Operation Of Heating System Research Articles

Methodological issues for the formation of reliable and efficient district-distributed heating systems

The general methodological issues for the formation and operation of district-distributed heating systems are formulated, including determining the areas of economic efficiency of district and distributed (prosumer sectors) heat supply to consumers, reliability analysis and synthesis, as well as economic analysis of failed conditions of the system (determination of damage from undersupply of thermal energy). Methodological provisions for solving these problems are proposed, structured in the form of a general algorithm with connection of problems, methods and results.

НЕЧІТКА ЕКСПЕРТНА СИСТЕМА ДЛЯ КЕРУВАННЯ ТЕМПЕРАТУРОЮ ПОВІТРЯ У ПРИМІЩЕННЯХ ТОРГОВЕЛЬНО-РОЗВАЖАЛЬНОГО ЦЕНТРУ

Abstract The article presents the stages of developing a fuzzy expert system for the operator of a heating point of a shopping and entertainment center. The principle of operation of the air heating system of the mall is shown, implemented using computer-integrated control with a SCADA system. For the effective operation of the air temperature control system in different areas of the mall, functions for belonging to comfort zones have been developed in terms of visitors and the requirements of sanitary standards. It is indicated that typical air temperature stabilization controllers cannot always provide the desired mode due to the influence of a large number of uncontrolled disturbances on the control system. In this case, in the absence of additional blocks for adapting control algorithms, it becomes expedient to remotely control the operator using a mnemonic diagram of the ventilation process. And to improve the efficiency of the process of remote control of thermal equipment, an expert system was proposed that implements the algorithm of I. Mamdani, to control the coolant flow valves. The controller receives information from the outdoor air and air temperature sensors in the control area of the mall. After processing the signals from the sensors, the controller transmits information to a computer with an expert system. Depending on the temperature and season of the year, the program calculates the optimal position of the valve (in percentage of stroke) for the flow rate of the coolant and recommends installing it to the operator. Also, it is shown that in the process of developing a fuzzy expert system, it is recommended to choose the Gaussian type of membership functions; minimal number of terms - sets - three functions of dependency; weight coefficient of each rule in the knowledge base is the same and equal to 100; the method of defasification is the method of the center of gravity. It is indicated that the introduction of expert advice to operators can also lead to a reduction in the response time to emergency situations up to 90% increase in the reliability of the equipment as a whole.

PRIVATE HOUSEHOLD HEAT PUMP-BASED HEATING SYSTEM WITH PHOTOVOLTAIC PLANT

Heat supply is the most energy-consuming industry in Ukraine. The reason for this is a large number of buildings built with a low level of thermal insulation, outdated thermal energy equipment and infrastructure, as well as a low level of implementation of heating systems based on renewable energy sources. Heat pumps are one of the alternatives to fossil fuel boilers for use in household heating systems. The problem of optimizing the operation of heating systems based on heat pumps is of practical importance, since its solution will potentially allow achieving several energy effects, including: reducing operating costs, as well as increasing the level of autonomy of the heating system in the case of providing electricity from an autonomous photovoltaic plant. The article presents the results of mathematical modeling of the heating system of a private house based on a heat pump, a thermal energy accumulator and a photovoltaic plant in the MATLAB/SIMULINK software environment. The model was created for the research purpose of the heating system of a private house with renewable energy sources through structural simulation modeling and conducting a comparative analysis of its management methods for three options (methods): "reactive", "economic" and "autonomous". It was found that the average annual operating costs with the "economic" method of management decreased by 22 % compared to the "reactive" method of management. When using the "autonomous" method of control, the annual maintenance cost of the system due to photogeneration increased by 48 %.

Метод уточнения нагрузок в системах теплоснабжения на основе анализа данных учета потребления тепловой энергии

Currently, to set up heating networks, the programs to calculate the operating modes of networks are widely used. It requires a large number of characteristics of network objects and consumer loads, in particular. At the same time, in the real world, since it is difficult to determine design loads, they are often considered with large errors, and models are unsuitable for setting operating modes. Thus, an urgent task is to clarify the loads of consumers based on an audit of the existing network operation mode. The paper uses methods to calculate the load characteristics of buildings, methods to collect and monitor data of heat energy supply metering units and data to monitor the operating modes of the heat supply system of IGEU boiler house. A method to audit and clarify loads according to monitoring data of the heating system operation modes is proposed, which allows to improve the quality of network configuration. The obtained results have confirmed the possibility to clarify the loads of consumers under the conditions of an unregulated network based on the analysis of the readings of metering devices installed at consumers. The developed method can be used to solve the problems of setting up heating networks of district boiler houses.

Prediction of the dependence of the indoor air temperature on the change in the working characteristics of the water heating system

This article was devoted to the theoretical determination of the predicted indoor air temperature based on the basic equations of hydraulics and heat exchange with variable operating characteristics of the water heating system network. Derive a relationship that will predict the indoor air temperature setting of the room that is being heated as a result of changes in the operating characteristics of the water heating systems. In basis the solution to the problem of determining the temperature in the room by changing the performance characteristics of the water heating system is based on the basic equations of hydraulics and heat transfer such as Darcy-Weisbach equation to determine the hydraulic losses in the network; flow continuity equation; equation to determine the heat flux from the coolant to the walls of the heater; equation for determining the heat transfer of the heater. The resulting dependence makes it possible to predict the setting of the indoor air temperature in the room heated as a result of changes in the operating characteristics of the water heating systems. This dependence will allow at the design stage and in the process of operation of water heating systems to predict changes in the indoor air temperature in order to take measures to stabilize it. The predicted indoor air temperature is theoretically determined based on basic equations of hydraulics and heat exchange with variable operational characteristics of the water heating system network. The obtained results of indoor air temperature prediction calculations show that the parameters of the indoor microclimate change due to changes in the operational characteristics of water heating systems (changes in coolant consumption, hydraulic characteristics of pipelines). This approach will allow you to make decisions to improve the reliability of water heating systems in the process of ensuring the parameters of the microclimate in the room.

Experimental research of electrical characteristics combined solar-electric air heater

Poor water quality in district heating systems leads to failure of boilers and pipelines in heating networks. The main reason for this is corrosion and scale deposits. The presence of these factors shows the low efficiency of water treatment systems. The article presents the results of the introduction of non-traditional water treatment technologies for district heating systems based on the experience of the Zhytomyrteplokommunenergo utility company of the Zhytomyr City Council in 2007-2021. In the boiler houses of the enterprise, water treatment systems were modernized, and the production chemical service was reorganized. In particular, chemical deaeration was launched in combination with traditional sodium cationization, as well as chemical deaeration in combination with complexonate water treatment against the classical water treatment technology - ion exchange. Installed magnetic sludge separators with magnetic inserts. The technology of water softening with anti-corrosion protection using Redox filters has been introduced. Gravimetric corrosion sensors of our own design have been developed and installed. The database of processing and statistical analysis Access "Corrosion damage of pipelines of heat networks" was created and put into operation. The experience of modernizing the water treatment system has shown that work in this direction increases the reliability of operation of district heating systems by reducing the consumption of energy carriers and material resources. In addition, the problem of improving the operational reliability of the heat exchange equipment of thermal stations needs to be solved. The projected start of the use of heat recovery devices on water heating boilers in operation, in condensation or partially condensation modes, will also bring with it a number of problems with the neutralization of condensate and its return to the heat supply system. The end result is an increase in production reliability, environmental friendliness and a reduction in the cost of heat for district heating systems.

Specifying boundary conditions for the operation of pipe heating systems with impact on the building energy balance

Unaddressed boundary conditions in the design of heating systems affect the energy balance of buildings, especially in buildings with very low energy consumption. Buildings with very low energy consumption are very sensitive to any heat flow and neglecting realistic heating water parameters affects their energy balance. Two simulation models of the end part of the heating system have been developed. The first simulation model shows the effect of the inaccuracy of the designed heating element on the calculated room temperature. The second model shows the hydraulic behaviour of the connection pipes of the designed heating element.

Portfolio optimization in district heating: Merit order or mixed integer linear programming?

Long-term portfolio optimization is commonly used to find the most cost-effective design and operation of a district heating system, subject to technical, financial, and environmental restrictions. Optimizing a district heating system is not trivial and demands high accuracy and high computational speed. However, existing methods addressing this problem offer one or the other but not both at the same time. The state-of-the-art method for portfolio optimization is mixed integer linear programming (MILP), which is extensively used in industry and academia but can be computing and resource-intensive for large portfolio models. This limitation has motivated the development of various options to reduce the computation time while maintaining the accuracy to a large extent. An alternative method to MILP is the merit order (MO) method, which has been used especially for power generation applications due to its simplicity and faster computation but somewhat reduced accuracy. The aim of this paper is to investigate the potential advantages and disadvantages of MO models compared to MILP models in the context of optimizing the portfolio of assets supplying a district heating network. As a study case, we analyze a large portion of the district heating network in Berlin. Four MO model variants with different levels of complexity are proposed and compared to a reference MILP model. Results suggest that MO models variants including heat storage and describing CHP plants with significant detail have the potential to reduce calculation time by nearly three orders of magnitude compared to the reference MILP model, without significantly sacrificing accuracy. In fact, differences in heat generation and net present value (NPV) between the most accurate MO model and the reference MILP model account for ±4% and −6%, respectively. Moreover, results show that combining MO and MILP models is advantageous and offers high computational speed and at the same time high accuracy, especially when a large number of runs might be necessary. MO models could thus be used prior to MILP models to perform a pre-evaluation, an exploration of sensitivities, or for downsizing the initial optimization problem. Combining MO and MILP models could result in faster and more robust decision-making, which could otherwise not be attained with any of the two options individually.

Demand side digitalisation: A methodology using heat cost allocators and energy meters to secure low-temperature operations in existing buildings connected to district heating networks

With regard to the green transition toward 4th generation district heating (4GDH), a critical element is ensuring low operating temperatures in networks. This can help leverage the technical and economic potential of connecting renewable energy sources and recovering excess local heat. Poorly controlled and operated heating systems in existing building stocks limit the possibility of lowering the operating temperatures of district heating networks. Hence, digitalising the demand side can afford new opportunities for building services by monitoring heating systems and improving operations to secure the expected comfort in existing buildings with lower temperatures. Accordingly, this study investigated the innovative use and integration of data from heat cost allocators, district heating energy meters, and temperature sensors to improve space heating system operations. Based on the measurements, the methodology focused on identifying the critical flat in the building with the highest heat demand and calculating the minimum possible operating temperature. Five Danish multi-family buildings were considered as case studies in the investigations, highlighting good agreement between the new weather-compensated control curve and the measurements. Almost 75% of the total space heating consumption was distributed under outdoor temperatures exceeding 0 °C in 2021, whereas only 0.5% was associated with the lowest outdoor temperature of −9 °C. This clearly suggests that design conditions rarely occur during the typical operation of systems and that the radiators are oversized and suitable for operation at low temperatures for most of the heating season. Notably, it was documented that supply temperatures of 48–53 °C were sufficient to secure the expected comfort at an outdoor temperature of 0 °C, without any extensive energy renovation in the buildings.

Research on the influencing factors of clean heating compound transformation under the carbon neutrality goal

The clean heating compound transformation under the Carbon Neutrality Goal is necessary for the high-quality development of the heating industry in China. Based on the literature analysis, questionnaires and semi-structured interviews, this paper identifies 15 driving factors affecting the transition at three levels: technology, organization and environment. This paper introduces Fuzzy Set Theory into Decision-Making Trial and Evaluation Laboratory method, and combined with explanatory structural models to form a combined Fuzzy-DEMATEL-ISM approach. Using the Fuzzy-DEMATEL-ISM method to analyze the degree of influence, hierarchical relationships and logical associations among the influencing factors to reveal the influence mechanism of the compound transition of clean heating. The results show that 1) the key influencing factors for the transition are energy use and delivery methods, heating system operation and maintenance management, and clean heating costs and expenses. 2) There are eight causal factors and seven consequential factors in the clean heating compound transition influence factor system. 3) The recursive structure model of influencing factors is divided into five levels from bottom to top: root level, deep level, middle level, shallow level and surface level, among which environmental and clean heating policies, clean heating technology innovation level and resource endowment status are the basic guarantees of transformation. It provides a theoretical supplement and practical guidance for the compound transition to clean heating under the carbon neutrality goal.

Day-ahead heat load forecasting during the off-season in the district heating system using Generalized Additive model

The paper presents the results of heat demand forecasting during the off-season (summertime and transitional period) in a real district heating system. The hourly heat demand in the analyzed system ranges from 16 to 28 MW, depending on the month and hour of the day. Short-term prediction of the heat demand in the day-ahead horizon is needed for effective operation of production units in the Cogeneration Heat and Power Plant (CHP). The method of an hourly heat load predictions using a data-driven model is presented. The algorithm is based on the Generalized Additive Model with hour of the day, day of the week and day of the year as predictors. A way of increasing the accuracy of forecasts using the autoregressive model for residuals of the model was discussed. The influence of the training dataset size on the model error was also examined. The several versions of the model were evaluated by comparing forecasted results with real values during the district heating system's operation from June to the end of August. For the most accurate one, Root Mean Square and Mean Average Percentage Error were 0.84 MW and 3.3 %, respectively.

Dynamic integrated control for Chinese district heating system to balance the heat supply and heat demand

District heating system (DHS) mainly consumes fossil fuel in North China. Reducing energy consumption of DHS is conducive to low-carbon sustainable development. Poor matching of heat supply and heat demand limits the efficient operation of the district heating system. To solve this issue, a dynamic integrated control method of buildings and heat exchange station (HES) is proposed. On the building side, five heating patterns are designed for space heating of buildings based on their indoor demand temperatures. On the HES side, to produce the accurate heat supply, four correction factors are introduced to modify the temperature-flow equations based on the DHS configuration difference between actual operation and design conditions. Five total correction factors are integrated to determine eventual regulation equations. Then single-level and double-level reverse control strategies are presented. A case study is illustrated to validate the proposed approach. With the integrated control, the matching values of calculated heat supply and actual heat consumption were 85.46%∼96.90% of buildings and over 90% of the whole DHS. Four years of operation data indicated the 12.75%∼31.08% of heat-saving rate and 5.23%∼24.62% of electricity saving rate, which brings about total emission reductions of 3803 tons CO2, 35 tons SO2 and 10 tons NOx.

A Model Predictive Control for Heat Supply at Building Thermal Inlet Based on Data-Driven Model

At present, the traditional control strategy of heating systems is still unable to achieve building heating on demand, which enhances the energy consumption of heating and affects the thermal comfort of buildings. Therefore, this study puts forward a novel data-driven MPC for building thermal inlet, which allows the optimal operation of the district heating system and has been verified by simulation with three public buildings. In this method, the indoor temperature at the next moment reaches the temperature set value by changing the current flow rate. First, based on the energy consumption monitoring platform and the measured data of the buildings, the building indoor temperature prediction model at the next moment is established by using long short-term memory (LSTM). Compared with subspace model identification (SMI), LSTM has higher prediction accuracy, and the R2 was about 0.9 in three buildings. Second, the particle generated by particle swarm optimization, which represents the flow variation, is input to the trained LSTM to predict the indoor temperature. By minimizing the objective function, the optimal flow change at the current time can be calculated. The results showed that the MPC based on a data-driven model can adjust the flow rate in time to maintain a stable indoor temperature with ±0.5 °C error. In addition, when the temperature setting needs to be changed, the indoor temperature can reach the new set value in 3 h, which outperforms the PID control. The method proposed in this paper can greatly reduce the influence of regulation lag by adjusting the flow in advance.

A market study of early adopters of fault detection and diagnosis tools for rooftop HVAC systems

Retrofit fault detection and diagnosis (FDD) products are undergoing major advances in their ability to optimize the operation and maintenance of building heating, ventilation, and air conditioning (HVAC) systems as a result of advances in artificial intelligence, cloud computing, and low-cost sensor networks. However, many market barriers still exist to their widespread adoption. This paper is the first to study the market and barriers for FDD products from the perspective of early adopters of HVAC rooftop retrofit FDD products as part of a field study of early adopters. Researchers engaged multiple sites and installed different FDD products at these sites for the purposes of (1) evaluating market readiness, market barriers, and user experience, (2) evaluating energy and demand savings, (3) evaluating the purchase, installation, training, and use process, and (4) determining overall FDD product effectiveness. This paper presents and focuses on the market study goals, methods, results, and findings determined based on survey data collected from key stakeholders participating in the study. These stakeholders included FDD providers, energy efficiency program managers and engineers, HVAC contractors, building owners, facility managers, energy managers, and consultants. The study provides results and analyses concerning (1) current knowledge and awareness levels for FDD technologies, (2) attitudes towards FDD products, (3) market barriers and resources available for FDD, and (4) insights on how stakeholders perceive and determine the value and cost for purchasing, using, and adopting FDD technologies and products. The study produced twelve (12) key findings, which provide valuable input for energy efficiency programs in their development of more effective FDD marketing programs that can increase adoption of FDD technologies and reduce barriers to widespread adoption.

Comparative Analysis of Resource and Climate Footprints for Different Heating Systems in Building Information Modeling

Buildings play an important role to meet Sustainable Development Goals, especially regarding the use of resources and greenhouse gas emissions. They are increasingly designed with energy-efficient solutions regarding their operations, while the related use of natural resources is still insufficiently considered. In this article, a methodology in Building Information Modeling is proposed to measure the resource and climate footprints of buildings’ heating systems. The methodology is applied to a case study building in Germany. The studied heating systems include a gas condensing boiler, ground-source heat pump, ground-source heat pump with a photo-voltaic system and air-source heat pump backed up with a gas boiler. Next to the operational energy, the production and transport of the heating systems were also studied. Results show that heating system operations have the largest impact and that the variant of ground-source heat pump combined with photovoltaics (GSHP + PV) has the lowest impact. In comparison with the gas boiler (GB), savings of 75%, 47%, 80%, and 84% are addressed to climate, material, energy, and land footprints, respectively, while the water footprint of GSHP + PV is 73% higher than that of GB.

A new business model for coordinated operation of wind power plant and flexible district heating system

This paper explores a new business model for the coordinated operation of wind power plant (WPP) and flexible district heating, which utilizes wind curtailment to supply the heat demand of a local heating system (LHS). By the proposed business model, the wind production that would have otherwise been curtailed can be further utilized to improve energy efficiency and generate extra revenue for the WPP. Besides, the LHS can save the heat supply cost by using the low-price curtailed wind power. To achieve the proposed business model, a coordinated operation strategy of the WPP and LHS is proposed. Based on that, the mathematical formulation for the optimal operation of the WPP and LHS is built by considering their respective constraints. The proposed business model is tested on a WPP and a 6-node LHS, and the simulation results show that the proposed business model can reduce 31.58% of the curtailed wind on the test day and the LHS can save the heating cost by 54.5%.

Heat flexibility evaluation and multi-objective optimized control of a low-energy building with district heating

Along with the increasing application of the renewable energy in the energy systems, the future energy system will be more stochastic and fluctuated. Therefore, it is of great importance to effectively coordinate the energy supply and demand side considering their different dynamic characteristics. This study analyzes the impact of the integrated energy flexibility from the building mass and the storage tank on the heating system operation for a low-energy building connected to district heating (DH). According to the actual room occupancy and dynamic heat price, the strategy to unlock the energy flexibility is developed and optimized. The detailed thermal performance of the system is simulated by Modelica models. Compared to the reference case, the integrated energy flexibility is helpful to make better use of the low-price heat. Moreover, a variety of quantification indices were developed to evaluate the flexibility and rebound effect. The results show that the fully charged thermal mass of the low-energy building can help maintain the comfort indoor temperature for up to 43 h. Combined with the storage tank, the heat flexibility potential of the case building reaches 78 kWh and saves 1.1 DKK of the daily heat cost with the optimized heating strategy compared to the reference scenario. Moreover, the flexibility factor is improved by shifting the peak heat load to the low-price period.

A stochastic methodology to exploit maximum flexibility of swimming pool heating systems

Swimming pool heating systems are known as one of the best flexible resources in buildings. However, they can be flexible only for a certain number of hours throughout a day due to the comfort constraints of the users. In this study, a new approach is proposed to determine a group of contract hour sets to procure maximum flexibility of swimming pool heating systems supplied by heat pumps for trading in the regulation market while respecting the comfort of users. The main advantage of the contract hour sets is the certainty in response to flexibility requests. The proposed approach consists of three main steps. First, a stochastic mixed-integer linear program is proposed to find the optimal operation of a swimming pool heating system that has agreed to provide flexibility in a contract hours set. Then, a metric is proposed to evaluate the effectiveness of contract hour sets using the results obtained in the first step. Finally, an algorithm is proposed to identify a group of the most efficient contract hour sets using the calculated metric. The proposed approach is validated through comprehensive simulation studies for a summerhouse with an indoor pool heated by a heat pump. Also, a cost–benefit analysis is performed to examine the feasibility of these contract hour sets from financial viewpoint. Simulation results show that the maximum contract hours can vary from 2 to 12 h depending on the building occupation pattern and the minimum payment to owners is between 0.03 to 0.06 (Euro/kW).

Grey-box modelling and virtual sensors enabling continuous commissioning of hydronic floor heating

Operating district heating systems with low supply and return temperatures improves heat production and distribution efficiency, permitting greater integration of renewable heat sources. Low-temperature district heating is viable without compromising comfort, but faults in end-users’ heating systems constrain temperature reductions. Such faults include malfunctioning valves, improper hydronic balancing, and excessive supply temperature setpoints. Occupants lack the resources to detect and diagnose these faults, so there is a need for automated solutions without requiring additional hardware. This paper proposes a method for improving the operation of an apartment's hydronic floor heating system using data from room thermostats, a heat meter and a circulation pump to identify a grey-box model of the system. The resulting model virtually senses each room loop's heat flux, flow, return temperature, and flow coefficient. The authors tested the model on a low-energy apartment in Denmark, using it to diagnose causes of high return temperatures, including poor hydronic balancing and an excessive supply temperature setpoint and pump setting. The authors also used the model to predict the minimum permissible supply temperature maintaining comfort, yielding a reduction in the energy-weighted supply and return temperatures of 8.6 °C and 6.5 °C, respectively.

Synergistic development of heating system decarbonization transition and large-scale renewable energy penetration: A case study of Beijing

In response to climate change, China has set the target to achieve carbon neutrality by 2060. The large-scale development of renewable energy and the decarbonization transition of the heating system are crucial for achieving this target. Is there a synergistic effect between the heating system's decarbonization transition and the use of large-scale renewable energy sources? What effect does this synergistic development have on the CO₂ emissions and the economic costs of an energy system? This paper conducts a case study of Beijing, China, and designs three technical path scenarios for heating system decarbonization transition in the future, namely, business as usual scenario where existing policies and regulations are applied, the electricity substitution scenario where the traditional fossil fuel heating system is replaced by electric heat pump, and the synergistic development scenario where the existing thermal power units are retrofitted to replace the consumption of fossil fuels with renewable energy sources. Using the EnergyPLAN model, the hourly operation of Beijing's power and heating systems under the three scenarios are simulated. The research results are: Firstly, the proportion of local renewable energy will be over 70% in all three scenarios, and in the synergistic development scenario, the electricity and heating demand can be met by 100% renewable energy, reducing CO₂ emissions resulted from fossil fuel combustion; secondly, in view of the real-time match of power supply and demand in the power system, at times renewable energy supply would exceed demand. The rational use of the surplus renewable energy can promote further the synergistic development of decarbonization transition of heating system and renewable energy, reducing the primary energy consumption and CO₂ emissions by over 16% and 28% respectively in the future heating system; Thirdly to improve the economic benefit of a synergistic electric power and heating system, focus should be on the reduction of infrastructure construction cost rather than the reduction of fuel consumption. The proposed method can be extended to regional energy systems with more energy sectors, and can be used to formulate decarbonization transition schemes for industry, agriculture, etc.