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  • 1.
    Calikus, Ece
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Nowaczyk, Sławomir
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pinheiro Sant'Anna, Anita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Gadd, Henrik
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap. Öresundskraft, Helsingborg, Sweden.
    Werner, Sven
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS).
    A data-driven approach for discovering heat load patterns in district heating2019Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 252, artikel-id 113409Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    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.

  • 2.
    Gadd, Henrik
    et al.
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Bio- och miljösystemforskning (BLESS), Energiteknik.
    Werner, Sven
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Bio- och miljösystemforskning (BLESS), Energiteknik.
    Achieving low return temperature from district heating substations2014Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 136, s. 59-67Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    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.

  • 3.
    Gadd, Henrik
    et al.
    Högskolan i Halmstad, Sektionen för ekonomi och teknik (SET), Bio- och miljösystemforskning (BLESS), Energiteknik.
    Werner, Sven
    Högskolan i Halmstad, Sektionen för ekonomi och teknik (SET), Bio- och miljösystemforskning (BLESS), Energiteknik.
    Daily Heat Load Variation in Swedish District Heating Systems2010Ingår i: 12th International Symposium on District Heating and Cooling, Tallinn, Estonia: Tallinn University of Technology , 2010, s. 199-201Konferensbidrag (Refereegranskat)
    Abstract [en]

    If daily heat load variations could be eliminated in district heating-systems, it would make the operation of the district heating system less costly and more competitive . There would be several advantages in the operation such as:

    • Less use of expensive peak load power where often expensive fuels are used.
    • Less need for peak load power capacity.
    • Easier to optimize the operation that leads to higher conversion efficiencies.
    • Less need for maintenance because of more smooth operation of the plants

    There are a number of ways to handle the daily variations of the heat load. Two often used are large heat storages or using the district heating network as temporary storage. If it would be possible to centrally control the customer substations, it would also be possible to use heavy buildings connected to the district heating system as heat storages.

    To be able to find the best way to reduce or even eliminate the daily heat load variations, you need to understand the characteristics of the daily variations. This paper will describe a way of characterizing daily heat load variations in some Swedish district heating-systems.

  • 4.
    Gadd, Henrik
    et al.
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Bio- och miljösystemforskning (BLESS), Energiteknik.
    Werner, Sven
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Bio- och miljösystemforskning (BLESS).
    Daily heat load variations in Swedish district heating systems2013Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 106, s. 47-55Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    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.

  • 5.
    Gadd, Henrik
    et al.
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Bio- och miljösystemforskning (BLESS), Energiteknik.
    Werner, Sven
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Bio- och miljösystemforskning (BLESS).
    Heat load patterns in district heating substations2013Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 108, s. 176-183Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    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.

  • 6.
    Gadd, Henrik
    et al.
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Bio- och miljösystemforskning (BLESS), Energivetenskap.
    Werner, Sven
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Bio- och miljösystemforskning (BLESS), Energivetenskap.
    Thermal energy storage systems for district heating and cooling2015Ingår i: Advances in Thermal Energy Storage Systems: Methods and Applications / [ed] Luisa F. Cabeza, Cambridge: Woodhead Publishing Limited, 2015, 1, s. 467-478Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    The context for this chapter is the current use and typical applications of thermal energy storages within contemporary district heating and cooling systems in the Nordic countries. Examples include a new assessment method, distributed heat storages, and hourly, daily, weekly, and seasonal heat and cold storages. Specific sizes have been estimated for 209 heat storages and 9 cold storages.

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