A district heating and hot water supply system is presented which synthetically utilizes geothermal energy,solar thermal energy and natural gas thermal energy.The multi-energy utilization system has been set at the ne...A district heating and hot water supply system is presented which synthetically utilizes geothermal energy,solar thermal energy and natural gas thermal energy.The multi-energy utilization system has been set at the new campus of Tianjin Polytechnic University(TPU),A couple of deep geothermal wells which are 2 300 m in depth were dug,Deep geothermal energy cascade utilization is achieved by two stages of plate heat exchangers(PHE) and two stages of water source heat pumps(WSHP).Shallow geothermal energy is used in assistant heating by two ground coupled heat pumps(GCHPs) with 580 vertical ground wells which are 120 m in depth.Solar thermal energy collected by vacuum tube arrays(VTAs) and geothermal energy are complementarily utilized to make domestic hot water.Superfluous solar energy can be stored in shallow soil for the GCHP utilization.The system can use fossil fuel thermal energy by two natural gas boilers(NGB) to assist in heating and making hot water.The heating energy efficiency was measured in the winter of 2010-2011.The coefficients of performance(COP) under different heating conditions are discussed.The performance of hot water production is tested in a local typical winter day and the solar thermal energy utilization factor is presented.The rusults show that the average system COP is 5.75 or 4.96 under different working conditions,and the typical solar energy utilization factor is 0.324.展开更多
The control of heat exchange stations in district heating system is critical for the overall energy efficiency and can be very difficult due to high level of complexity. A conventional method is to control the equipme...The control of heat exchange stations in district heating system is critical for the overall energy efficiency and can be very difficult due to high level of complexity. A conventional method is to control the equipment such that the temperature of hot water supply is maintained at a set-point that may be a fixed value or be compensated against the external temperature. This paper presents a novel scheme that can determine the optimal set-point of hot water supply that maximizes the energy efficiency whilst providing sufficient heating capacity to the load. This scheme is based on Adaptive Neuro-Fuzzy Inferential System. The aim of this study is to improve the overall performance of district heating systems.展开更多
The most economical and rational means of heat supply for city inhabitants are district heating systems. Heat generated in power plants and large heat sources is cheaper than heat from individual sources. The reason f...The most economical and rational means of heat supply for city inhabitants are district heating systems. Heat generated in power plants and large heat sources is cheaper than heat from individual sources. The reason for that is the amount of the generated heat and the used fuel （coal for most heat sources）. District heating, a very important energy sub-sector for the Polish economy, provides heat supply to centralised heating systems, which, on average, satisfy 72% of the demand for heat in Polish cities. Therefore, several million Polish citizens use heat from district heating systems that produce heat in professional, industrial and municipal power plants. In Europe, over 100 million citizens use district heating systems. The present situation of the Polish district heating sector is a result of Poland＇s transformation that took place at the beginning of the 1990s. The reform put the obligation of heat supply on the local authorities, on the municipality, instead of the state. Along with the transformation, district heating also made huge technological and technical progress. Increasing expectations of recipients posed new challenges for the branch, however.展开更多
The upgrading of the DH （district heating） system through installing WSN （wireless sensor networks）--a technology by which to monitor and control quality operation of the DH system will lead to more effective use ...The upgrading of the DH （district heating） system through installing WSN （wireless sensor networks）--a technology by which to monitor and control quality operation of the DH system will lead to more effective use of thermal energy, enabling also the provision of quality customer services, as the data concerning the status of the existing networks is available in a timely manner, and in the stated amounts. Over the last decades, the use of WSN systems in enabling quality monitoring of heat production and supply process has been widely discussed among various researchers and industry experts, but has been little deployed in practice. These researchers and industry experts have analysed the advantages and constraints related to the use of the WSN in district heating. A pilot project conducted by Riga Heat （the main heating supplier in Riga, Latvia） has allowed to gain a real life experience as to the use of the WSN system in district in-house heating substations, and is deemed to be a major step towards future development of WSN technologies.展开更多
The district heating company ＂Rigas siltums＂ operates biomass fuelled boiler in Riga city. Three systems consisting ofbiomass boilers having a comparatively similar heat capacity and particle abatement units like mu...The district heating company ＂Rigas siltums＂ operates biomass fuelled boiler in Riga city. Three systems consisting ofbiomass boilers having a comparatively similar heat capacity and particle abatement units like multicyclons, electrostatic precipitators and flue gas condensers are compared. The main goal of the study is to evaluate the boiler plant as a system where solid particles are both emitted and caught. The results show that, the particulate matter can be efficiently trapped from flue gases by the particle abatement technologies, and the electrostatic precipitator with sufficiently large collection surfaces is able to provide appropriate flue gas treatment of the particulate matter in the biomass boilers also without pre-cleaning of the flue gas in multieyelons.展开更多
As the improvement of district heating systems,the fine-tuning of operational equipment has become a promising direction.However,in the practical district heating systems,relying solely on manual control and the exist...As the improvement of district heating systems,the fine-tuning of operational equipment has become a promising direction.However,in the practical district heating systems,relying solely on manual control and the existing basic models,the dynamic hydraulic-thermal process is hard to cover.Consequently,the primary side control in the current district heating system mainly results in the over or under-supply of heating substations.This article constructs a dynamic hydraulic-thermal model and performs a balanced operation strategies optimization based on the hydraulic-thermal model.The linearization and iterative optimization process are adopted to simplify the hydraulic and thermal modeling for the single pipe,and the hydraulic and thermal calculation are conducted sequentially.For the primary side network in the various operation conditions,the dynamic hydraulic-thermal model is established.The heating supply imbalance of the primary side return temperatures among different heating substations is defined and optimized based on the dynamic hydraulic-thermal model and the particle swarm optimization algorithm.In the case analysis,the results of heating supply imbalance before and after optimization are 0.81 K and 0.47 K,respectively,with a 42.0%reduction in heating imbalances after optimization.The proposed method could contribute to the fine-tuning of heating substations and the reduction of energy waste due to the imbalanced heating supply,which is significant for the operation strategies of district heating systems.展开更多
As district heating networks evolve to meet climate-neutral objectives,optimizing their control under heterogeneous building characteristics and dynamic environmental conditions remains a significant challenge.Traditi...As district heating networks evolve to meet climate-neutral objectives,optimizing their control under heterogeneous building characteristics and dynamic environmental conditions remains a significant challenge.Traditional control strategies often lack the adaptability necessary to account for building-specific dynamics and to ensure real-time adherence to operational safety constraints.In this work,we present an integrated machine learning-based framework that combines an adaptive context-aware transformer model with deep reinforcement learning to address these limitations.The proposed approach introduces an adaptive context-aware transformer as a predictive environment within a Deep Q-Network(DQN)framework,enabling data-driven,building-specific control of district heating systems.Utilizing real-world data from 148 residential buildings across Sweden and Finland,the model incorporates contextual embeddings and temporal features to predict indoor temperature trajectories with high accuracy,achieving root mean square error values between 0.18-0.24℃ for Swedish buildings and 0.26-0.32℃ for Finnish buildings.The DQN agent leverages these predictions to optimize heating control while ensuring compliance with operational safety limits and preserving occupant comfort.Experimental results demonstrate significant energy savings,with mid-rise buildings achieving up to 14.85%reduction in energy consumption,and peak seasonal savings exceeding 20%during spring months.This integrated approach illustrates the potential for substantial energy optimization and reliable indoor climate management in future district heating networks.展开更多
Fault detection in district heating(DH)substations is crucial for maintaining energy efficiency.However,existing methods often fall short and rely on labelled data or global analysis that may miss subtle anomalies.We ...Fault detection in district heating(DH)substations is crucial for maintaining energy efficiency.However,existing methods often fall short and rely on labelled data or global analysis that may miss subtle anomalies.We introduce HEAT,a Hierarchical-constrained Encoder-Assisted Time series clustering method designed to enhance fault detection in DH substations.HEAT operates in a two-phase approach:first,it approximates a relative network topology using a constraint hierarchical clustering algorithm on supply temperature profiles.HEAT incorporates a Convolutional AutoEncoder(CAE)for dimensionality reduction of the time series data and uses adaptive soft constraints in the linkage function,enabling both minimum and maximum cluster size constraints while supporting domain knowledge,e.g.,must-link and cannot-link constraints,using a constraint matrix.Second,we use the topology approximation to perform intra-cluster analysis using Mean Absolute Deviation(MAD)z-scores,with neighbouring substations serving as a validation mechanism,allowing for robust analysis without requiring labelled data.Experimental results demonstrate that HEAT outperforms conventional clustering methods while achieving 74.1%sensitivity and 95.5%specificity in fault detection,significantly improving over typical global analysis.HEAT not only identified major faults(e.g.,sensor issues,valve failures)but also detected subtle anomalies(e.g.,secondary leakages)while minimising false positives.This unsupervised method offers a viable and flexible solution for DH networks,improving operational efficiency and energy sustainability without disclosing sensitive information.展开更多
The integrated electricity-heat-hydrogen system(IEHHS)facilitates the efficient utilization of multiple energy sources,while the operational flexibility of IEHHS is hindered by the high heat inertia of alkaline electr...The integrated electricity-heat-hydrogen system(IEHHS)facilitates the efficient utilization of multiple energy sources,while the operational flexibility of IEHHS is hindered by the high heat inertia of alkaline electrolyzers(AELs)and the variations of renewable energy.In this paper,we propose a robust scheduling of IEHHS considering the bidirectional heat exchange(BHE)between AELs and district heating networks(DHNs).First,we propose an IEHHS model to coordinate the operations of AELs,active distribution networks(ADNs),and DHNs.In particular,we propose a BHE that not only enables the waste heat recovery for district heating but also accelerates the thermal dynamics in AELs.Then,we formulate a two-stage robust optimization(RO)problem for the IEHHS operation to consider the variability of renewable energy in ADNs.We propose a new solution method,i.e.,multi-affine decision rule(MADR),to solve the two-stage RO problem with less conservatism.The simulation results show that the operational flexibility of IEHHS with BHE is remarkably improved compared with that only with unidirectional heat exchange(UHE).Compared with the traditional affine decision rule(ADR),the MADR effectively reduces the IEHHS operating costs while guaranteeing the reliability of scheduling strategies.展开更多
The integration of continuously varying and not easily predictable wind power generation is affecting the stability of the power system and leads to increasing demand for balancing services.In this study,a short-term ...The integration of continuously varying and not easily predictable wind power generation is affecting the stability of the power system and leads to increasing demand for balancing services.In this study,a short-term operation model of a district heating system is proposed to optimally schedule the production of both heat and power in a system with high wind power penetration.The application of the model in a case study system shows the increased flexibility offered by the coordination of power generation,consumption and heat storage units which are available in district heating systems.展开更多
The ongoing development of cogeneration technology has promoted public awareness on the integration of different types of energy systems.Integration of power and heating systems is the most common approach for energy ...The ongoing development of cogeneration technology has promoted public awareness on the integration of different types of energy systems.Integration of power and heating systems is the most common approach for energy transmission.The heat and power coupling of combined heat and power(CHP)units constrains the improvement of flexibility to accommodate more wind power,especially in winter.To address this problem,electrical boilers(EBs)are utilized as independent heat sources in one heat station to enhance their flexibility.This paper proposes a subsidy based bi-level optimal model.The objective of the upper problem is to minimize the operating cost,while the lower problem is to maximize the benefits of CHP and EBs based on the subsidy signals sent by the power system operator(PSO).The bi-level model is reformulated as a single-level linear problem by Karush Kuhn Turck(KKT)conditions and recast to a mix integer quadratic program using strong duality theory.Numerical results performed on an IEEE six-bus system with a eight-node district heating system validate the proposed model.The results demonstrate that the subsidy strategies can make the EB and CHP units operate according to the system operators’preferences to accommodate more wind power.展开更多
Building a trading market can promote energy conservation provided that the trading method is deter- mined. Energy consumption for heat supply is huge. Tianjin Municipal Government is planning to establish an energy e...Building a trading market can promote energy conservation provided that the trading method is deter- mined. Energy consumption for heat supply is huge. Tianjin Municipal Government is planning to establish an energy efficiency trading platform for district heating taking into consideration the experience in carbon trading market and specific situation in Tianjin. This paper presented an in-depth analysis of the district heating industry in Tianjin municipality, and identified the potentials of energy saving and carbon dioxide emissions reduction. Since energy efficiency was closely related to different heating source technologies, baselines were determined for boiler plants and thermal power plants respectively. Three scenarios were discussed for baseline determination. 472 boiler plants were surveyed and operational data relating to energy consumption were collected. Through data analysis, 27 boiler plants which have reasonable recorded energy consumption values were chosen as samples. By analyzing the dataset and referring to the related standards, method of determining the baseline for district heating carbon market was established. Finxally, the baseline for boiler plant was determined to be 52.0 kgce/GJ, and that for thermal power plant was 43.0 kgce/GJ in 2011. Carbon abatement against the baselines above was calculated and considerable carbon dioxide emissions reduction could be achieved.展开更多
The district heating system(DHS)consumes a lot of energy in winter,and its control accuracy needs to be improved urgently.To apply advanced process control(APC)in DHS,the thermal dynamic model of the existing building...The district heating system(DHS)consumes a lot of energy in winter,and its control accuracy needs to be improved urgently.To apply advanced process control(APC)in DHS,the thermal dynamic model of the existing buildings is essential.This paper uses the subspace method which is a data-driven approach for modelling the thermal dynamics of the building.The model’s performance is analyzed using the collected data,and the differences compared to the classical methods are also analyzed.The method reduces the RMSE by about 20%compared with the ARX model for the same complexity.Subsequently,the analysis of the training residuals indicates that the estimate of periodic intra-building disturbance can be obtained by minimizing the training residuals.By introducing the estimated disturbance function,the RMSE on the test set is further reduced by 26%.At the end of the article,a simple parameter extrapolation experiment is conducted,and the result shows that the parameters can be extrapolated to other buildings without large errors.展开更多
Conventional approaches towards energy-system modelling and operation are based upon the system design and performance optimization.In system-design optimization,the thermal or mechanical characteristics of the system...Conventional approaches towards energy-system modelling and operation are based upon the system design and performance optimization.In system-design optimization,the thermal or mechanical characteristics of the systems providing for the heat or electricity demands were derived separately without integration with the energy source and without interaction with demand,which results in low-efficiency energy performance.This paper presents a key review on the integration of biomass-powered combined heat and power(BCHP)systems in district-heating systems as well as coupling with thermal-energy storage.In BCHP design,the appropriate sizing of the associated components as part of the district-heating system is very important to provide the optimal dispatch strategy as well as minimized cost and environmental impact while it co-operates with thermal-energy storage.Future strategies for the feasibility,evaluation and integration of biomass-powered energy systems in the context of district systems are also studied.展开更多
The paper presents a novel demand-responsive control strategy to be equipped centrally at the district level for district heating systems.The demand-responsive feature was maintained as to both the direct and the indi...The paper presents a novel demand-responsive control strategy to be equipped centrally at the district level for district heating systems.The demand-responsive feature was maintained as to both the direct and the indirect substation configurations(by basing on their rating measures)in order to achieve lowest possible return temper-ature degrees from the end-user substations.Different than the traditional weather-compensation based supply temperature resetting,the new control strategy was formulated to adjust the supply temperature at the district level as to the cooling performance at the end-user substations.Two different simulations were carried out in order to quantify the benefits of the novel control strategy as compared to the traditional weather-compensation,equipped both at the substation level and the district level.The results obtained showed that the new control strategy,when considering the electricity loss at the heat production plant,shows superiority when compared to other control strategies.展开更多
Decarbonisation of district heating and cooling(DHC)system in Helsinki metropolitan area requires investments in new energy technologies and approaches to replace fossil fuel fired district heating(DH)production.Inves...Decarbonisation of district heating and cooling(DHC)system in Helsinki metropolitan area requires investments in new energy technologies and approaches to replace fossil fuel fired district heating(DH)production.Invest-ment paths involving(a)DH heat pumps(HPs)from low quality heat sources and(b)small modular nuclear reactors(SMR)are compared by utilising investment analysis based on optimisation model depicting the as-sumed 2030 situation.Several scenarios,with varying assumptions concerning existing DHC system,investment costs and electricity prices,are analysed in terms of new capacity and total annualised costs.The results indicate that the SMR option is more cost-efficient than the HP option with 4-8€/MWh difference in operation costs including annualised investments.Biomass fired boiler investments,enabled in both options,are preferred to HP investments in most scenarios.The cost-efficiency of HP investments is sensitive to investment cost,whereas SMR investments are relatively stable to investment cost variations.Varying electricity market prices affect cost-efficiency of large-scale HPs,and investments in SMR cogeneration units take place only with high electricity prices.展开更多
Northwest China has abundant solar energy resources and a large demand for winter heating.Using solar energy for centralized heating is a clean and effective way to solve local heating problems.While present studies u...Northwest China has abundant solar energy resources and a large demand for winter heating.Using solar energy for centralized heating is a clean and effective way to solve local heating problems.While present studies usually decoupled solar heating stations and the heating network in the optimization design of centralized solar heating systems,this study developed a joint multi-objective optimization model for the equipment capacity and the diameters of the heating network pipes of a centralized solar district heating system,using minimum total life cycle cost and CO_(2)emission of the system as the optimization objectives.Three typical cities in northwest China with different solar resource conditions(Lhasa,Xining,and Xi'an)were selected as cases for analysis.According to the results,the solar heating system designed using the method proposed in this study presents lower economic cost and higher environmental protection in comparison to separately optimizing the design of the solar heating station and the heating network.Furthermore,the solar fraction of the optimal systems are 90%,70%,and 31%for Lhasa,Xining,and Xi'an,and the minimum water supply temperatures are 55℃,50℃,and 65℃for an optimal economy and 55℃,45℃,and 45℃for optimal environmental protection,respectively.It was also established that the solar collector price has a greater impact on the equipment capacity of the solar heating station than the gas boiler price.展开更多
When regulating a pipe network according to user demand,hydraulic balance and power consumption are crucial factors for a multi-source looped-pipe network applying distributed variable-speed pumps compared to the conv...When regulating a pipe network according to user demand,hydraulic balance and power consumption are crucial factors for a multi-source looped-pipe network applying distributed variable-speed pumps compared to the conventional central circulating pump system.In this paper,the influence of the fill point on power consumption and hydraulic balance of the multi-source looped-pipe network was studied.A mathematical model for electricity energy consumption analysis was built and calculated for a large sized looped-pipe network with multiple heat sources and distributed variable-speed pumps.The hydraulic calculation models of each single element,such as pipe,distribution pump,valve,replenishment pump,heat source and substation,were built.A case located in Dezhou city,China was analyzed.The results showed that:the maximum power saving(39.2%)could be achieved when each heat source had its own fill point,but the heat sources would not meet their design flows;to meet the design flows of all the heat sources,only one fill point should be necessarily located near the heat source with the lowest flow rate to get the expected hydraulic stability and energy saving.展开更多
In the paper, the concept of the heating network coupling is introduced. Amathematical modal of heating network in water power is established. The coupling degree of theheating network is also calculated trough the li...In the paper, the concept of the heating network coupling is introduced. Amathematical modal of heating network in water power is established. The coupling degree of theheating network is also calculated trough the liquid increasing matrix展开更多
District heating networks (DHNs) provide an efficient heat distribution solution in urban areas, accomplished through interconnected and insulated pipes linking local heat sources to local consumers. This efficiency i...District heating networks (DHNs) provide an efficient heat distribution solution in urban areas, accomplished through interconnected and insulated pipes linking local heat sources to local consumers. This efficiency is further enhanced by the capacity of these networks to integrate renewable heat sources and thermal storage systems. However, integration of these systems adds complexity to the physical dynamics of the network, necessitating complex dynamic simulation models. These dynamic physical simulations are computationally expensive, limiting their adoption, particularly in large-scale networks. To address this challenge, we propose a methodology utilizing Artificial Neural Networks (ANNs) to reduce the computational time associated with the DHNs dynamic simulations. Our approach consists in replacing predefined clusters of substations within the DHNs with trained surrogate ANNs models, effectively transforming these clusters into single nodes. This creates a hybrid simulation framework combining the predictions of the ANNs models with the accurate physical simulations of remaining substation nodes and pipes. We evaluate different architectures of Artificial Neural Network on diverse clusters from four synthetic DHNs with realistic heating demands. Results demonstrate that ANNs effectively learn cluster dynamics irrespective of topology or heating demand levels. Through our experiments, we achieved a 27% reduction in simulation time by replacing 39% of consumer nodes while maintaining acceptable accuracy in preserving the generated heat powers by sources.展开更多
基金Project(2010DFA72740-06) supported by International Science & Technology Cooperation Program of China
文摘A district heating and hot water supply system is presented which synthetically utilizes geothermal energy,solar thermal energy and natural gas thermal energy.The multi-energy utilization system has been set at the new campus of Tianjin Polytechnic University(TPU),A couple of deep geothermal wells which are 2 300 m in depth were dug,Deep geothermal energy cascade utilization is achieved by two stages of plate heat exchangers(PHE) and two stages of water source heat pumps(WSHP).Shallow geothermal energy is used in assistant heating by two ground coupled heat pumps(GCHPs) with 580 vertical ground wells which are 120 m in depth.Solar thermal energy collected by vacuum tube arrays(VTAs) and geothermal energy are complementarily utilized to make domestic hot water.Superfluous solar energy can be stored in shallow soil for the GCHP utilization.The system can use fossil fuel thermal energy by two natural gas boilers(NGB) to assist in heating and making hot water.The heating energy efficiency was measured in the winter of 2010-2011.The coefficients of performance(COP) under different heating conditions are discussed.The performance of hot water production is tested in a local typical winter day and the solar thermal energy utilization factor is presented.The rusults show that the average system COP is 5.75 or 4.96 under different working conditions,and the typical solar energy utilization factor is 0.324.
文摘The control of heat exchange stations in district heating system is critical for the overall energy efficiency and can be very difficult due to high level of complexity. A conventional method is to control the equipment such that the temperature of hot water supply is maintained at a set-point that may be a fixed value or be compensated against the external temperature. This paper presents a novel scheme that can determine the optimal set-point of hot water supply that maximizes the energy efficiency whilst providing sufficient heating capacity to the load. This scheme is based on Adaptive Neuro-Fuzzy Inferential System. The aim of this study is to improve the overall performance of district heating systems.
文摘The most economical and rational means of heat supply for city inhabitants are district heating systems. Heat generated in power plants and large heat sources is cheaper than heat from individual sources. The reason for that is the amount of the generated heat and the used fuel （coal for most heat sources）. District heating, a very important energy sub-sector for the Polish economy, provides heat supply to centralised heating systems, which, on average, satisfy 72% of the demand for heat in Polish cities. Therefore, several million Polish citizens use heat from district heating systems that produce heat in professional, industrial and municipal power plants. In Europe, over 100 million citizens use district heating systems. The present situation of the Polish district heating sector is a result of Poland＇s transformation that took place at the beginning of the 1990s. The reform put the obligation of heat supply on the local authorities, on the municipality, instead of the state. Along with the transformation, district heating also made huge technological and technical progress. Increasing expectations of recipients posed new challenges for the branch, however.
文摘The upgrading of the DH （district heating） system through installing WSN （wireless sensor networks）--a technology by which to monitor and control quality operation of the DH system will lead to more effective use of thermal energy, enabling also the provision of quality customer services, as the data concerning the status of the existing networks is available in a timely manner, and in the stated amounts. Over the last decades, the use of WSN systems in enabling quality monitoring of heat production and supply process has been widely discussed among various researchers and industry experts, but has been little deployed in practice. These researchers and industry experts have analysed the advantages and constraints related to the use of the WSN in district heating. A pilot project conducted by Riga Heat （the main heating supplier in Riga, Latvia） has allowed to gain a real life experience as to the use of the WSN system in district in-house heating substations, and is deemed to be a major step towards future development of WSN technologies.
文摘The district heating company ＂Rigas siltums＂ operates biomass fuelled boiler in Riga city. Three systems consisting ofbiomass boilers having a comparatively similar heat capacity and particle abatement units like multicyclons, electrostatic precipitators and flue gas condensers are compared. The main goal of the study is to evaluate the boiler plant as a system where solid particles are both emitted and caught. The results show that, the particulate matter can be efficiently trapped from flue gases by the particle abatement technologies, and the electrostatic precipitator with sufficiently large collection surfaces is able to provide appropriate flue gas treatment of the particulate matter in the biomass boilers also without pre-cleaning of the flue gas in multieyelons.
基金supported by National Natural Science Foundation of China(Grant No.51806190)supported by National Key R&D Program of China(Grant No.2023YFE0108600).
文摘As the improvement of district heating systems,the fine-tuning of operational equipment has become a promising direction.However,in the practical district heating systems,relying solely on manual control and the existing basic models,the dynamic hydraulic-thermal process is hard to cover.Consequently,the primary side control in the current district heating system mainly results in the over or under-supply of heating substations.This article constructs a dynamic hydraulic-thermal model and performs a balanced operation strategies optimization based on the hydraulic-thermal model.The linearization and iterative optimization process are adopted to simplify the hydraulic and thermal modeling for the single pipe,and the hydraulic and thermal calculation are conducted sequentially.For the primary side network in the various operation conditions,the dynamic hydraulic-thermal model is established.The heating supply imbalance of the primary side return temperatures among different heating substations is defined and optimized based on the dynamic hydraulic-thermal model and the particle swarm optimization algorithm.In the case analysis,the results of heating supply imbalance before and after optimization are 0.81 K and 0.47 K,respectively,with a 42.0%reduction in heating imbalances after optimization.The proposed method could contribute to the fine-tuning of heating substations and the reduction of energy waste due to the imbalanced heating supply,which is significant for the operation strategies of district heating systems.
基金supported by the Industrial Graduate School Collaborative AI&Robotics funded by the Swedish Knowledge Foun-dation Dnr:20190128in collaboration with industrial partner EcoGuard AB.
文摘As district heating networks evolve to meet climate-neutral objectives,optimizing their control under heterogeneous building characteristics and dynamic environmental conditions remains a significant challenge.Traditional control strategies often lack the adaptability necessary to account for building-specific dynamics and to ensure real-time adherence to operational safety constraints.In this work,we present an integrated machine learning-based framework that combines an adaptive context-aware transformer model with deep reinforcement learning to address these limitations.The proposed approach introduces an adaptive context-aware transformer as a predictive environment within a Deep Q-Network(DQN)framework,enabling data-driven,building-specific control of district heating systems.Utilizing real-world data from 148 residential buildings across Sweden and Finland,the model incorporates contextual embeddings and temporal features to predict indoor temperature trajectories with high accuracy,achieving root mean square error values between 0.18-0.24℃ for Swedish buildings and 0.26-0.32℃ for Finnish buildings.The DQN agent leverages these predictions to optimize heating control while ensuring compliance with operational safety limits and preserving occupant comfort.Experimental results demonstrate significant energy savings,with mid-rise buildings achieving up to 14.85%reduction in energy consumption,and peak seasonal savings exceeding 20%during spring months.This integrated approach illustrates the potential for substantial energy optimization and reliable indoor climate management in future district heating networks.
文摘Fault detection in district heating(DH)substations is crucial for maintaining energy efficiency.However,existing methods often fall short and rely on labelled data or global analysis that may miss subtle anomalies.We introduce HEAT,a Hierarchical-constrained Encoder-Assisted Time series clustering method designed to enhance fault detection in DH substations.HEAT operates in a two-phase approach:first,it approximates a relative network topology using a constraint hierarchical clustering algorithm on supply temperature profiles.HEAT incorporates a Convolutional AutoEncoder(CAE)for dimensionality reduction of the time series data and uses adaptive soft constraints in the linkage function,enabling both minimum and maximum cluster size constraints while supporting domain knowledge,e.g.,must-link and cannot-link constraints,using a constraint matrix.Second,we use the topology approximation to perform intra-cluster analysis using Mean Absolute Deviation(MAD)z-scores,with neighbouring substations serving as a validation mechanism,allowing for robust analysis without requiring labelled data.Experimental results demonstrate that HEAT outperforms conventional clustering methods while achieving 74.1%sensitivity and 95.5%specificity in fault detection,significantly improving over typical global analysis.HEAT not only identified major faults(e.g.,sensor issues,valve failures)but also detected subtle anomalies(e.g.,secondary leakages)while minimising false positives.This unsupervised method offers a viable and flexible solution for DH networks,improving operational efficiency and energy sustainability without disclosing sensitive information.
基金supported by the Science and Technology Project of State Grid“Research and Application of Wide Area Multi energy Storage Collaborative Optimization and Control Technology in Provincial Power Grid”.
文摘The integrated electricity-heat-hydrogen system(IEHHS)facilitates the efficient utilization of multiple energy sources,while the operational flexibility of IEHHS is hindered by the high heat inertia of alkaline electrolyzers(AELs)and the variations of renewable energy.In this paper,we propose a robust scheduling of IEHHS considering the bidirectional heat exchange(BHE)between AELs and district heating networks(DHNs).First,we propose an IEHHS model to coordinate the operations of AELs,active distribution networks(ADNs),and DHNs.In particular,we propose a BHE that not only enables the waste heat recovery for district heating but also accelerates the thermal dynamics in AELs.Then,we formulate a two-stage robust optimization(RO)problem for the IEHHS operation to consider the variability of renewable energy in ADNs.We propose a new solution method,i.e.,multi-affine decision rule(MADR),to solve the two-stage RO problem with less conservatism.The simulation results show that the operational flexibility of IEHHS with BHE is remarkably improved compared with that only with unidirectional heat exchange(UHE).Compared with the traditional affine decision rule(ADR),the MADR effectively reduces the IEHHS operating costs while guaranteeing the reliability of scheduling strategies.
基金sponsored by Swe GRIDS,the Swedish Centre for Smart Grids and Energy Storage,www.swegrids.se.
文摘The integration of continuously varying and not easily predictable wind power generation is affecting the stability of the power system and leads to increasing demand for balancing services.In this study,a short-term operation model of a district heating system is proposed to optimally schedule the production of both heat and power in a system with high wind power penetration.The application of the model in a case study system shows the increased flexibility offered by the coordination of power generation,consumption and heat storage units which are available in district heating systems.
基金This work was supported by the National Key Research and Development Program of China(No.2017YFB0902100).
文摘The ongoing development of cogeneration technology has promoted public awareness on the integration of different types of energy systems.Integration of power and heating systems is the most common approach for energy transmission.The heat and power coupling of combined heat and power(CHP)units constrains the improvement of flexibility to accommodate more wind power,especially in winter.To address this problem,electrical boilers(EBs)are utilized as independent heat sources in one heat station to enhance their flexibility.This paper proposes a subsidy based bi-level optimal model.The objective of the upper problem is to minimize the operating cost,while the lower problem is to maximize the benefits of CHP and EBs based on the subsidy signals sent by the power system operator(PSO).The bi-level model is reformulated as a single-level linear problem by Karush Kuhn Turck(KKT)conditions and recast to a mix integer quadratic program using strong duality theory.Numerical results performed on an IEEE six-bus system with a eight-node district heating system validate the proposed model.The results demonstrate that the subsidy strategies can make the EB and CHP units operate according to the system operators’preferences to accommodate more wind power.
文摘Building a trading market can promote energy conservation provided that the trading method is deter- mined. Energy consumption for heat supply is huge. Tianjin Municipal Government is planning to establish an energy efficiency trading platform for district heating taking into consideration the experience in carbon trading market and specific situation in Tianjin. This paper presented an in-depth analysis of the district heating industry in Tianjin municipality, and identified the potentials of energy saving and carbon dioxide emissions reduction. Since energy efficiency was closely related to different heating source technologies, baselines were determined for boiler plants and thermal power plants respectively. Three scenarios were discussed for baseline determination. 472 boiler plants were surveyed and operational data relating to energy consumption were collected. Through data analysis, 27 boiler plants which have reasonable recorded energy consumption values were chosen as samples. By analyzing the dataset and referring to the related standards, method of determining the baseline for district heating carbon market was established. Finxally, the baseline for boiler plant was determined to be 52.0 kgce/GJ, and that for thermal power plant was 43.0 kgce/GJ in 2011. Carbon abatement against the baselines above was calculated and considerable carbon dioxide emissions reduction could be achieved.
文摘The district heating system(DHS)consumes a lot of energy in winter,and its control accuracy needs to be improved urgently.To apply advanced process control(APC)in DHS,the thermal dynamic model of the existing buildings is essential.This paper uses the subspace method which is a data-driven approach for modelling the thermal dynamics of the building.The model’s performance is analyzed using the collected data,and the differences compared to the classical methods are also analyzed.The method reduces the RMSE by about 20%compared with the ARX model for the same complexity.Subsequently,the analysis of the training residuals indicates that the estimate of periodic intra-building disturbance can be obtained by minimizing the training residuals.By introducing the estimated disturbance function,the RMSE on the test set is further reduced by 26%.At the end of the article,a simple parameter extrapolation experiment is conducted,and the result shows that the parameters can be extrapolated to other buildings without large errors.
文摘Conventional approaches towards energy-system modelling and operation are based upon the system design and performance optimization.In system-design optimization,the thermal or mechanical characteristics of the systems providing for the heat or electricity demands were derived separately without integration with the energy source and without interaction with demand,which results in low-efficiency energy performance.This paper presents a key review on the integration of biomass-powered combined heat and power(BCHP)systems in district-heating systems as well as coupling with thermal-energy storage.In BCHP design,the appropriate sizing of the associated components as part of the district-heating system is very important to provide the optimal dispatch strategy as well as minimized cost and environmental impact while it co-operates with thermal-energy storage.Future strategies for the feasibility,evaluation and integration of biomass-powered energy systems in the context of district systems are also studied.
基金supported by the‘European Union’,the‘Euro-pean Regional Development Fund(ERDF)’,‘Flanders Innovation&En-trepreneurship’and the‘Province of Limburg’.
文摘The paper presents a novel demand-responsive control strategy to be equipped centrally at the district level for district heating systems.The demand-responsive feature was maintained as to both the direct and the indirect substation configurations(by basing on their rating measures)in order to achieve lowest possible return temper-ature degrees from the end-user substations.Different than the traditional weather-compensation based supply temperature resetting,the new control strategy was formulated to adjust the supply temperature at the district level as to the cooling performance at the end-user substations.Two different simulations were carried out in order to quantify the benefits of the novel control strategy as compared to the traditional weather-compensation,equipped both at the substation level and the district level.The results obtained showed that the new control strategy,when considering the electricity loss at the heat production plant,shows superiority when compared to other control strategies.
基金The authors of this paper gratefully acknowledge the public fi-nancing of Business Finland for the“EcoSMR”project(Grant No.:9277/31/2019).
文摘Decarbonisation of district heating and cooling(DHC)system in Helsinki metropolitan area requires investments in new energy technologies and approaches to replace fossil fuel fired district heating(DH)production.Invest-ment paths involving(a)DH heat pumps(HPs)from low quality heat sources and(b)small modular nuclear reactors(SMR)are compared by utilising investment analysis based on optimisation model depicting the as-sumed 2030 situation.Several scenarios,with varying assumptions concerning existing DHC system,investment costs and electricity prices,are analysed in terms of new capacity and total annualised costs.The results indicate that the SMR option is more cost-efficient than the HP option with 4-8€/MWh difference in operation costs including annualised investments.Biomass fired boiler investments,enabled in both options,are preferred to HP investments in most scenarios.The cost-efficiency of HP investments is sensitive to investment cost,whereas SMR investments are relatively stable to investment cost variations.Varying electricity market prices affect cost-efficiency of large-scale HPs,and investments in SMR cogeneration units take place only with high electricity prices.
基金This research was supported by the National Natural Science Foundation of China(52008328)National Key Research and Development Project(2018YFD1100202)+1 种基金the Science and Technology Department of Shaanxi Province(2020SF-393,2018ZDCXL-SF-03-04)the State Key Laboratory of Green Building in Western China(LSZZ202009).
文摘Northwest China has abundant solar energy resources and a large demand for winter heating.Using solar energy for centralized heating is a clean and effective way to solve local heating problems.While present studies usually decoupled solar heating stations and the heating network in the optimization design of centralized solar heating systems,this study developed a joint multi-objective optimization model for the equipment capacity and the diameters of the heating network pipes of a centralized solar district heating system,using minimum total life cycle cost and CO_(2)emission of the system as the optimization objectives.Three typical cities in northwest China with different solar resource conditions(Lhasa,Xining,and Xi'an)were selected as cases for analysis.According to the results,the solar heating system designed using the method proposed in this study presents lower economic cost and higher environmental protection in comparison to separately optimizing the design of the solar heating station and the heating network.Furthermore,the solar fraction of the optimal systems are 90%,70%,and 31%for Lhasa,Xining,and Xi'an,and the minimum water supply temperatures are 55℃,50℃,and 65℃for an optimal economy and 55℃,45℃,and 45℃for optimal environmental protection,respectively.It was also established that the solar collector price has a greater impact on the equipment capacity of the solar heating station than the gas boiler price.
基金This work is supported by the National Program on Key Basic Research Project of China(973 Program)(Grant No.2014CB249201).
文摘When regulating a pipe network according to user demand,hydraulic balance and power consumption are crucial factors for a multi-source looped-pipe network applying distributed variable-speed pumps compared to the conventional central circulating pump system.In this paper,the influence of the fill point on power consumption and hydraulic balance of the multi-source looped-pipe network was studied.A mathematical model for electricity energy consumption analysis was built and calculated for a large sized looped-pipe network with multiple heat sources and distributed variable-speed pumps.The hydraulic calculation models of each single element,such as pipe,distribution pump,valve,replenishment pump,heat source and substation,were built.A case located in Dezhou city,China was analyzed.The results showed that:the maximum power saving(39.2%)could be achieved when each heat source had its own fill point,but the heat sources would not meet their design flows;to meet the design flows of all the heat sources,only one fill point should be necessarily located near the heat source with the lowest flow rate to get the expected hydraulic stability and energy saving.
文摘In the paper, the concept of the heating network coupling is introduced. Amathematical modal of heating network in water power is established. The coupling degree of theheating network is also calculated trough the liquid increasing matrix
文摘District heating networks (DHNs) provide an efficient heat distribution solution in urban areas, accomplished through interconnected and insulated pipes linking local heat sources to local consumers. This efficiency is further enhanced by the capacity of these networks to integrate renewable heat sources and thermal storage systems. However, integration of these systems adds complexity to the physical dynamics of the network, necessitating complex dynamic simulation models. These dynamic physical simulations are computationally expensive, limiting their adoption, particularly in large-scale networks. To address this challenge, we propose a methodology utilizing Artificial Neural Networks (ANNs) to reduce the computational time associated with the DHNs dynamic simulations. Our approach consists in replacing predefined clusters of substations within the DHNs with trained surrogate ANNs models, effectively transforming these clusters into single nodes. This creates a hybrid simulation framework combining the predictions of the ANNs models with the accurate physical simulations of remaining substation nodes and pipes. We evaluate different architectures of Artificial Neural Network on diverse clusters from four synthetic DHNs with realistic heating demands. Results demonstrate that ANNs effectively learn cluster dynamics irrespective of topology or heating demand levels. Through our experiments, we achieved a 27% reduction in simulation time by replacing 39% of consumer nodes while maintaining acceptable accuracy in preserving the generated heat powers by sources.
