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Li, H., Song, J., Sun, Q., Wallin, F. & Zhang, Q. (2019). A dynamic price model based on levelized cost for district heating. Energy, Ecology and Environment, 4(1), 15-25
Åpne denne publikasjonen i ny fane eller vindu >>A dynamic price model based on levelized cost for district heating
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2019 (engelsk)Inngår i: Energy, Ecology and Environment, ISSN 2363-7692, Vol. 4, nr 1, s. 15-25Artikkel i tidsskrift (Fagfellevurdert) Published
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.

sted, utgiver, år, opplag, sider
Joint Center on Global Change and Earth System Science of the University of Maryland and Beijing Normal University, 2019
Emneord
District heating, Dynamic heat price, Heat demand, Levelized cost of heat, Price model
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-42917 (URN)10.1007/s40974-019-00109-6 (DOI)2-s2.0-85062437670 (Scopus ID)
Tilgjengelig fra: 2019-03-19 Laget: 2019-03-19 Sist oppdatert: 2019-08-13bibliografisk kontrollert
Xi, X., Li, H., Wallin, F., Avelin, A., Yang, X. & Yu, Z. (2019). Air pollution related externality of district heating - A case study of Changping, Beijing. In: Energy Procedia: . Paper presented at 10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China (pp. 4323-4330). Elsevier Ltd
Åpne denne publikasjonen i ny fane eller vindu >>Air pollution related externality of district heating - A case study of Changping, Beijing
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2019 (engelsk)Inngår i: Energy Procedia, Elsevier Ltd , 2019, s. 4323-4330Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Air pollution, caused by the use of fossil fuel, has been an environmental plague in China. It has a strong negative impact on human health. Since the costs of damage to health are not born by the pollution producers, these costs translate to social externality. Policies have an important role in optimizing resource allocation, such as penalizing the pollutant producers and incentivizing clean energy development. Among others, replacing coal with natural gas for heating represents an important example of air quality improvement measures. This paper presents a study that evaluates the health impacts from air pollution and the external cost of the "Coal-To-Gas" policy in district heating using Changping District (Beijing, China) as an example. Four scenarios were considered based on the historical and standard PM2.5 concentration. Results show that PM2.5 is responsible for causing an increase of 40% premature deaths in 2015 and that the monetary value of damage to health is higher than 1.2 billion CNY. In 2016 and 2017, the reported air quality was better than that in 2015. As a result, 13.3% and 26% premature deaths caused by air pollution were avoided in 2016 and 2017 compared to 2015 respectively. If the PM2.5 concentration level were to be reduced to national standard, the number of premature deaths attributed to PM2.5 could further decrease to 47.7% compared to 2015. Overall, the Coal-To-Gas policy in district heating reduces 0.017%~0.45% of premature death caused by air pollution each year. Air pollution reduction policies, which are expected to improve air quality together in the future, and the specific policy of Coal-To-Gas in district heating, could make great contribution to reducing the premature death caused by environmental problem and need more attention from the government and the public.

sted, utgiver, år, opplag, sider
Elsevier Ltd, 2019
Emneord
Coal-To-Gas, District heating, Externality, Health effect, PM2.5
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-43140 (URN)10.1016/j.egypro.2019.01.789 (DOI)000471031704105 ()2-s2.0-85063905381 (Scopus ID)
Konferanse
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China
Tilgjengelig fra: 2019-04-18 Laget: 2019-04-18 Sist oppdatert: 2019-07-11bibliografisk kontrollert
Maher, A., Eskilsson, A. & Wallin, F. (2019). An open-source visualization platform for energy flows mapping and enhanced decision making. In: Energy Procedia: . Paper presented at 10th International Conference on Applied Energy, ICAE 2018, 22 August 2018 through 25 August 2018 (pp. 3208-3214). Elsevier Ltd, 158
Åpne denne publikasjonen i ny fane eller vindu >>An open-source visualization platform for energy flows mapping and enhanced decision making
2019 (engelsk)Inngår i: Energy Procedia, Elsevier Ltd , 2019, Vol. 158, s. 3208-3214Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Visualization of energy consumption within the built environment, both in the private and public sectors, can be a potent tool for increasing conservation behavior. For instance, dynamics visualization could add new knowledge to the end-users to have a better understanding of the energy flows, dynamic mapping of the energy usage in order to avoid misplacing effort and resources, e.g. when it comes to selection of heating systems, investing in energy efficiency measures and renewables as well as when stakeholders are planning for new area to be populated with either commercial or residential buildings. This paper introduces an open-source visualization platform allowing various energy flows mapping in both time and space of a sports facilities. It further includes advanced functionalities such as key performance indicators and integrated prediction models to assist the benchmarking and decision making processes.

sted, utgiver, år, opplag, sider
Elsevier Ltd, 2019
Emneord
Decision making, Energy mapping, Smart metering, Visualization, Benchmarking, Energy efficiency, Energy utilization, Flow visualization, Mapping, Built environment, Decision making process, Efficiency measure, Integrated prediction models, Key performance indicators, Residential building, Visualization platforms
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-43185 (URN)10.1016/j.egypro.2019.01.1006 (DOI)000471031703089 ()2-s2.0-85063900381 (Scopus ID)
Konferanse
10th International Conference on Applied Energy, ICAE 2018, 22 August 2018 through 25 August 2018
Tilgjengelig fra: 2019-04-25 Laget: 2019-04-25 Sist oppdatert: 2019-07-11bibliografisk kontrollert
Ma, Z., Xie, J., Li, H., Sun, Q., Wallin, F., Si, Z. & Guo, J. (2019). Deep Neural Network-based Impacts Analysis of Multimodal Factors on Heat Demand Prediction. IEEE Transactions on Big Data
Åpne denne publikasjonen i ny fane eller vindu >>Deep Neural Network-based Impacts Analysis of Multimodal Factors on Heat Demand Prediction
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2019 (engelsk)Inngår i: IEEE Transactions on Big Data, ISSN 2372-2096Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Prediction of heat demand using artificial neural networks has attracted enormous research attention. Weather conditions, such as direct solar irradiance and wind speed, have been identified as key parameters affecting heat demand. This paper employs an Elman neural network to investigate the impacts of direct solar irradiance and wind speed on the heat demand from the perspective of the entire district heating network. Results of the overall mean absolute percentage error (MAPE) show that direct solar irradiance and wind speed have quite similar impacts. However, the involvement of direct solar irradiance can clearly reduce the maximum absolute deviation when only involving direct solar irradiance and wind speed, respectively. In addition, the simultaneous involvement of both wind speed and direct solar irradiance does not show an obvious improvement of MAPE. Moreover, the prediction accuracy can also be affected by other factors like data discontinuity and outliers.

sted, utgiver, år, opplag, sider
IEEE, 2019
Emneord
District heating, deep learning, Elman neural network, heat demand, direct solar irradiance, wind speed
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-46991 (URN)10.1109/TBDATA.2019.2907127 (DOI)
Tilgjengelig fra: 2020-02-06 Laget: 2020-02-06 Sist oppdatert: 2020-02-06
Song, J., Wallin, F. & Li, H. (2019). Effectiveness of introducing heat storage to repress cost increase. In: : . Paper presented at 10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China (pp. 4344-4349). , 158
Åpne denne publikasjonen i ny fane eller vindu >>Effectiveness of introducing heat storage to repress cost increase
2019 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

Serie
Energy Procedia, ISSN 1876-6102
Emneord
District heating; price model trannsition; energy storage; peak shifting; optimization
HSV kategori
Forskningsprogram
energi- och miljöteknik
Identifikatorer
urn:nbn:se:mdh:diva-42248 (URN)10.1016/j.egypro.2019.01.786 (DOI)000471031704108 ()2-s2.0-85063890121 (Scopus ID)
Konferanse
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China
Tilgjengelig fra: 2018-12-31 Laget: 2018-12-31 Sist oppdatert: 2019-07-11bibliografisk kontrollert
Maher, A., Eskilsson, A. & Wallin, F. (2019). Energy flow mapping and key performance indicators for energy efficiency support: A case study a sports facility. In: Energy Procedia: . Paper presented at 10th International Conference on Applied Energy, ICAE 2018, 22 August 2018 through 25 August 2018 (pp. 4350-4356). Elsevier Ltd, 158
Åpne denne publikasjonen i ny fane eller vindu >>Energy flow mapping and key performance indicators for energy efficiency support: A case study a sports facility
2019 (engelsk)Inngår i: Energy Procedia, Elsevier Ltd , 2019, Vol. 158, s. 4350-4356Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

This paper aims to investigate the energy consumption in a sport facilities and elaborate a set of novel energy indicators to support decision making process. Sports facilities are complex systems having higher significant energy demand than other facilities for service and recreation. These facilities require massive demand of various energy (e.g. heat, cooling, electricity) to meet the requirement of different types of sports facilities leading to a high complexity to understand and describe such facility accurately. To tackle this problem, an energy flow mapping of different energy demand is developed to have more insights on the energy flow in both time and space domain within one of the biggest sports facilities in Sweden, Rocklunda arena. All the energy meters are virtually connected to design a comprehensive mapping of the energy streams. Then the data is processed and analyzed to elaborate a set of novel key performance indicators KPIs allowing a simplistic description of the different aspects of the system consumption profile and the related energy performance.

sted, utgiver, år, opplag, sider
Elsevier Ltd, 2019
Emneord
Energy flow mapping, Key Performance Indicators, Smart metering, Sports facility, Benchmarking, Decision making, Electric measuring instruments, Energy management, Energy utilization, Mapping, Recreation centers, Sports, Decision making process, Efficiency supports, Energy flow, Energy indicator, Energy performance, Sport facilities, Energy efficiency
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-43186 (URN)10.1016/j.egypro.2019.01.785 (DOI)000471031704109 ()2-s2.0-85063891899 (Scopus ID)
Konferanse
10th International Conference on Applied Energy, ICAE 2018, 22 August 2018 through 25 August 2018
Tilgjengelig fra: 2019-04-25 Laget: 2019-04-25 Sist oppdatert: 2019-07-11bibliografisk kontrollert
Bian, C., Li, H., Wallin, F., Avelin, A., Lin, L. & Yu, Z. (2019). Finding the optimal location for public charging stations - A GIS-based MILP approach. In: Energy Procedia: . Paper presented at 10th International Conference on Applied Energy, ICAE 2018, 22 August 2018 through 25 August 2018 (pp. 6582-6588). Elsevier Ltd, 158
Åpne denne publikasjonen i ny fane eller vindu >>Finding the optimal location for public charging stations - A GIS-based MILP approach
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2019 (engelsk)Inngår i: Energy Procedia, Elsevier Ltd , 2019, Vol. 158, s. 6582-6588Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Electric Vehicles (EVs) have achieved a significant development because of the continuous technology revolution and policy supports in recent years, which leads to a larger demand of charging stations. Strategies about how to find the optimal location for charging facilities are urgently needed in order to further assist the development of EVs. This paper focus on the return of investments on EV charging stations and proposes a Mixed Integer Linear Programming (MILP) model based on Geographic Information System (GIS) to identify the optimal location of charging stations in cities. Traffic flow data and land-use classifications are used as important inputs, and six important constraints are included in the MILP model with the objective function of maximizing the total profits of new charging stations. The effectiveness of the proposed method is then demonstrated by implementing a case study in Västerås, Sweden.

sted, utgiver, år, opplag, sider
Elsevier Ltd, 2019
Emneord
EV, GIS, MILP, Optimal location, Public charging startions, Charging (batteries), Economics, Integer programming, Investments, Land use, Location, Electric Vehicles (EVs), Landuse classifications, Mixed integer linear programming model, Optimal locations, Return of investments, Technology revolution, Geographic information systems
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-43192 (URN)10.1016/j.egypro.2019.01.071 (DOI)000471031706145 ()2-s2.0-85063879695 (Scopus ID)
Konferanse
10th International Conference on Applied Energy, ICAE 2018, 22 August 2018 through 25 August 2018
Tilgjengelig fra: 2019-04-25 Laget: 2019-04-25 Sist oppdatert: 2019-07-11bibliografisk kontrollert
Hennessy, J., Li, H., Wallin, F. & Thorin, E. (2019). Flexibility in thermal grids: A review of short-term storage in district heating distribution networks. In: Energy Procedia: . Paper presented at 10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China (pp. 2430-2434). Elsevier Ltd, 158
Åpne denne publikasjonen i ny fane eller vindu >>Flexibility in thermal grids: A review of short-term storage in district heating distribution networks
2019 (engelsk)Inngår i: Energy Procedia, Elsevier Ltd , 2019, Vol. 158, s. 2430-2434Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Future energy systems need to be more flexible. The use of cross-sector coupling in combination with thermal storage in thermal grids has been shown to provide such flexibility. The presented study reviews how short-term storage in district heating distribution networks is used or modelled for flexibility, what are the most important parameters, and where the knowledge gaps remain. The results show that the potential for flexibility from district heating has not been fully exploited. Sensible thermal storage tanks are 50-100 times cheaper than electrical storage and storage in the distribution network requires little additional investment in infrastructure. In some countries, the majority of district heating systems have sensible thermal storage tanks, with as much as 64 % of their capacity available for flexibility services. Initial results suggest that only smaller networks are prevented from using the distribution network for storage, but the impacts of this type of use on the physical components and the capacity limitations remain unclear and show a need for standardised methods for analysis. There is a growing interest, both in Europe and China, in the use of short-term storage in district heating to provide flexibility, particularly in the form of ancillary services to the electricity grid, but implementations of these techniques are rare. The presented study identifies a number of remaining knowledge gaps that should be addressed in order to harness available flexibility in district heating.

sted, utgiver, år, opplag, sider
Elsevier Ltd, 2019
Emneord
Curtailment, District heating and cooling, Flexibility, Renewable energy, Thermal grids, Thermal inertia, Thermal storage
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-43135 (URN)10.1016/j.egypro.2019.01.302 (DOI)000471031702121 ()2-s2.0-85063896688 (Scopus ID)
Konferanse
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China
Tilgjengelig fra: 2019-04-18 Laget: 2019-04-18 Sist oppdatert: 2019-07-11bibliografisk kontrollert
Wang, C., Du, Y., Li, H., Wallin, F. & Min, G. (2019). New methods for clustering district heating users based on consumption patterns. Applied Energy, 251, Article ID 113373.
Åpne denne publikasjonen i ny fane eller vindu >>New methods for clustering district heating users based on consumption patterns
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2019 (engelsk)Inngår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 251, artikkel-id 113373Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Understanding energy users’ consumption patterns benefits both utility companies and consumers as it can support improving energy management and usage strategies. The rapid deployment of smart metering facilities has enabled the analysis of consumption patterns based on high-precision real usage data. This paper investigates data-driven unsupervised learning techniques to partition district heating users into separate clusters such that users in the same cluster possess similar consumption pattern. Taking into account the characteristics of heat usage, three new approaches of extracting pattern features from consumption data are proposed. Clustering algorithms with these features are executed on a real-world district heating consumption dataset. The results can reveal typical daily consumption patterns when the consumption linearly related to ambient temperature is removed. Users with heat usages that are highly imbalanced within a certain period of time or are highly consistent with the utility heat production load can also be grouped together. Our methods can facilitate gaining better knowledge regarding the behaviors of district heating users and hence can potentially be used to formulate new pricing and energy reduction solutions.

sted, utgiver, år, opplag, sider
Elsevier Ltd, 2019
Emneord
District heating, Energy consumption pattern, Feature extraction, User clustering
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-43875 (URN)10.1016/j.apenergy.2019.113373 (DOI)000497966300083 ()2-s2.0-85066498359 (Scopus ID)
Tilgjengelig fra: 2019-06-11 Laget: 2019-06-11 Sist oppdatert: 2019-12-12bibliografisk kontrollert
Dong, S., Li, H., Wallin, F., Avelin, A., Zhang, Q. & Yu, Z. (2019). Volatility of electricity price in Denmark and Sweden. In: Yan, J Yang, HX Li, H Chen, X (Ed.), INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS: . Paper presented at 10th International Conference on Applied Energy (ICAE), AUG 22-25, 2018, Hong Kong, HONG KONG (pp. 4331-4337). ELSEVIER SCIENCE BV
Åpne denne publikasjonen i ny fane eller vindu >>Volatility of electricity price in Denmark and Sweden
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2019 (engelsk)Inngår i: INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS / [ed] Yan, J Yang, HX Li, H Chen, X, ELSEVIER SCIENCE BV , 2019, s. 4331-4337Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Under the pressure of global environmental climate change, all countries in the world are developing renewable energy such as hydropower, wind energy, and solar energy As a result, the electricity price varies in different patterns depending on the penetration of renewable energy. In this paper, a non-parametric model is employed to analyze the historical data of electricity spot price from Danish price areas of the Nord Pool (with high percentage of wind power), Swedish price areas of the Nord Pool (with high percentage of hydropower) and PJM market (with little renewable energy penetrated). The objective is to deeply understand the influence of renewable energies on electricity price volatility. It is found that electricity prices are more stable in Swedish price areas as hydropower is a more stable energy source. The electricity price in PJM market is also comparatively stable, only more volatile than Swedish market, as fossil fuels are dominant energy resources. For Danish price areas, the volatility of electricity prices is clearly affected by wind power, which is a highly intermittent energy resource.

sted, utgiver, år, opplag, sider
ELSEVIER SCIENCE BV, 2019
Serie
Energy Procedia, ISSN 1876-6102 ; 158
Emneord
volatility of elecctricity price, electricity spot price, penetration of renewable energy, electricity market
HSV kategori
Identifikatorer
urn:nbn:se:mdh:diva-44854 (URN)10.1016/j.egypro.2019.01.788 (DOI)000471031704106 ()
Konferanse
10th International Conference on Applied Energy (ICAE), AUG 22-25, 2018, Hong Kong, HONG KONG
Tilgjengelig fra: 2019-07-11 Laget: 2019-07-11 Sist oppdatert: 2019-07-11bibliografisk kontrollert
Organisasjoner
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0003-4589-7045