Operation Of Heating System Research Articles

Assessment of Thermal Comfort in the Intelligent Buildings in View of Providing High Quality Indoor Environment

The paper analyses the indoor environment in two modern intelligent buildings located in Poland. Measurements of air and globe temperatures, relative humidity and carbon dioxide concentration in 117 rooms carried out in the space of 1.5 years were presented. Thermal comfort of the occupants has been investigated using a questionnaire survey. Based on 1369 questionnaires, thermal sensation, acceptability and preference votes were analysed in view of their interdependency as well as their dependency on operative temperature, which proved to be very strong. It has been found that the respondents did not completely rate thermal comfort and indoor environment quality as very high, although the overwhelming sensations were positive. Apart from the operation of heating, ventilation and air conditioning (HVAC) systems, this might have also been the cause of individual human factors, such as body mass index, as tested in the study, or the finding that people were generally in favour of a warmer environment. Moreover, thermal environment proved to be the most important element for ensuring the well-being of the occupants.

Investigation of optimized network splitting of large-scale urban centralized heating system operation

Operation optimization is a critical issue in the management of the multi-source large-scale urban centralized heating system (UCHS). A major challenge is to deal with the complex topological structure of its heating network. We investigate the operation enhancement of UCHS from the view of network splitting. We carry out the network splitting analysis of UCHS by establishing its heating network model and corresponding simulation platform based on graph theory. We validate the model against experimental data in a city located in northern China, and further use the model to show the effectiveness of network splitting by calculating its energy consumption indices under different splitting schemes. Simulation results show that the optimal network splitting scheme could improve the load distribution among the heating sources and reduce the operation cost. We apply the scheme during the 2018–2019 heating season and compare the results with the previous season operated by its existing scheme. The optimized scheme reduces heat supply requirements for heating sources and improves the load distribution among heating sources. With the weather condition change considered, seasonal accumulated area specific daily heat supply is reduced by 3.9%. Overall, seasonal natural gas consumption is reduced by 16.8%.

Bi-level modeling of district heating systems with prosumers

The paper deals with the actual problem of the functioning and development of district heating systems in the framework of the transition to intelligent energy, in which the active consumers (prosumers) holds the key place. The paper proposes an optimization mathematical model for management the operation of district heating systems taking into account prosumers based on the bi-level modeling method (bi-level programming). The proposed mathematical model allows taking into account the technical and economic characteristics of heat sources and heat networks, the interests of participants in the process of heat supply to consumers and determining the optimal conditions for management the operation of district heating systems.

Impacts of thermal energy storage on the management of variable demand and production in electricity and district heating systems: a Swedish case study

ABSTRACTThis study investigates how thermal energy storage (TES) influences the cost-optimal investment and operation of electricity and district heating (DH) systems in different scenarios. Greenfield energy system modelling for Year 2050 with a high time resolution shows that sensible TES strategies have a strong impact on the composition and operation of the DH system in all investigated scenarios. The introduction of TES displaces to a significant extent the heat-only boilers in all scenarios and can promote solar heating in small DH networks. The modelling shows that TES also promotes the use of power-to-heat processes and enables combined heat and power plants to increase full-load hours, with simultaneous adaptation to the variable production in the electricity system. A major benefit derived from TES is the ability to respond to rapid variations in the electricity system. Thus, the pit and tank storage systems with higher (dis)charging capacities are preferred over borehole storage.

Optimal operation of flexible heating systems for reducing wind power curtailment

Flexibility in a heating system refers to the ability of regulating its heat consumption/supply/storage from time to time, which indirectly affects the corresponding electricity production and consumption. Through an optimal use this kind of ability, integration challenges for wind power such as curtailment can be addressed. In the paper, a series of flexibility options in the heating system are modeled and investigated, including extraction combined heat and power plant, electric boiler, electric heat pump (HP), heat storage and demand response management of the heat load. Based on a mathematical model developed for achieving an optimal dispatch of the heating system, heating systems with various configurations of flexibility options can be investigated regarding their contribution to wind power curtailment. A practical case study is presented to validate the proposed solution, with eight configuration scenarios defined to represent the existing and other possible system setups. The results show that there is a huge potential of using the flexibility from the heat sector to support wind power integration, and the potential can be affected by the seasonal variations of energy demand, wind profile and technical parameters like efficiency of the HP. Further, contribution of different flexibility options to wind power integration is different in regards to the achieved operation-scale techno-economic performance.

ИМИТАЦИОННАЯ МОДЕЛЬ СИСТЕМЫ ОТОПЛЕНИЯ ПРИГОРОДНЫХ ЭЛЕКТРОПОЕЗДОВ ПОСТОЯННОГО ТОКА

Most of the Russian Federation territory is located in the zone of long-term exposure to negative ambient temperatures. In this regard, a significant proportion of power consumption in the suburban traffic on the railways of the Russian Federation accounts for the operation of heating and air conditioning systems. Currently, Russian and foreign scientists are developing energy-saving methods and tools to reduce the power consumption for auxiliary needs of electric-multiple units. In this paper, the authors used the method of constructing simulation models in the MATLAB Simulink program in order to create an energy-saving heating and air conditioning system since this method allows you to explore various options for constructing the studied systems with lower financial and labour costs in comparison with the experimental method. In order to verify its adequacy the simulation model includes standard values of electric energy consumption for heating and air conditioning for various sections and operating conditions obtained by the authors earlier during the correlation and regression analysis of data from parameter recorders installed in electric-multiple units. The results of the study showed the adequacy of application of the developed simulation model for organizing the control of power consumption for heating and air conditioning of direct current electric-multiple units.

Model research of the energy efficiency of a cogeneration backpressure steam turbine installation

In the contemporary district heating systems (DHS) heat energy for the customers is generated by cogeneration method, which leads to the saving of primary energy resources compared to the separate production method. The most widespread technology for combined production is based on steam turbine installations with adjustable steam extraction and backpressure steam turbine. In these technologies district heating water is heated to the required temperature either in district heaters in case of steam turbine with adjustable steam extractions or in boiler-condenser in case of backpressure steam turbine installations. The temperature of the district heat water at the inlet of the CHP installation depends on the mode of operation of the DHS. The heat load, distributed to consumers, is regulated at the heat source (CHP installation) by temperature and flow rate of the district heating water, mainly following the change in climatic factors. Current study presents the development of a simulation model of existing CHP backpressure steam turbine. The object studied is a backpressure steam turbine type SST-300 CE2L/V36S. Presented are results from the validation of the simulated model with data from the design documentation. The model has been used to study the energy efficiency of a steam turbine installation based on multivariate simulation calculations. The results obtained relate the energy efficiency indicators of CHP backpressure steam turbine with the factors that characterize the mode of operation of the district heating system.

A Novel Hybrid Spatial-Temporal Attention-LSTM Model for Heat Load Prediction

Accurate heat load prediction algorithm provides important support for the stable and efficient operation of smart district heating system (SDHS) and helps to realize energy saving and consumption reduction. However, previous researches on heat load prediction are mostly carried out on various regression analyses and modeling prediction, without considering the inherent time delay and spatial dependence between heat exchange stations during regulation. Therefore, a novel heat load prediction model based on the hybrid spatial-temporal attention long short-term memory (STALSTM) is proposed. The STALSTM model introduces the spatial dependence characteristics of heating pipe network into the heat load prediction model, and the influencing factors of heat consumption are considered comprehensively from the time and space dimensions. Then, the LSTM algorithm is used to memory the information of historical data sequence, and the attention mechanism is used to realize the adaptive estimation of the characteristic weight of each influencing factor, which improves the prediction accuracy. And in order to verify the effectiveness of the proposed model, a detailed experimental comparison is made between the STALSTM model and the state-of-the-art algorithms. The results show that the STALSTM model has the best prediction accuracy, and the correctness of introducing the spatial-temporal characteristics and the attention mechanism is also proved.

Interval-Valued Features Based Machine Learning Technique for Fault Detection and Diagnosis of Uncertain HVAC Systems

The operation of heating, ventilation, and air conditioning (HVAC) systems is usually disturbed by many uncertainties such as measurement errors, noise, as well as temperature. Thus, this paper proposes a new multiscale interval principal component analysis (MSIPCA)-based machine learning (ML) technique for fault detection and diagnosis (FDD) of uncertain HVAC systems. The main goal of the developed MSIPCA-ML approach is to enhance the diagnosis performance, improve the indoor environment quality, and minimize the energy consumption in uncertain building systems. The model uncertainty is addressed by considering the interval-valued data representation. The performance of the proposed FDD is investigated using sets of synthetic and emulated data extracted under different operating conditions. The presented results confirm the high-efficiency of the developed technique in monitoring uncertain HVAC systems due to the high diagnosis capabilities of the interval feature-based support vector machines and k-nearest neighbors and their ability to distinguish between the different operating modes of the HVAC system.

INVESTIGATION OF VARIABLE MODES OF CENTRALIZED HEAT SUPPLY SYSTEMS OPERATION WITH QUALITATIVE AND QUANTITATIVE REGULATION

The combined method of generating electric and heat energy at CHP plants has been and remains the most effective way of fuel saving both in housing and communal services and in industry. In Russia, historically, a qualitative method of regulation has been adopted, which consists in changing the temperature of the fluid depending on the change in the temperature of the outside air at a constant flow rate of the fluid. An analysis of the heat supply schemes of a number of Russian cities revealed that central quality regulation at heat sources has practically ceased everywhere. In modern methods of calculating the qualitative and quantitative regulation, the main load is heating, and the load of hot water is taken into account only by increasing the flow rate of network water and the variable modes of joint operation of heating and hot water systems are not calculated. Thus, at present, there are no methods for calculating the qualitative and quantitative regulation, allowing to fully taking into account the effect of the load of hot water on the operation of heating systems. Therefore, in modern conditions, the previously developed methods and technological methods of controlling the combined heat load are characterized by a decrease in efficiency, and, accordingly, the problem of their optimization arises. For different temperatures of outdoor air, the calculation of variable operating modes of the heat supply system was carried out, which showed that the existing schedules of qualitative and quantitative regulation cannot provide a comfortable temperature condition of the premises. Under the conditions of a connected supply of heat, simply adding up the flows of network water for heating and hot water supply fails to achieve optimal thermal conditions for the premises. Therefore, further improvement of the technology of the central qualitative and quantitative regulation of the heat load taking into account hot water supply is required.

Estimates of pollutant temporal and spatial variability in commercial buildings from the joint urban 2003 field experiments.

In this paper, we report on the indoor concentrations from a suite of full-scale outdoor tracer-gas point releases conducted in the downtown area of Oklahoma City in 2003. A point release experiment consisted of releases of sulfur hexafluoride (SF6 ) in multiple buildings and from different outdoor locations. From the measurements, we are able to estimate the concentration variations indoors for a building operating under "typical" operating conditions. The mean indoor spatial coefficients of variation are 30% to 45% from a daytime outdoor release are around 80% during an outdoor evening release. Having estimates of the spatial coefficient of variation provides stakeholders, including first responders, with the likely range of concentrations in the building when little is known about the building characteristics and operating behavior, such as developing urban-scale hazard and consequence analyses. We show differences in indoor measurements at different distances to the release points, floors of the building, and heating, ventilation, and air conditioning system (HVAC) operation. We also show estimates at different time resolutions. The statistics show that in the studied medium to large commercial buildings, spatial differences would result in peak indoor concentrations in certain parts of the buildings that may be substantially higher than the building average. To our knowledge, very few tracer gas measurements have been conducted in buildings of this scope, particularly with measurements on multiple floors and within a floor. The resulting estimates of spatial variability provide a unique opportunity for hazard assessment, and comparison to multi-zone models.

A study on operation control of urban centralized heating system based on cyber-physical systems

Intelligent and efficient operation of large-scale urban centralized heating system (UCHS) is a hot topic in urban energy system field. This study develops an intelligent operation control platform for China’s UCHS via “cyber-physical systems” (CPS). The platform is based on graph theory and thermal-hydraulic modeling and has been validated against measured data collected from the substations. 88.5% of the modeled substation supply pressure has an error of less than 5%, and 82.1% of the modeled substation return pressure has an error of less than 5%. The platform carries out “model-based prediction” and “prediction-based decision-making” by incorporating state sensing, load forecasting, modeling, and model-based operation optimization. The platform is further applied to a target UCHS using coal-based combined heat and power (CHP) units and gas-fired boilers as heating sources and covering an area of 15 million m2. To ensure the accuracy, this study carries out online calibration with real-time operation data and tests the load distribution feature during the pilot heating season. During a two-day operation, the optimized heating sources load distribution scheme could reduce natural gas consumption by up to 31.2% when compared with existing experience-based operation. The operation cost during that operation period is also reduced by 2.6%, accordingly.

Development Features of Heat Power Industry Legislation in Russia

Abstract In Russia, the legislative support for the construction and operation of heating systems is permanently developing and improving. The Federal law “On heat supply” adopted in 2010 is the basic and most important document that regulates the work of heating systems. Moreover, the country has more than 10 additional documents that regulate this industry, and a great number of documents that establish rules for building and operating energy systems. The paper presents the main documents that regulate the heat supply industry in the Russian Federation, and a brief description of the main stages of heating system life cycle and problems solved in each of them. Despite the national policy of energy conservation and energy efficiency enhancement, there are still problems related to heat supply management due to large extension, complexity and a variety of types and structures of the systems. The main cause of the poor heat supply efficiency in Russia is explained by a considerable change in the structure of heat loads that has occurred of late years, a decrease in the loading of the main generating equipment and heat networks, which amid other things is fostered by an increasing wear of the systems. Upgrading of generating capacities and heat networks is considered in the framework of long-term investment projects for their modernization and expansion. The obtained solutions are reflected in the Schemes of urban heat supply. This paper proposes solutions aimed at enhancing the effectiveness of decisions made in the field of heat supply. It formulates the proposals on organization and regulation of the activities of all the participants in heat supply in the stage of long-term planning of heating system expansion, because well-founded and rational planning of construction and expansion of the systems is a basis for their efficient operation.

Reducing environmental pollution and fuel consumption using optimization algorithm to develop combined cooling heating and power system operation strategies

A combined cooling heating and power model with photovoltaic generation unit, thermal storage tank and battery is established to improve energy efficiency and reduce carbon emissions in combined cooling heating and power model for achieving cleaner production and environmental pollution reduction, and the hybrid following the electric load strategy and hybrid following the thermal load strategy are proposed based on the following the electric load strategy and following the thermal load strategy. Besides, the chaos-mutation-whale optimization algorithm is proposed to solve the models by using chaotic initialization and mutation rules into the original whale optimization algorithm. A large hotel case is used to analyze the feasibility of the proposed method. The result demonstrates the electricity import saving ratio, primary energy saving ratio and fuel consumption to cost ratio are 62.07%, 35.75% and 1.47% under the hybrid following the thermal load strategy, and the chaos-mutation-whale optimization algorithm achieves optimization in a shorter number of iterations. The performance indicators are better than the following the electric load, following the thermal load and hybrid following the thermal load strategies, indicating that environmental pollution and fuel consumption are greatly reduced by using the proposed method, which is of great significance to the realization of cleaner production and environmental sustainability. This study is carried out under ideal circumstances.

Demonstration of heating demand peak shaving in smart homes

Flexible heating demand in buildings plays an important role in achieving a carbon neutral society. For the district heating system of Copenhagen, heating demand flexibility can help to eliminate the use of fossil-fueled boilers that are used during peak-load periods. In this project, field tests in 16 apartments were conducted, aiming to gain insights into the use of information and communication technologies (ICT) to manage heating systems operation for flexible demand. The apartments are equipped with sensors and devices interfaced to an ICT system composed of blocks responsible for data storage, monitoring and control. In the experiments, we controlled temperature setpoints of individual rooms during defined periods of the day, and continuously developed control strategies throughout the tests in the heating season 2018/19. The final algorithm was implemented with features to reduce the rebound effect and include residents feedback. All the algorithms are generic and can be applied in other smart homes where heating supply to rooms is controlled using thermostats. The ICT system architecture used in the experiments showed to be a feasible way to implement demand side management (DSM) in the heating system, and the learning process of the experiments resulted in improvements on the control strategies, leading to a better system performance.

Simulation of thermal characteristics of heat supply systems in variable operating modes

The operation of heat supply systems is often associated with the inefficient use of heat energy. New formulas have been obtained for calculation of variable thermal and hydraulic modes of heat exchangers of heat supply systems. The rather high correlation coefficient of the operational and design parameters of the heating system operation makes it possible to use the obtained formulas to optimize the variable operating modes of heat exchangers when using programmable regulators.

Installation and Operation of a Double-Sided Laser Heating System for the Synthesis of Novel Materials Under Extreme Conditions

Installation and Operation of a Double-Sided Laser Heating System for the Synthesis of Novel Materials Under Extreme Conditions

Numerical analysis of the operation regulation in a solar heating system with seasonal water pool thermal storage

A solar heating system with seasonal water pool thermal storage (SHS-SWPTS) was represented to investigate the year-round operating performance in the cold areas of China. According to the performance of solar collector, heat storage pool, water source heat pump (WSHP) and the water temperature operation of floor radiant heating system, a year-round operation control strategy of the above system was proposed. A simulation model with self-programmed control module was established in the TRNSYS simulation platform. And the accuracy of the simulation model was verified. The simulated model consists of designed collector area of 8000 m2 and the volume of the seasonal storage pool of 13300 m3. By simulating and analyzing the year-round running performance, several parameters were achieved, such as building dynamic heat load and outlet water temperature of the collector. Then, the rationality of system operation control strategy was analyzed. The results show that the heating load of the solar heating system can match the dynamic heat load of the building. During the initial heating stage, solar energy can guarantee 100% indirect heating and direct heating heat loads by running hot water storage pools. In addition, from mid-January to the end of the heating period (the beginning of April), the average COP of the WSHP is 4.3. And the monthly average solar energy guarantee rate of the system is between 70% and 75%. Thus, it is proved that this operation control strategy can improve the solar energy guarantee rate and system energy efficiency of seasonal solar energy heating system.

Modification of the solar heating system diagnostic method under operating conditions

One of the problems with the operation of solar heating systems is the variable capacity of the system dependent on the prevailing operating conditions. One of the methods for increasing the capacity of a solar system is to control the volume flow of the working medium. Volume flow of working medium in solar heating installation should be follow operating conditions. Designing a continuous control system based eg. on the PID controller requires knowledge of the dynamic properties of a solar system under operating conditions: gain coefficient, equivalent time constant and delay time of the solar collector response to a change in solar radiation intensity and the inlet temperature of a working medium. To date, the delay time has been omitted in the analyses. It is necessary to know the value of the delay time for proper design of the solar system controls, because the object response cannot be simultaneous with the moment of the input function. The paper presents the method for determining the dynamic properties of a solar system under operating conditions. The method is based on the comparison of two models: an analog model based on the energy balance of a collector and a digital model developed with the use of parametric identification based on a short-term measurement of solar radiation intensity and working medium temperatures. In the collector analog model, on the basis of the design and operating parameters of the collector, the transport delay time has been defined, which is an innovative aspect of this study. The modified analog collector model was verified on the basis of the step response determined experimentally in accordance with the applicable ISO 9806: 2017 standard. A very good convergence of the model with actual data was achieved for the time constant – 87%, effective thermal capacity – 85.9%, and the delay time – 96%. Practical application of the modified diagnostic method is presented on the example of a solar heating system composed of five flat-plate collectors with a total absorber area of 10 m2.

Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms

Predicting next-day heat load curves is essential to guarantee sufficient heat supply and optimal operation of district heat systems (DHSs). Existing studies have mainly investigated one-step ahead forecasting methods, which can predict a single value at a future time step. To predict heat load curves, multi-step ahead forecasting methods are needed. This study proposes a machine learning-based framework for multi-step ahead DHS heat load forecasting. Specifically, support vector regression, deep neural network, and extreme gradient boosting (XGBoost) are respectively used as the base learner to develop forecasting models. Two multi-step ahead forecasting methods, i.e. direct strategy and recursive strategy, adopt the learnt models to generate predictions. A DHS in China is used as the case study to comprehensively assess the performance of these two forecasting strategies. Recursive strategy using the XGBoost-based forecasting model can achieve the most accurate and stable predictions with a value of 10.52% for the coefficient of variation of root mean square error. Furthermore, the modeling process of recursive strategy is much more convenient than that of direct strategy. The research shows that the recursive strategy is a better solution to multi-step ahead forecasting than the direct strategy with respect to accuracy, prediction stability, and modeling process.