th generation networks. However, the lowest heat transfer fluid temperatures in district heating are achieved through ultra-low temperature networks, referred to as 5th generation district heating networks (5GDHNs). Low temperatures in heat distribution results in an extremely different configuration of 5GDHN compared to traditional district heating network, especially in the grid substation due to the inability to directly couple the grid with the buildings. This paper presents a detailed design of a 5th generation substation prototype, which is carried out to verify the proper operation and monitor the performance of this type of substation in a real case study. The prototype is fed by low-temperature waste heat, currently dissipated through evaporative towers, and will be built in the city of Brescia, Italy. The layout of the substation prototype, consisting of a bidirectional pumping system, a reversible water-to-water heat pump, an inertial thermal energy storage and a heat exchanger, is presented. An analysis is performed to figure out which refrigerant offers the best performance of the heat pump. In addition, fixed the refrigerant, the performance of the grid connected heat pump is found to be increased from 29.5% to 55.5% for both heating and cooling compared with a stand-alone air-to-water heat pump solution. Finally, the process flow diagram and the piping and instrumentation diagram of the substation are presented and commented.

Research on heat consumption detection, restoration and prediction methods for discontinuous heating substation

Under the goal of low-carbon heating, the control modes of heating substation will develop from traditional continuous heating to discontinuous heating, indicating that the existing methods for detection, restoration and prediction are not applicable. Based on data-knowledge analysis, this paper conducts a systematic study. Firstly, the associated parameters of the control mode were determined according to professional knowledge, including date, daily heat consumption and standard deviation, and the control mode of discontinuous heating substation was successfully identified by K-means. Secondary, by analyzing the internal heating parameters affecting the changing of heat consumption, the detection methods for different types of abnormal data are proposed. Thirdly, the restoration effect of statistics methods and Data-driven methods on abnormal data are compared, and data-driven methods with input parameters of secondary supply temperature, return temperature and temperature difference can successfully restore different abnormal heat consumption with an average error of less than 5%. Finally, the input parameters for heat consumption prediction of discontinuous heating stations, including outdoor temperature, time point and secondary return temperature were determined, and extreme gradient boosting had a higher prediction accuracy than support vector machine and multiple linear regression, with R2 >0.85.

Novel effective room temperature-based predictive feedback control method for large-scale district heating substation

• A predictive feedback control strategy based on effective room temperature is proposed. • The feasibility of the method is verified using an existing district heating substation. • The proposed method is flexible and performs well in terms of anti-interference. • The proposed method can reduce thermal energy consumption by 6.1%. Conventional district heating (DH) substations in China use a feed-forward adjustment method that predicts the water supply temperature based on the outdoor temperature. This method does not consider the delay of the pipe network and the thermal inertia of the building. Most importantly, the lack of closed-loop feedback on the indoor temperature results in high energy consumption and large fluctuations in room temperature. In this study, a predictive feedback system based on effective temperature control has been proposed to improve the quality of district heating. First, a dynamic simulation control model of a DH substation was created based on measured data. Then, through dynamic simulation analysis, the influence of the heating network delay on the room temperature was observed to be smaller than the influence of the building's thermal inertia, which confirmed that predictive feedback control based on effective temperature could be achieved. Finally, the new control method was compared to two conventional control methods. Based on the comparison with the two conventional controls, refining the timespan of the feed-forward control was found to be ineffective for improving room temperature stability owing to thermal inertia. The new control method demonstrated high control flexibility and strong anti-interference, and the indoor temperature fluctuation decreased from ±1.1 °C to ±0.3 °C compared with conventional control methods. In this case, under the premise that thermal comfort is not affected, the room temperature setting can be reduced by 0.5 °C, resulting in an energy saving of 6.1%, with a payback return period of less than a year. This method only requires installing room temperature sensing equipment and linking the feedback control algorithm to the original control system and is therefore easy to achieve.

Design method of general heat exchanger networks with heat pumps based on thermal energy discretization and matching

The design method of a general heat exchanger network with heat pumps (GHEN) is significant owing to its wide application in different industrial and building processes. However, the thermal energy grade of the energy pocket cannot be fully used in the pinch method, and the thermodynamic meaning of the optimal solution cannot be clearly explained by the mathematical programming method. In this paper, a design method with as little high-grade energy use as possible is proposed for GHENs based on thermal energy discretization and matching (TEDM). This method obeys thermodynamic laws and designs GHENs through programming. Two types of advanced systems, an absorption heat exchanger and a composite district heating substation, were designed using the TEDM method to demonstrate its correctness and practicability. The energy and economic performance of a GHEN in an actual scenario were analyzed and compared with a system designed using the pinch method. The results indicated that the advanced systems presented in the literature can be easily constructed using the TEDM method. Compared with the system designed using the pinch method, the exergy consumption and operational cost of the system designed using the TEDM method decreased by 14.9% and 30.9%, respectively. The TEDM method provides a more promising alternative to the pinch method for the design of GHENs.

Operational signature-based symbolic hierarchical clustering for building energy, operation, and efficiency towards carbon neutrality

Buildings are considered the enormous source of untapped energy efficiency potential in the global carbon neutrality. It is necessary to ensure that buildings are energy-efficient using operational pattern analytics and diagnostics. Therefore, this study proposes a novel symbolic hierarchical clustering method (named HOS-SAX) to evaluate the building system operation, efficiency, and energy usage patterns. The proposed HOS-SAX method is intended to enhance the existing methods that focus only on the energy usage characteristics and thus offer limited insights on the building system and operational efficiency. The proposed method consists of: (1) Holistic Operational Signature (HOS) and (2) HOS-based symbolic aggregate approximation (SAX) analyses. A HOS analysis is conducted to derive the representative operational signatures for building operation and efficiency using system-, building-, and weather-level data. Then, SAX is performed with the operational signatures derived from the HOS to cluster the building operation patterns. In a case study for a district heating substation serving residential buildings, the HOS-SAX cluster analysis showed 15 sections in the cluster map that visualize the: (1) energy usage, (2) design efficiency, and (3) control efficiency. The cluster map revealed that the sections that operated inefficiently account for approximately 71% of the entire operation period. Moreover, it is expected that the supply temperature of 0.87 °C can be reduced in the most inefficient sections.

A numerical assessment of a latent heat storage system for district heating substations

This work deals with the development and sizing of a latent heat storage system for an urban district heating system (UDHS). The investigated system is a cylindrical tank containing spherical phase change material (PCM) capsules. A physical model based on the apparent specific capacity method was adopted and validated to describe the phase transition within the capsules. The effects of various designs and operating factors on storage performance are detailed and addressed, including the thermal energy provided by the system during the discharge period, the melting temperature, tank volume, and water return temperature. The results show that the energy efficiency of such a device can be enhanced only through a judicious choice of the mentioned parameters. For example, it was found that increasing the UDHN thermal power demand influences the system's performance and leads to reduce the discharging duration. Based on the presented analyses, it can be concluded that the proposed numerical tool can be used by thermal designers of urban heating networks to size, optimise, and predict the actual dynamic behaviour of the storage system under real exploitation conditions.

The efficiency of innovative technologies for transition to 4th generation of district heating systems in Ukraine

The district heating system (DHS) is an efficient way for heat supply in urban areas. The efficiency of the DHS is considerably increased with the modern developments of technology, introducing 4th and 5th generations of centralised DHS. The existing DHS in Ukraine needs energy-efficient modernisation, where the reduction of heat losses at buildings and pipelines, the low temperatures of heat carriers, the use of heat pumps and individual heat substations with measuring devices and automated control are needed. The work proposes a novel methodology of transition to 4th generation DHS that allows its implementation with limited funds for investment. It consists of the step-by-step realisation of required innovations that allow optimising investments schedule and payback time. The methodology is illustrated by two case studies. In one of them, the university administrative building built 50 years ago is considered. The proposed improvement method can decrease the total energy consumption by 85%, with investments lower by 47% compared to traditional simultaneous realisation. The introduction of a new generation of DHS in Ukraine can be performed by gradual additions of new elements to existing DHS and integrating individual heat substations with heat pumps and renewable energy sources.

RESEARCH OF TECHNOLOGICAL POSSIBILITIES OF HEAT PUMPS’ APPLICATION IN DISTRICT HEATING OF RESIDENTIAL BUILDINGS

The main users of district heating (DH) systems are multi-apartment buildings – 53% of these buildings in Lithuania are supplied with heat from DH systems. Heating systems in buildings are the largest final consumer of energy, accounting for almost half of total energy consumption in many European countries. One of the measures planned for the Lithuanian energy policy in the heat sector of renewable energy sources (RES) until 2030 is the installation of heat pumps (HP) in the DH networks. The purpose of the study is to evaluate the technological possibilities of integrating HP into existing buildings to evaluate the low temperature heat supply. To evaluate the potential temperature lowering of the building heating system, a graph of the lowest possible building heating system temperatures is set, according to which the heat pump for the heating substation is selected, which would raise the temperature of the heat carrier supplied from DH networks to the required temperature for the heating and hot water systems of the building. Applying thermodynamic analysis, a mathematical model is developed that evaluates the ability of the HP to raise the temperature of the supplied heat carrier at the heat substation and determines the energy efficiency of such a solution. During the simulation, two alternatives of constant (regardless of outdoor air temperature) heat carrier temperatures supplied from DH networks were considered: 60 °C (alternative A) and 55 °C (alternative B). To adapt the most appropriate option for the integration of HP, it would be appropriate to combine both alternatives, i. y. to supply 60 °C from the DH network in the cold period of the year and 55 °C in the warm period of the year.

Determination of the Fouling Degree of the Heat Substation Based on Tests of Plate Heat Exchangers

The subject of the following considerations is research on plate heat exchangers. The research concerns the determination of the degree of fouling of plate heat exchangers with mineral deposits in the water. The method proposed in this publication for determining the thermal resistance of fouling is based on the determination of the overall heat transfer coefficient for a clean heat exchanger (operating under laboratory conditions) and a fouled one (operating in a heat substation). With the overall heat transfer coefficients determined, the difference in thermal resistance for the fouled and clean heat exchanger and thus the total thermal resistance of the fouling can be determined. The calculation algorithm presented in the work will allow the creation of software that enables monitoring, thus optimizing work heating centers.

Data augmentation for improving heating load prediction of heating substation based on TimeGAN

Heating load predictions serve as one of the fundamental tasks in heating operation management. Many studies have used data-driven methods to build prediction models, and the quantity and quality of training data are key factors affecting the model performance. However, for some special cases, such as new heating substation and the end period of heating with different load characteristics, sufficient and high-quality data cannot be provided for model training, resulting in low accuracy of the model. In this paper, TimeGAN is applied in the heating field for the first time to augment the data and improve the prediction accuracy of the model. Results show that the prediction error reduces by 50% and CV-RMSE can reach 0.0405 after using TimeGAN in the early period of heating, and the accuracy is highest when the synthetic data are three times of original data. For the mid and end period of heating, the prediction errors can also be reduced by 3%–8% compared with training on original data, and the data amount reaches 15,000–30000, the performance of the model reaches the best.