scholarly journals Methodology for Evaluation of District Heating Network Efficiency

2020 ◽  
Vol 186 ◽  
pp. 01006
Author(s):  
Daniel Anthony Howard ◽  
Konstantin Filonenko ◽  
Frederik Stjernholm Busk ◽  
Christian Veje
Keyword(s):  
Large Scale ◽  
Network Performance ◽  
District Heating ◽  
Performance Estimation ◽  
Network Efficiency ◽  
Contributing Factors ◽  
Transmission Coefficients ◽  
Operational Temperature ◽  
Definition Of ◽  
Heating Networks

The definition of overall district heating network performance indicators is under-investigated in the literature. This study reviews existing methods of performance estimation and develops a convenient methodology for an array of district heating networks applied to a Danish case study. Performances of the networks with state-of-art pipe transmission coefficients are compared to older traditional pipes using an effective average approach. The reported efficiencies and analysis of contributing factors show, that a single parameter is not sufficient to compare large-scale district heating systems and a multiparametric analysis must be employed. The effective average total heat transmission coefficient is evaluated based on the Technical Evaluation Factor and a multivariate regression is performed on typical sets of network parameters: pipe type, pipe series, pipe age, and operational temperature. The developed methodology is applied to testing an array of geographically independent district heating networks, pointing to possible performance bottlenecks, and discussing potential remedies.

scholarly journals Estimation of load curves for large-scale district heating networks

2020 ◽  
Vol 588 ◽  
pp. 052032
Author(s):  
Kai Nino Streicher ◽  
Stefan Schneider ◽  
Martin K. Patel
Keyword(s):  
Large Scale ◽  
District Heating ◽  
Heating Networks

scholarly journals Methodology for the Improvement of Large District Heating Networks

2012 ◽  
Vol 10 (1) ◽  
pp. 39-45 ◽  
Author(s):  
Anna Volkova ◽  
Vladislav Mashatin ◽  
Aleksander Hlebnikov ◽  
Andres Siirde
Keyword(s):  
Heat Generation ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
District Heating ◽  
Heating System ◽  
District Heating System ◽  
Effective Operation ◽  
The Cost ◽  
Heating Networks

Abstract The purpose of this paper is to offer a methodology for the evaluation of large district heating networks. The methodology includes an analysis of heat generation and distribution based on the models created in the TERMIS and EnergyPro software Data from the large-scale Tallinn district heating system was used for the approbation of the proposed methodology as a basis of the case study. The effective operation of the district heating system, both at the stage of heat generation and heat distribution, can reduce the cost of heat supplied to the consumers. It can become an important factor for increasing the number of district heating consumers and demand for the heat load, which in turn will allow installing new cogeneration plants, using renewable energy sources and heat pump technologies

scholarly journals A new combined clustering method to Analyse the potential of district heating networks at large-scale

Energy ◽  
2018 ◽  
Vol 156 ◽  
pp. 73-83 ◽  
Author(s):  
Julien F. Marquant ◽  
L. Andrew Bollinger ◽  
Ralph Evins ◽  
Jan Carmeliet
Keyword(s):  
Large Scale ◽  
District Heating ◽  
Clustering Method ◽  
Heating Networks

scholarly journals Towards a RINA-Based Architecture for Performance Management of Large-Scale Distributed Systems

Computers ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 53 ◽  
Author(s):  
Peter Thompson ◽  
Neil Davies
Keyword(s):  
Distributed Systems ◽  
Performance Management ◽  
Large Scale ◽  
Network Performance ◽  
Modern Society ◽  
Performance Management System ◽  
Reliable Performance ◽  
Critical Traffic ◽  
Definition Of ◽  
Time Critical

Modern society is increasingly dependent on reliable performance of distributed systems. In this paper, we provide a precise definition of performance using the concept of quality attenuation; discuss its properties, measurement and decomposition; identify sources of such attenuation; outline methods of managing performance hazards automatically using the capabilities of the Recursive InterNetworking Architecture (RINA); demonstrate procedures for aggregating both application demands and network performance to achieve scalability; discuss dealing with bursty and time-critical traffic; propose metrics to assess the effectiveness of a performance management system; and outline an architecture for performance management.

The role and costs of large-scale heat pumps in decarbonising existing district heating networks – A case study for the city of Herten in Germany

Energy ◽  
2019 ◽  
Vol 180 ◽  
pp. 918-933 ◽  
Author(s):  
Eftim Popovski ◽  
Ali Aydemir ◽  
Tobias Fleiter ◽  
Daniel Bellstädt ◽  
Richard Büchele ◽  
...  
Keyword(s):  
Large Scale ◽  
District Heating ◽  
Heat Pumps ◽  
The City ◽  
Heating Networks

Research and Application of Importance Degree Evaluation Method of Complex Network Cascade Connection Node Based on Load Redistribution

2014 ◽  
Vol 998-999 ◽  
pp. 1174-1177
Author(s):  
Yun Peng Zhang
Keyword(s):  
Complex Network ◽  
Network Performance ◽  
Evaluation Method ◽  
Cascading Failure ◽  
Network Efficiency ◽  
Node Importance ◽  
Critical Nodes ◽  
Cascade Connection ◽  
The One ◽  
Definition Of

This paper presented a model with overload function for cascading failure. The main differences with respect to previous models are as follows: overload function is defined for each node, according to the value of overload function, one node has th ree states: success, overload, failure. After the load decreases, an overloaded node can be success again. The evolution of topology is replaced by the evolution of value of overload function during the process of cascading failure. It’s needless to delete the failure nodes and its edges, the load will avoid the failure nodes automat ically and the decrease of network performance will be reflected by network efficiency. An evaluation method of node importance considering cascading failure is proposed, and its algorithm is presented. A new definition of node importance is proposed. The most important node is the one who see failure results in the largest decrease of networks efficiency at the end of cascading. The evaluation method can help us to find some potential critical nodes which are sensitive to the efficiency of networks but not so important intuitively. Final example verifies its efficiency and feasibility.

scholarly journals Reliability and Component Importance in Networks Subject to Spatially Distributed Hazards Followed by Cascading Failures

2017 ◽  
Vol 3 (2) ◽  
Author(s):  
Anke Scherb ◽  
Luca Garrè ◽  
Daniel Straub
Keyword(s):  
Random Field ◽  
Spatial Correlation ◽  
System Reliability ◽  
Large Scale ◽  
Network Performance ◽  
Network Reliability ◽  
Cascading Failures ◽  
Network Efficiency ◽  
Component Importance ◽  
Spatially Distributed

We investigate reliability and component importance in spatially distributed infrastructure networks subject to hazards characterized by large-scale spatial dependencies. In particular, we consider a selected IEEE benchmark power transmission system. A generic hazard model is formulated through a random field with continuously scalable spatial autocorrelation to study extrinsic common-cause-failure events such as storms or earthquakes. Network performance is described by a topological model, which accounts for cascading failures due to load redistribution after initial triggering events. Network reliability is then quantified in terms of the decrease in network efficiency and number of lost lines. Selected importance measures are calculated to rank single components according to their influence on the overall system reliability. This enables the identification of network components that have the strongest effect on system reliability. We thereby propose to distinguish component importance related to initial (triggering) failures and component importance related to cascading failures. Numerical investigations are performed for varying correlation lengths of the random field to represent different hazard characteristics. Results indicate that the spatial correlation has a discernible influence on the system reliability and component importance measures, while the component rankings are only mildly affected by the spatial correlation. We also find that the proposed component importance measures provide an efficient basis for planning network improvements.

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