Energy efficiency performance of multi-energy district heating and hot water supply system

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.

Value analysis of district heating system with gas-fired peak load boiler in secondary network

In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fuels of the system,including coal and gas,would cause different environmental impacts. Meanwhile,the reliability of the heating networks would be changed because the peak load regulating boiler could work as a standby heat source. A model for assessment of heating system was established by value analysis to optimize this kind of system. Energy consumption,greenhouse gas emission,pollution emission and system reliability were selected as functional assessment indexes in the model. Weights of each function were determined by analytical hierarchy process (AHP) and experts consultation. Life cycle cost was used as the cost in the model. A real case as an example was discussed to obtain the optimal base load ratio. The result shows that the optimal base load ratio of the case is 0.77.

The Preliminary Research of Sea Water District Heating and Cooling for Tallinn Coastal Area

This paper describes possibilities to utilize sea water for district heating and cooling purposes in Tallinn costal area. The sea water temperature profiles and suitability of heating and cooling generation are studied for continental climatic conditions. The district network study bases on 21 buildings located near to the Gulf of Finland. Industrial reversible heat pump technology is selected to cover heating and cooling loads for the new buildings. Combination of existing district heating and heat pump technology is considered for existing buildings. The results show possibilities, threats and need for further research of the sea water based heat pump district network implementation.

A Neuro-Fuzzy Based Adaptive Set-Point Heat Exchanger Control Scheme in District Heating System

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.

Polish District Heating Systems--Development Perspectives

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.

Wireless Sensor Networks for Optimisation of District Heating

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.

Solid Particle Emission Abatement from Biomass-Fired Boilers at District Heating Plants

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.

Test and Analysis of Indoor Thermal Environment of Urban Heating Residential Building in Hanzhong Area

By testing indoor and outdoor thermal environment of residential buildings that apply 4 mostused heating ways in Hantai District,Hanzhong City,this paper explored the indoor thermal environment conditions of different heating ways,to provide references for choosing a suitable heating way in the local area.

Topology reduction through machine learning to accelerate dynamic simulation of district heating

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.

Legal Framework as a Core Element of District Cooling Success—The Case of Denmark

This paper describes the Danish legal framework for district cooling as an example of a model which so far has had limited success. A number of suggestions are analysed and discussed.

基于ANFIS的太阳能-空气源热泵供暖系统温度控制研究

针对太阳能-空气源热泵供暖系统运行环境复杂多变,模糊控制器的设计高度依赖人工经验的问题,提出一种基于自适应神经模糊推理系统(ANFIS)改进的模糊控制方法。该方法利用ANFIS在复杂系统建模中的优势,结合供暖系统温度响应特性和实际运行数据,建立联合供暖系统变工况ANFIS模型,生成与系统性能适配的模糊规则库并传递给模糊控制器执行。Matlab/Simulink仿真对比试验表明,与单一的模糊控制相比,该方法的控制精度提高了17.65%,调节时间缩短了36.4%,具有更高的控制精度和响应速度。

小样本情形集中供热系统元件失效率估计方法研究

对国内3个典型城市集中供热系统失效事件进行了调查统计,并对元件失效率进行了估计。针对直接估计模型存在的限制,引入了Bayes(贝叶斯)理论,融合历史信息,提出了一般Bayes模型和分层Bayes模型。比较了3种模型的精度,管道、阀门和补偿器3类元件的分层Bayes模型精度分别为0.31、0.32、0.29,在3种模型中精度最高;最终通过改变样本量,得出3种模型精度随样本量增加均呈现上升趋势,且相互差距逐渐缩小,验证了Bayes模型在小样本情形的适用性。

西藏高原零碳太阳能区域供暖新模式与实践

西藏高原冬季寒冷漫长,煤炭、天然气等常规能源储量近乎为零,建筑供暖挑战极大。然而,当地太阳能资源极其丰富,具备利用太阳能实现建筑零碳供暖的先决条件。针对西藏高原“绿洲型”县城和乡镇,对“规模化太阳能集热+大型水体蓄热+建筑围护结构差异化保温+南北分环独立供暖”全链条零碳太阳能区域供暖模式进行了探索,阐述了规模化太阳能集热技术与产品、大型蓄热水体容量配置与高效蓄取热技术、建筑围护结构“差异化保温”设计方法、南北分环双独立供暖新系统等成套关键支撑技术与方法,并介绍了供暖新模式在西藏高原的工程实践经验与成效。

利用数据中心余热供热的系统设计与分析

数据中心余热供热是提高数据中心能源利用效率和实现冬季清洁供暖的重要途径。本文提出了一种适用于数据中心的长距离供热系统,在热源和热汇处设置多级热泵以增大供热管网供回水温差,并使用储热装置保障数据中心和供热系统的安全性,提高数据中心余热利用率。以张家口某数据中心为例进行了分析,该系统初投资为50.21元/m^(2),运行费用为26.37元/GJ,投资回收期约为5.31 a,具有较好的经济性和节能减排效果。

地热驱动的双温热力站系统及其变工况性能

高温地热能是宝贵的可再生能源供热资源,降低地热水回水温度是发挥地热供热潜力、扩大供热面积的重要途径。鉴于既有建筑普遍采用散热器等高温供热末端,而新建建筑多采用地暖等低温供热末端,二者的需求供水温度不同,对此提出了单吸收式热泵+双换热器的地热能驱动双温热力站系统,以制取高、低温末端用双温热水,并尽可能降低地热水回灌温度。模拟分析表明:在地热出水为100℃,二次网高、低温末端供热量相同且供水温度分别为50℃和35℃条件下设计的双温热力站,可将地热水回水温度降至20.1℃,相比于采用2个换热器串联的热力站,其地热水的回水温度可降低14.9℃、流量可降低18.6%,系统的COP提升11%,具有显著的节能优势。变工况分析表明:低温供热末端的应用有利于进一步降低地热水回灌水温,增加向末端用户的供热量,并提高双温热力站系统的COP。

基于数据增广的区域供热系统热力站负荷预测模型准确率提升方法研究

开展了热力站数据生成模型研究,基于生成对抗网络和去噪扩散概率模型建立了数据生成模型,通过学习气象、室温、热力站运行数据的联合分布,对原始训练数据进行增广,为预测模型训练提供充足的数据支撑,从而提高预测模型的准确率。在北京市某热力站进行了验证和实际测试,结果表明:该方法可以将热力站一次侧电动调节阀开度和二次网供水温度的预测误差分别降低约7%和11%;同时,应用准确率提升后的负荷预测值进行供热量调节得到的预计室温与室温目标值之间的偏差可进一步降低5.44%。基于生成对抗网络的生成模型能够扩展预测模型的预测范围,基于去噪扩散概率模型的生成模型能够在原预测范围内提高预测模型的准确率。本文研究可为进一步提高区域供热系统热力站负荷预测能力与按需精准调控水平提供支撑。

District heating system operation in power systems with high share of wind power

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.

Energy efficiency and carbon dioxide emissions reduction opportunities in district heating source in Tianjin

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.

Optimal Scheduling for Combined District Heating and Power Systems Using Subsidy Strategies

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.

电-热-氢综合能源系统鲁棒区间优化调度

储能技术与风电相结合实现电能的时空平移是解决系统运行稳定性问题的有效手段。氢储能具有储存容量大、可实现电热联产联供的优点,具有很大的发展潜能。然而由于风电存在不确定性,氢储能系统在频繁切换工作模式时面临着不确定的热能需求。因此,文中综合考虑氢储能在间歇模式下的热能需求,首先,介绍了氢储能系统接入的电-热综合能源系统基本结构,将风电场与氢储能相结合构成风-氢混合系统;然后,提出考虑风-氢混合系统热平衡需求不确定性的电-热综合能源系统鲁棒区间优化调度模型;最后,基于对偶理论,对所提出的模型转化求解,通过算例对比分析各类情况优化结果,验证了氢储能在促进风电消纳、提高系统能源综合利用率方面的有效性,并证明了考虑电解槽和燃料电池工作温度能提高系统的工作效率并提高风电场并网功率。