Understanding the heat usage of customers is crucial for effective district heating operations and management. Unfortunately, existing knowledge about customers and their heat load behaviors is quite scarce. Most previous studies are limited to small-scale analyses that are not representative enough to understand the behavior of the overall network. In this work, we propose a data-driven approach that enables large-scale automatic analysis of heat load patterns in district heating networks without requiring prior knowledge. Our method clusters the customer profiles into different groups, extracts their representative patterns, and detects unusual customers whose profiles deviate significantly from the rest of their group. Using our approach, we present the first large-scale, comprehensive analysis of the heat load patterns by conducting a case study on many buildings in six different customer categories connected to two district heating networks in the south of Sweden. The 1222 buildings had a total floor space of 3.4 million square meters and used 1540 TJ heat during 2016. The results show that the proposed method has a high potential to be deployed and used in practice to analyze and understand customers’ heat-use habits. © 2019 Calikus et al. Published by Elsevier Ltd.

This paper presents a novel approach to modeling the gradual reduction in heat demand and the evolving expansion of district heating (DH) grids for assessing the DH potential in EU member states (MS). It introduces new methodological elements for modeling the impact of connection rates below 100% on heat distribution costs in both dense and sparse areas. The projected heat demand in 2050 is derived from a decarbonization scenario published by the EU, which would lead to a reduction in demand from 3128 TWh in 2020 to 1709 TWh by 2050. The proposed approach yields information on economic DH areas, DH potential, and average heat distribution costs. The results confirm the need to expand DH grids to maintain supply levels in view of decreasing heat demand. The proportion of DH potential from the total demand in the EU-27 rises from 15% in 2020 to 31% in 2050. The analysis of DH areas shows that 39% of the DH potential is in areas with heat distribution costs above 35 EUR/MWh, but most MS have average heat distribution costs between 28 and 32 EUR/MWh. The study reveals that over 40% of the EU's heat demand is in regions with high potential for implementing DH.  © 2023 The Author(s)

District heating systems contribute with low primary energy supply in the energy system by providing heat from heat assets like combined heat and power, waste incineration, geothermal heat, wood waste, and industrial excess heat. These heat assets would otherwise be wasted or not used. Still, there are several reasons to use these assets as efficiently as possible, i.e., ability to compete, further reduced use of primary energy resources, and less environmental impact. Low supply and return temperatures in the distribution networks are important operational factors for obtaining an efficient district heating system. In order to achieve low return temperatures, customer substations and secondary heating systems must perform without temperature faults. In future fourth generation district heating systems, lower distribution temperatures will be required. To be able to have well-performing substations and customer secondary systems, continuous commissioning will be necessary to be able to detect temperature faults without any delays. It is also of great importance to be able to have quality control of eliminated faults. Automatic meter reading systems, recently introduced into district heating systems, have paved the way for developing new methods to be used in continuous commissioning of substations. This paper presents a novel method using the temperature difference signature for temperature difference fault detection and quality assurance of eliminated faults. Annual hourly datasets from 140 substations have been analysed for temperature difference faults. From these 140 substations, 14 were identified with temperature difference appearing or eliminated during the analysed year. Nine appeared during the year, indicating an annual temperature difference fault frequency of more than 6%. © 2014 The Authors.

Heat load variations in district heating systems are both seasonal and daily. Seasonal variations have mainly its origin from variations in outdoor temperature over the year. The origin of daily variations is mainly induced by social patterns due to customer social behaviours. Heat load variations cause increased costs because of increased peak heat load capacity and expensive peak fuels. Seasonal heat load variations are well-documented and analysed, but analyses of daily heat load variations are scarce. Published analyses are either case studies or models that try to predict daily heat load variations. There is a dearth of suitable assessment methods for more general analyses of existing daily load variations. In this paper, a novel assessment method for describing daily variations is presented. It is applied on district heating systems, but the method is generic and can be applied on every kind of activity where daily variations occur. The method was developed from two basic conditions: independent of system size and no use of external parameters other than of the time series analysed. The method consists of three parameters: the annual relative daily variation that is a benchmarking parameter between systems, the relative daily variation that describes the expected heat storage size to eliminate daily variations, and the relative hourly variation that describes the loading and unloading capacity to and from the heat storage. The assessment method could be used either for design purposes or for evaluation of existing storage. The method has been applied on 20 Swedish district heating systems ranging from small to large systems. The three parameters have been estimated for time series of hourly average heat loads for calendar years. The results show that the hourly heat load additions beyond the daily averages, vary between 3% and 6% of the annual volume of heat supplied to the network. Hereby, the daily variations are smaller than the seasonal variations, since the daily heat load additions, beyond the annual average heat load, are between 17% and 28% of the annual volume of heat supplied to the network. The size of short term heat storage to eliminate the daily heat load variations has been estimated to a heat volume corresponding to about 17% of the average daily heat supplied into the network. This conclusion can also be expressed as an average demand of 2.5 m3 of heat storage volume per TJ of heat supplied by assuming a water temperature difference of 40 C. The capacity for loading and unloading the storage should be equal to about half of the annual average heat load for heat supplied into the network. © 2013 Elsevier Ltd.

Current temperature levels in European district heating networks are still too high with respect to future conditions as customer heat demands decrease and new possible heat source options emerge. A considerable reduction of temperature levels can be accomplished by eliminating current faults in substations and customer heating systems. These faults do not receive proper attention today, because neither substations nor customer heating systems are centrally supervised. The focus of this paper has been to identify these faults by annual series of hourly meter readings obtained from automatic meter reading systems at 135 substations in two Swedish district heating systems. Based on threshold methods, various faults were identified in 74% of the substations. The identified faults were divided into three different fault groups: Unsuitable heat load pattern, low average annual temperature difference, and poor substation control. The most important conclusion from this early study of big data volumes is that automatic meter reading systems can provide proactive fault detection by continuous commissioning of district heating substations in the future. A complete reduction of current faults corresponds to approximately half the required reduction of the current temperature levels in the effort toward future low-temperature district heating networks. (C) 2015 The Authors. Published by Elsevier Ltd.

Future smart energy grids will require more information exchange between interfaces in the energy system. One interface where dearth of information exists is in district heating substations, being the interfaces between the distribution network and the customer building heating systems. Previously, manual meter readings were collected once or a few times a year. Today, automatic meter readings are available resulting in low cost hourly meter reading data. In a district heating system, errors and deviations in customer substations propagates through the network to the heat supply plants. In order to reduce future customer and heat supplier costs, a demand appears for smart functions identifying errors and deviations in the substations. Hereby, also a research demand appears for defining normal and abnormal heat load patterns in customer substations. The main purpose with this article is to perform an introductory analysis of several high resolution measurements in order to provide valuable information about substations for creating future applications in smart heat grids. One year of hourly heat meter readings from 141 substations in two district heating networks were analysed. The connected customer buildings were classified into five different customer categories and four typical heat load patterns were identified. Two descriptive parameters, annual relative daily variation and annual relative seasonal variation, were defined from each 1 year sequence for identifying normal and abnormal heat load patterns. The three major conclusions are associated both with the method used and the objects analysed. First, normal heat load patterns vary with applied control strategy, season, and customer category. Second, it is possible to identify obvious outliers compared to normal heat loads with the two descriptive parameters used in this initial analysis. Third, the developed method can probably be enhanced by redefining the customer categories by their indoor activities.

Increased recovery of excess heat from thermal power generation and industrial processes has great potential to reduce primary energy demands in EU27. In this study, current excess heat utilisation levels by means of district heat distribution are assessed and expressed by concepts such as recovery efficiency, heat recovery rate, and heat utilisation rate. For two chosen excess heat activities, current average EU27 heat recovery levels are compared to currently best Member State practices, whereby future potentials of European excess heat recovery and utilisation are estimated. The principle of sequential energy supply is elaborated to capture the conceptual idea of excess heat recovery in district heating systems as a structural and organisational energy efficiency measure. The general conditions discussed concerning expansion of heat recovery into district heating systems include infrastructure investments in district heating networks, collaboration agreements, maintained value chains, policy support, world market energy prices, allocation of synergy benefits, and local initiatives. The main conclusion from this study is that a future fourfold increase of current EU27 excess heat utilisation by means of district heat distribution to residential and service sectors is conceived as plausible if applying best Member State practice. This estimation is higher than the threefold increase with respect to direct feasible distribution costs estimated by the same authors in a previous study. Hence, no direct barriers appear with respect to available heat sources or feasible distribution costs for expansion of district heating within EU27. © 2012 Elsevier Ltd.

The competitiveness of present and future district heating systems can be at risk when residential and service sector heat demands are expected to decrease in the future. In this study, the future competitiveness of district heating has been examined by an in depth analysis of the distribution capital cost at various city characteristics, city sizes, and heat demands. Hereby, this study explores an important market condition often neglected or badly recognised in traditional comparisons between centralised and decentralised heat supply.

By a new theoretical approach, the traditional and empirical expression for linear heat density is transformed into an analytical expression that allows modelling of future distribution capital cost levels also in areas where no district heating exists today. The independent variables in this new analytical expression are population density, specific building space, specific heat demand and effective width.

Model input data has primarily been collected from national and European statistical sources on heat use, city populations, city districts and residential living areas. Study objects were 83 cities in Belgium, Germany, France, and the Netherlands. The average heat market share for district heat within these cities was 21 % during 2006.

The main conclusion is that the future estimated capital costs for district heat distribution in the study cities are rather low, since the cities are very dense. At the current situation, a market share of 60 % can be reached with a marginal distribution capital cost of only 2.1 €/GJ, corresponding to an average distribution capital cost of 1.6 €/GJ. The most favourable conditions appear in large cities and in inner city areas. In the future, there is a lower risk for reduced competitiveness due to reduced heat demands in these areas, since the increased distribution capital cost is low compared to the typical prices of district heat and competing heat supply. However, district heating will lose competitiveness in low heat density areas. Hence, reduced heat demands in high heat density areas are not a general barrier for district heating in the future. © 2010 Elsevier Ltd.

This paper presents a newly developed methodology aimed at assessing at national level the techno-economic potential of district heating (DH) based on renewables and excess heat sources. The novelty of the model lies in the use of an optimization approach to match heat demand and heat sources at large scale level, while keeping a high degree of spatial detail. Areas suitable for DH adoption are identified by minimizing heat delivery costs, and therefore by choosing the most economical technology between district heating and the alternative individual solution. The optimization approach, usually applicable at limited analytical scope because of the computational burden, is here adapted to large scale analysis through the introduction of novel methodological elements with which the network topology is simulated nationwide. The methodology applies to preliminarily identified maps of available heat sources and eligible heat demand, with the quantification of the latter including retrofitting and low connection rate scenarios. It then consists in two steps: connecting elements in a graph through triangulation and routing algorithms and optimizing connections to minimize the overall heat delivery costs, either by adopting district heating or individual heating systems. The whole methodology is based on open-source data and tools for broad applicability. The paper presents the elaborated methodology together with the application of the entire model to Italy. The outcome is a map of the potential district heating systems identified with significant spatial detail nationwide. A four-fold expansion is envisaged, covering 12% of the national heat demand with renewables- and excess heat- based district heating. © 2024 The Authors. Published by Elsevier Ltd.

District heating and cooling systems can aid in decarbonisation and the provision of efficient heating and cooling in Europe. However, whereas these systems have achieved high penetration rates in colder climates of Northern, Central and Eastern Europe, they remain marginal in milder climates of Southern Europe. In terms of network design, district heating and cooling systems can be configured in different ways. In so-called warm networks, the required temperature for all the consumers is attained city-wide, and in so-called cold systems, the necessary temperature is achieved at the consumers' premises by ancillary equipment. The most cost-effective heating and cooling solution for urban areas requires investigation. This research models and compares cold and warm district energy systems with other heating and cooling solutions through a comprehensive case study executed in the city of Bilbao, Spain. The city is characterised by a mild climate and a high population density which is characteristic of many Southern European cities. The results show that district energy systems are economically advantageous compared to other low-carbon solutions, such as air-source heat pumps. However, these systems are not able to outcompete natural gas under current cost and taxation levels. Warm networks provide a cheaper source of heat compared to cold networks, but both network types lead to similar expenditures for combined heating and cooling supply. This paper, presents the study context and its results, and is complemented by an exhaustive detailed methodology document and a separate supplementary material repository. © 2024 The Authors

This paper presents a review of the sparse district-heating research programme undertaken in Sweden between 2002 and 2006. The goal of the programme was to increase the future competitiveness for district heat in low heat density areas, e.g., suburban single-family houses and small villages. Such areas are unfavourable, since revenues from heat sold are low compared with the investment cost for the local distribution network. In Sweden, district heat has a dominant position in the heat market for residential and service-sector buildings. In order for the business to grow, it is necessary to increase the rate of expansion in the detached-house segment. This is why the programme was initiated. The extent of the programme was set at € 3.6 million with equal financing from the Swedish District-Heating Association and the Swedish Energy-Agency. The research was carried out in three phases: a state of the art survey; a development phase focused on productivity gains where new research on both technology and customer interaction was performed; and finally a demonstration phase where new methods were tested in full-scale field operation. The programme has shown that the Swedish district-heating industry needs to adjust in order to reach a higher profitability for sparse district-heating investments. Tradition from large-scale high-density district heating is hard to scale to fit sparse district-heating systems. For example, the construction becomes very labour intensive and the industry is weak when it comes to market-oriented business logic, sales and private customer interaction. Innovation seems to be a way forward and active management of innovations is a way to create increased value of the investments. Other keys to improving the profitability of sparse district-heating investments are more efficient working routines (resulting in higher productivity) and revised ways of customer communications. These seem more important than increasing efficiency in district-heating technology. © 2007.

The expansion of district heating into areas of low heat densities (heat sparse areas) constitutes a challenge due to the higher distribution costs. The profitability of sparse district heating has been analysed from actual investments in 74 areas with 3227 one-family houses connected to district heating between 2000 and 2004 in Göteborg, Sweden. The profitability was estimated from a probable price model, a typical marginal heat generation cost, and the investments from the actual connections made. The analysis identified factors as the linear heat density and heat sold per house explaining the main variations in profitability. The profitability analysis was concluded with a competition analysis. The main conclusion is that sparse district heating is possible when reaching low investment costs for the local distribution network and low marginal costs for the heat generation. In Sweden, the general competitiveness of sparse district heating is facilitated by the high consumption taxes for fuel oil, natural gas, and electricity. Hence, it should be more difficult to introduce sparse district heating in other countries with low energy taxes. © 2008.