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  • 1.
    Du, Y.
    et al.
    College of Electronics and Information Engineering, Tongji University, Shanghai, China.
    Wang, C.
    College of Electronics and Information Engineering, Tongji University, Shanghai, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Song, Jingjing
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Li, B.
    School of Mechanical Engineering, Hubei University of Arts and Science, Hubei Province, China.
    Clustering heat users based on consumption data2019In: Energy Procedia, Elsevier Ltd , 2019, Vol. 158, p. 3196-3201Conference paper (Refereed)
    Abstract [en]

    In today's district heating (DH) energy market, it is common to use user functional categories in price models to determine the heat price. However, users in the same category do not necessarily have the same energy consumption patterns, which potentially leads to unfair prices and many other practical issues. Taking into account heat usage characteristics, this work proposes two data-driven methods to cluster DH users to identify similar usage patterns, using practical energy consumption data. Efforts are focused on extracting representative features of users from their daily usage profiles and duration curves, respectively. Employing clustering based on these features, the resulting typical usage patterns and user category distributions are discussed. Our results can serve as potential inputs for future energy price models, demand-side management, and load reshaping strategies.

  • 2.
    Li, Hailong
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Song, Jingjing
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Sun, Q.
    Institute of Thermal Science and Technology, Shandong University, Jinan, China.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Zhang, Q.
    China Petroleum University, Beijing, China.
    A dynamic price model based on levelized cost for district heating2019In: Energy, Ecology and Environment, ISSN 2363-7692, Vol. 4, no 1, p. 15-25Article in journal (Refereed)
    Abstract [en]

    District Heating (DH) is facing a tough competition in the market. In order to improve its competence, an effective way is to reform price models for DH. This work proposed a new dynamic price model based on the levelized cost of heat (LCOH) and the predicted hourly heat demand. A DH system in Sweden was used as a case study. Three methods were adopted to allocate the fuel cost to the variable costs of heat production, including (1) in proportion to the amount of heat and electricity generation; (2) in proportion to the exergy of generated heat and electricity; and (3) deducting the market price of electricity from the total cost. Results indicated that the LCOH-based pricie model can clearly reflect the production cost of heat. Through the comparison with other market-implemented price models, it was found that even though the market-implemented price models can, to certain extent, reflect the variations in heat demand, they cannot reflect the changes in production cost when different methods of heat production are involved. In addition, price model reforming can lead to a significant change in the expense of consumers and consequently, affect the selection of heating solution.

  • 3.
    Lundström, Lukas
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Song, Jingjing
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    SEASONAL DEPENDENT ASSESSMENT OF ENERGY CONSERVATION WITHIN DISTRICT HEATING AREAS2014In: Proceedings from the 14th International Symposium on District Heating and Cooling, September 7th to September 9th, 2014, Stockholm, Sweden / [ed] Anna Land, Stockholm: Swedish District Heating Association , 2014Conference paper (Refereed)
    Abstract [en]

    When housing companies plan for energy conserving renovations, costs and amount of saved energy are usually estimated with yearly mean values. Yet the fuel mix varies widely depending on heat demand of district heating system, often with higher cost and CO2 emission rates during winter than summer.

    Instead of comparing different energy conserving measures’ potentials with yearly mean values, it would be beneficial to examine them in a higher resolution, e.g. on daily or monthly basis, to identify real effectiveness of different measures in reducing CO2-emissions and primary energy consumption.

    In this study, three energy conserving measures are put into a building simulation model to obtain results of hourly energy consumption reduction, which is then fitted into a district heating optimization model to analyze the impact on district heating system.

    This study also discuss the correlation between energy cost for the customer and different measures’ environmental impact under new circumstances: seasonal energy price models of district heating, a price model which introduce price fluctuation throughout a year. This new factor provides a more comprehensive incitement to the property owners to encourage them to make environmental friendly decisions when planning for energy conserving renovations.

  • 4.
    Song, Jingjing
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Restructured district heating price models and their impact on district heating users2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    District heating (DH) is considered to be an efficient, environmentally friendly and cost-effective method for providing heat to buildings, since electricity is usually co-generated in biomass fuelled combined heat and power (CHP) plants. This gives it an important role in the mitigation of climate change. Swedish district heating companies are currently facing multiple challenges, and are in urgent need of new price models to increase transparency and maintain their competitiveness.

    This thesis describes a survey carried out to understand the structure of the present price models and subsequently proposes and compares two restructured price models with the most commonly used price model. This work also investigates the impact of restructured price models on users who would encounter a significant cost increase if the restructured price models were to be introduced. The district heating costs of different price models are compared with three alternative technical solutions.

    The results show that price models based on the consumption pattern of users can reflect district heating companies’ cost structure. Meanwhile, adopting a pricing strategy based on users’ consumption patterns increased the incentives to reduce the peak load.

    Consequently, users with high load factor (flat consecutive load curve) were able to reduce costs whereas users with low load factor (steep consecutive load curve) faced possible cost increases, when the load demand cost was changed to daily or hourly peak demand based methods. Further, the most economically preferable option for the invested district heating user was to combine district heating with direct electrical heating or with a ground source heat pump.

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  • 5.
    Song, Jingjing
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Cost comparison between district heating and alternatives during the price model restructuring process2017In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 105, p. 3922-3927Article in journal (Refereed)
    Abstract [en]

    District heating (DH) has been considered as a resource- and cost-efficient way of supplying heat and a promising method to mitigate climate change, yet it also facing growing competition from alternative technical solutions, such as heat pumps. Many DH companies are under price model restructuring process to enhance their competitiveness. This study investigated the competitiveness of DH among users which would encounter significant cost increase during the price model restructuring process through comparing the cost of different DH price models with three alternative technical solutions. The result shows that for the invested DH user, instead of DH, the most economic preferable choice is to install ground source heat pump combining with direct electrical heating.

  • 6.
    Song, Jingjing
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    District heating cost fluctuation caused by price model shift2017In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 194, p. 715-724Article in journal (Refereed)
    Abstract [en]

    District heating companies are facing multiple challenges nowadays, including increased investment and maintenance cost and critique from customers regarding opaque price model. Hence there is an urgent need to develop new price models. In this paper, a survey was carried out and identified four basic components in the price model. Three price models that represent the current situation and future trend have been extracted from the survey as well. Based on those price models, investigation was performed to study the impacts of different components in price models on customers’ cost. The result shows that customers with flatter consumption profiles can benefit from the price model that has a higher share of load demand component and use consumers’ real-time consumption data for charging. On the contrary, when a price model that has a higher share of energy component is adopted, customers with flatter consumption profiles may experience an increase in the cost.  

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  • 7.
    Song, Jingjing
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Effectiveness of introducing heat storage to repress cost increase2019Conference paper (Refereed)
    Abstract [en]

    District heating companies have been adapting their price models to reflect the changes in production cost caused by penetration of renewable fuels, and promote the applications of energy conservation measures that benefit the system efficiency. One of the approaches is to introduce a peak demand component in the price model, which has been proved to be effective to benefit users with lower peak demand. Whereas, this approach also significantly increase the cost for users with high peak demand. One of the measures that could help with high peak demand is installing energy storage on the demand side. In order to understand how the energy storage could change the users’ cost and help DH users to make informed decision, this study analyses the economic benefits of demand-side heat storage, namely if installing low-investment, low-tech, short-term hot-water storage on demand side could effectively repress the cost increase caused by new price models. Five types of building are considered here: multifamily house, commercial building, hospital and social services, industrial building, and office and school. One user of each type, whose costs increased the most during the price model transition process have been included. The result shows that heat storage could efficiently repress the cost increase, and all the investments will be paid back within 3 years, which means introducing heat storage is an efficient measure for cost saving under the circumstances.

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  • 8.
    Song, Jingjing
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Karlsson, Björn
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Price models of district heating in Sweden2016In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 88, p. 100-105Article in journal (Refereed)
    Abstract [en]

    Traditional pricing scheme of district heating is based on previous experience of system operation. This strategy does not work well under the circumstances of decreasing demand and shifting consumption pattern. Therefore new pricing strategies are needed. To have a comprehensive view on existing price models in Sweden, a price model survey was carried out among all members of the district heating quality system REKO. Four basic price components and multiple variants of them are detected in the survey. The result also shows that most of the district heating companies still use traditional methods and do not consider their customers’ consumption pattern while charging them.

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1 - 8 of 8
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