District Heating Pipelines Research Articles

Energy and reserve procurement in integrated electricity and heating system: A high-dimensional covariance matrix approach based on stochastic differential equations

The integration of stochastic renewable energy sources into energy systems presents challenges due to flexibility insufficiency and uncertainty modeling inaccuracy. To address these challenges, this paper explores a high-dimensional covariance matrix approach based on stochastic differential equations (SDEs) for energy and reserve co-dispatch in integrated electricity and heating systems. By capturing the long-term correlation of wind power forecast errors, the SDE model simultaneously models point forecasts and high-dimensional positive-definite covariance matrices, resulting in a compact uncertainty set. To ensure computational efficiency, we employ duality theory to transform the stochastic co-dispatch problem with the high-dimensional uncertainty set into deterministic convex programming. Additionally, a virtual heat storage model is introduced for the district heating network, leveraging the thermal inertia of the network to enhance reserve capacity. Simulations validate the calibration and sharpness of the proposed high-dimensional uncertainty set. The results demonstrate that co-dispatch using the SDE-based uncertainty set reduces operational costs by 4.9% compared to a set that does not consider the long-term correlation of wind power, under a 95% coverage rate. Moreover, the storage capabilities of district heating pipelines and smart buildings provide cost-free reserves, saving the operational costs of the two test systems by 2.8% and 1.3%, respectively.

DETECTION OF DISTRICT HEATING PIPELINE USING UAVMOUNTED THERMAL CAMERA AND GPR SCANNING

<p>In this paper the benefits of integration of UAV-mounted (Unmanned Aerial Vehicle) thermal camera and GPR (Ground Penetrating Radar) are analysed. As an example we analized a district heating pipeline in a part of university campus in Novi Sad. Thermal camera mounted on UAV enables fast mapping of routes. These data are then used to detect critical zones where leaking or some other problem occurs and to validate utility cadastral data. Detailed inspection of zones is done using GPR scanning. This provides data such as geometry, precise location of damage, etc. In the last section of the paper advantages of non-invasive detection of district heat line combining active and passive sensors with UAV are explained.</p>

Thermal fatigue analysis of district heating pipeline under variable frequency regulation of circulating water pump

The use of variable frequency control of circulating water pumps is an important energy-saving operation strategy to cope with changes in heating load. However, it can lead to low cycle fatigue failure of the pipeline when the cyclic stress generated by frequent water temperature fluctuations reaches the fatigue limit. Accurately prediction of the maximum total temperature difference cycles of pipelines is of great significance for ensuring the safe operation of centralized heating networks with frequent water flow rates regulation. Based on the actual operating data of 360,000 heat exchange stations, the stress amplitude and corresponding temperature difference cycles of pipelines at different operating temperatures were calculated, the maximum total temperature difference cycle of pipelines for 30 years was predicted. We calculated the stress limit of pipelines at different safety levels, and evaluated the impact of temperature on the fatigue life of pipelines under different building types and working conditions. The results show that the number of temperature difference cycles in primary network pipelines is three times that in secondary network pipelines, and the number of temperature difference cycles in pipelines of different building types varies greatly. The lower the operating temperature of the pipeline, the smaller the temperature difference fluctuation and the greater the contribution of pipeline fatigue damage when regulating the variable flow rate of the circulating water pump. The stress limit values of primary network supply and return water pipelines are 650 MPa and 759 MPa, while the stress limit values of secondary network supply and return water pipelines are 811 MPa and 946 MPa.

Study of the Precise Determination of Pipeline Geometries Using UAV Scanning Compared to Terrestrial Scanning, Aerial Scanning and UAV Photogrammetry.

Transmission pipelines belong to technical infrastructure, the condition of which is subject to periodic monitoring. The research was to verify whether aerial measurement methods, especially UAV laser scanning, could determine the geometric shape of pipelines with a precision similar to that of terrestrial scanning, adopted as a reference method. The test object was a section of a district heating pipeline with two types of surfaces: matte and glossy. The pipeline was measured using four methods: terrestrial scanning, airborne scanning, UAV scanning and the structure from motion method. Then, based on the reference terrestrial scanning data, pipeline models were created, with which all methods were compared. The comparison made it possible to find that only the UAV scanning yielded results consistent with those of the terrestrial scanning for all the pipes. The differences usually did not exceed 10 mm, sometimes reaching 20 mm. The structure from motion method yielded unstable results. For the old, matte pipes, the results were similar to those of the UAV scan; however, for the new, shiny pipes, the differences were up to 60 mm.

Difference analysis and recognition of hydraulic oscillation by two types of sudden faults on long-distance district heating pipeline

The implementation of long-distance district heating (LDH) systems, which rely on renewable energy sources, waste heat recovery, and waste heat reuse, offers a scientifically supported and environmentally friendly approach to achieving low-carbon emission reduction goals. As the common sudden failure on the long-distance district heating pipeline (LDHP), the leakage and valve failure will lead to strong hydraulic oscillation, which may cause heating failure if they are not recognized and handled in time. In this paper, the difference in hydraulic oscillation induced by leakage and valve failure is investigated with the hydraulic transient model. Based on the above analysis, a recognition method combining the support vector machine (SVM) and particle swarm optimization (PSO) is proposed to identify these two types of sudden faults. Taking a 20 km LDH system as an example, the effectiveness and robustness of the recognition method are investigated. The results show that the types, locations, and status of these two types of sudden faults can be accurately recognized and the robustness of the recognition method is strong when the sample time is less than 10 s. Our research deepens the understanding of the characteristics of the hydraulic oscillation induced by the leakage and valve failure on the LDHP and gives a new idea for the intelligent recognition of sudden faults online.

Derivation of Corrosion Depth Formula According to Corrosion Factors in District Heating Water through Regression Analysis.

In order to predict the corrosion depth of a district heating pipeline, it is necessary to analyze various corrosion factors. In this study, the relationship between corrosion factors such as pH, dissolved oxygen, and operating time and corrosion depth was investigated using the Box-Behnken method within the response surface methodology. To accelerate the corrosion process, galvanostatic tests were conducted in synthetic district heating water. Subsequently, a multiple regression analysis was performed using the measured corrosion depth to derive a formula for predicting the corrosion depth as a function of the corrosion factors. As a result, the following regression formula was derived for predicting the corrosion depth: "corrosion depth (μm) = -133 + 17.1 pH + 0.00072 DO + 125.2 Time - 7.95 pH × Time + 0.002921 DO × Time".

A data-based reduced-order model for dynamic simulation and control of district-heating networks

This study concerns the development of a data-based compact model for the prediction of the fluid temperature evolution in district heating (DH) pipeline networks. This so-called “reduced-order model” (ROM) is obtained from reduction of the conservation law for energy for each pipe segment to a semi-analytical input–output relation between the pipe outlet temperature and the pipe inlet and ground temperatures that can be identified from training data. The ROM basically is valid for generic pipe configurations involving 3D unsteady heat transfer and 3D steady flow as long as heat-transfer mechanisms are linearly dependent on the temperature field. Moreover, the training data can be generated by physics-based computational “full-order” models (FOMs) yet also by (calibration) experiments or field measurements. Performance tests using computational training data for a single-pipe configuration demonstrate that the ROM (i) can be successfully identified and (ii) can accurately describe the response of the outlet temperature to arbitrary input profiles for inlet and ground temperatures. Application of the ROM to two case studies, i.e. fast simulation of a small DH network and design of a controller for user-defined temperature regulation of a DH system, demonstrate its predictive ability and efficiency also for realistic systems. Dedicated cost analyses further reveal that the ROM may significantly reduce the computational costs compared to FOMs by (up to) orders of magnitude for higher-dimensional pipe configurations. These findings advance the proposed ROM as a robust and efficient simulation tool for practical DH systems with a far greater predictive ability than existing compact models.

Thermo-hydraulic coupled analysis of long-distance district heating systems based on a fully-dynamic model

The long-distance district heating pipeline (LDHP) system is a key solution for transporting the renewable heat from the suburban to urban areas. In LDHP, thermal and hydraulic characteristics are coupled. Developing effective thermo-hydraulic co-simulation method is vital to enhance LDHP’s operation performance and to enhance its flexibility. As the pressure wave travels much faster than the hot water in the district heating (DH) pipeline, the research in this regard mainly focuses on pseudo-dynamic model, in which the calculation of thermal dynamics only adopts the static hydraulic conditions. In this paper, a novel fully-dynamic model considering both the hydraulic transients and thermal dynamics is developed. The model is solved using the method of characteristic (MOC). The optimal spatial and temporal step sizes for the thermal dynamic modeling are analyzed and studied. Next, we compared our proposed model with the conventional pseudo-dynamic model on a 20 km LDHP. Results show that the simulated temperature fluctuations of the two models are close to each other, but the predicted temperature arriving at the heat exchange station is up to 28 s earlier than the pseudo-dynamic model, indicating that hydraulic transients have some influence thermal dynamics. Moreover, the fully-dynamic model has capability to predict the temperature and flow rate transport of the system in both disturbance state and steady state, which is important for the rapid and accurate analysis of the operation of LDHP.

Thermo-Economic Assessment on Insulation Conditions of the Buried Heating Pipeline for District Heating

Insulation performance and buried depth of heating pipelines are the vital factors affecting the energy loss of directly buried heating pipelines. This study considers the thermo-economic assessment of insulation of directly buried heating pipelines for district heating. The optimal insulation thickness, energy-saving effect, and payback period of district heating pipelines with five nominal pipe diameters, four fuel types, four kinds of insulation materials, and four buried depths are calculated. A numerical code is developed based on Life Cycle Cost Analysis and is validated via comparing with results in the open literature. Three representative cities of Xi’an, Shenyang, and Harbin subjected to three different climatic zones in China are explored. The highest values of optimum insulation thickness are 176, 153, and 121 mm in Harbin, Shenyang, and Xi’an, respectively, which are reached using oil as fuel, rock wool as insulation material, nominal pipe diameter 500 mm, and buried depth 1 m. A sensitivity analysis is performed to indicate how much the optimum insulation thickness and payback period are sensitive to the changes of insulation, fuel, and buried depth. The results show that insulation and fuel have a greater influence on the optimum insulation and payback period than the buried depth.

Valve failure detection of the long-distance district heating pipeline by hydraulic oscillation recognition: A numerical approach

The long-distance district heating pipeline (LDHP) system can deliver waste heat from suburban areas to urban areas. Valve-induced hydraulic oscillation caused by valve failure will lead to large fluctuations of pressure, which may also result in pipeline rupture of the LDHP system. Fast and accurate detection of the faulty valve is a necessary measure for efficient repair and adjustment of the LDHP system. In this paper, the hydraulic transient model of the LDHP system based on the distributed parameter method is combined with the Particle Swarm Optimization algorithm to realize fast and accurate detection of the location and status of faulty valve, by recognizing the faulty valve-induced hydraulic oscillation in the LDHP. The effectiveness of the detection algorithm is verified by numerical simulation of a 20 km LDHP system, and the effects of instrumental error and sampling period on the robustness of the algorithm are investigated. Results show that when the sampling period is less than 10 s, the relative errors of the detected location and opening of the faulty valve are less than 8% and 0.1%, respectively. Therefore, the faulty valve-induced hydraulic oscillation in the LDHP can be effectively detected based on the method proposed in this paper.

Unlocking the Flexibility of District Heating Pipeline Energy Storage with Reinforcement Learning

The integration of pipeline energy storage in the control of a district heating system can lead to profit gain, for example by adjusting the electricity production of a combined heat and power (CHP) unit to the fluctuating electricity price. The uncertainty from the environment, the computational complexity of an accurate model, and the scarcity of placed sensors in a district heating system make the operational use of pipeline energy storage challenging. A vast majority of previous works determined a control strategy by a decomposition of a mixed-integer nonlinear model and significant simplifications. To mitigate consequential stability, feasibility, and computational complexity challenges, we model CHP economic dispatch as a Markov decision process. We use a reinforcement learning (RL) algorithm to estimate the system’s dynamics through interactions with the simulation environment. The RL approach is compared with a detailed nonlinear mathematical optimizer on day-ahead and real-time electricity markets and two district heating grid models. The proposed method achieves moderate profit impacted by environment stochasticity. The advantages of the RL approach are reflected in three aspects: stability, feasibility, and time scale flexibility. From this, it can be concluded that RL is a promising alternative for real-time control of complex, nonlinear industrial systems.

A Data-driven Model of Pipe Diameter and Insulation Thickness Optimization for District Heating Systems

One of the major downsides of district heating systems is the large thermal loss through the distribution pipe network, which is expected to be alleviated through the optimization for the thickness of the insulation layer and the pipe diameter. Although a few previous studies have developed a diversity of techno-economic models for optimizing the pipe diameter or the insulation thickness of the district heating pipeline, few of them were able to capture the complicated relationship among the heat loss, pipe diameter, insulation thickness, operation parameters, and complex exterior conditions in the real world (such as the conditions of the soil and degradation condition of the insulation layer). The present study devises a combined model that first bases on the heat transfer model to theoretically estimate heat losses and then bases on the data-driven artificial-neural-network model to fill in the gap between the measured and theoretical heat losses. Results show that the predicted heat losses via the developed combined model reproduce the measured data well. Furthermore, compared with the original pipe diameter and insulation layer thickness, the optimized diameters of the pipe and thickness values of the insulation layers via the proposed combined model are all elevated.

Leak detection of long-distance district heating pipeline: A hydraulic transient model-based approach

Long-distance district heating pipelines (LDHPs) are important infrastructures in large scale district heating (DH) system. Their safety and stability are crucial for stable and efficient operation of the whole DH system. Pipeline leakage is a common accident in the operation of DH system, accurate and fast leak detection technique is an indispensable measure for ensuring efficient repair and avoiding large-area heating failure. In this paper, a fast and accurate leak detection technique for LDHPs is proposed. The technique utilizes the numerical hydraulic transient model of the LDHP and the particle swarm optimization (PSO) algorithm to find the leak point. A pressure wave velocity identification procedure is also established for the leak detection. Simulation tests are conducted on a 20 km LDHP to investigate the influences of instrumental error and sampling frequency of measured data on the accuracy of the leak detection. Results show that when the sampling frequency is higher than 0.1 Hz, the relative errors of the detected leak point areas and leak point positions can be less than 2.73 % and 2.40 %, respectively. Effective leak detection of LDHPs can be therefore conducted through the proposed leak detection technique and measuring instruments with high precision and proper sampling frequency.

Air-source heat pump heating based water vapor compression for localized steam sterilization applications during the COVID-19 pandemic

Sterilization is of great importance to prevent the spread and resurgence of the COVID-19, yet sterilization methods are all energy intensive in general. Steam sterilization is easily maintained and can be applied in various scenarios with less residual pollution. However, the current steam generator (so called boiler) has brought many energy and environmental concerns. With the investigation on steam sterilization's features, this study proposed a clean and flexible steam generation system with the air source heat pump and water vapor compressor, and the system can be further simplified through the combination with district heating pipeline. The critical design parameters and simulated performance of the system are evaluated and optimized through a MATLAB simulation, and a prototype was built with experimental performance assessing. The results show the system has an average boiler efficiency of over 170% when the ambient temperature varies from 5 °C to 35 °C and the temperature of outlet steam is above 110 °C, and has the best economic performance when the operating period is above 3 years. Furthermore, the air-source heat pump boiler system is proved to effectively respond to the surging sterilization demands during the peaks of the COVID-19 pandemic and is well consistent with the UN Sustainable Development Goals.

Techno-economic analysis and multiobjective optimization of a novel proposal for addressing summer-supply challenges of district heating systems

A critical challenge of some district heating systems is too low summer demand, which results in a too low temperature at the consumption points. To prevent this large temperature drop along the path, the heat production plants have to oversupply hot water to the pipeline, which is itself problematic techno-economically. One more challenge of summer supply, if supplied by waste incineration plants, is that due to the low heating demand during the summer, there will be too much useless excess municipal solid waste at the disposal, causing further technical and economic issues. In the proposed concept of this study, an integrated district heating/cooling system is proposed to address both of these problems. For this, a solar-assisted chiller is utilized to not only take advantage of the excess waste of the power plant but also the excess hot water injected into the pipeline for cold supply. The research question is about the optimal sizing of the system. The sizing of the components of the system is carried out via a rigorous multiobjective genetic algorithm work package covering technical, economic, and environmental objectives, and then, the optimal design is techno-economic-environmentally analyzed. In summer, the velocity of hot water reaches the appropriate value of 0.8 m/s, and following the cold load supply, 67.8 kg/s extra mass flow rate of hot water with a temperature over 80 ℃ could feed the district heating system. Besides, at least 78 tonnes more waste will be burnt per day. It means challenges of the high amount of waste disposal, low velocity of hot water in district heating pipeline, and the high amount of waste heat will be solved, and the levelized cost of cooling production would decrease by 10%.

Durability of District Heating Pipelines Exposed to Thermal Aging and Cyclic Operational Loads

AbstractFourth generation district heating networks (4GDH) must be designed for future energy systems, integrating renewable volatile energy sources, with lower operation temperatures, and conseque...

Evaluation of internal corrosion property in district heating pipeline using fracture mechanics and electrochemical acceleration kinetics

The corrosion of district heating (DH) pipelines in the internal environment is carefully controlled, however the long-terms of corrosion induced fracture is still uncertain. The general corrosion of pipeline in the heating water is very moderate, therefore it is almost not affected to initiate fracture. While, localized corrosion in weld zone is very dangerous situation because it can act as a stress concentration point. Therefore, it is significant to analyze using the fracture mechanics whether a fracture actually occurs due to the localized corrosion or not.In this study, the long-term corrosion was simulated using the electrochemical acceleration method. The surface morphology parameter of the accelerated specimen was analyzed using a 3D profiler. The crack tip opening displacement (CTOD) was calculated using the corrosion morphology parameters. Consequently, in internal DH environment, general corrosion is the dominant factor in fracture rather than localized corrosion. In other words, internal corrosion cannot be a main reason of the DH pipeline fracture.

Methodology for calculating the ineffective diameter of thermal insulation

This article describes the results of energy efficiency analysis of various types of pipeline thermal insulation in a district heating system and equipment. The mathematical relations used in calculating the thickness of the thermal insulation for heat pipes and equipment are given. The concept of the critical value of the thermal insulation outside diameter of the heat pipe is described. An equation is presented that determines the ineffective thickness of the heat pipe insulation. A solution to this equation is proposed using numerical methods, namely, Newton’s method. The results of calculations of ineffective thermal insulation diameters for various parameters of the coolant, the diameters of the pipeline itself, and various heat-insulating materials are presented. The obtained data are analyzed. Recommendations are given for the correct selection and calculation of the thermal insulation thickness of district heating pipelines, as well as for the reconstruction of the existing ones.

Coordination of Electricity, Heat, and Natural Gas Systems Accounting for Network Flexibility

Existing energy networks can foster the integration of uncertain and variable renewable energy sources by providing additional operational flexibility. In this direction, we propose a combined power, heat, and natural gas dispatch model to reveal the maximum potential “network flexibility”, corresponding to the ability of natural gas and district heating pipelines to store energy. To account for both energy transport and linepack in the pipelines in a computational efficient manner, we explore convex quadratic relaxations of the nonconvex flow dynamics of gas and heat. The resulting model is a mixed-integer second-order cone program. An ex-post analysis ensures feasibility of the heat dispatch, while keeping the relaxation of the gas flow model sufficiently tight. The revealed flexibility is quantified in terms of system cost compared to a dispatch model neglecting the ability of natural gas and district heating networks to store energy.

Optimization of Cathodic Protection System for River-Crossing District Heating Pipeline using Computational Analysis: Part II. The effective location of anodes

Optimization of Cathodic Protection System for River-Crossing District Heating Pipeline using Computational Analysis: Part II. The effective location of anodes