6533b82ffe1ef96bd1294628

RESEARCH PRODUCT

District heating networks: enhancement of the efficiency

Girts KarnitisUgis SarmaJānis ZutersEdvins Karnitis

subject

020209 energynetwork design02 engineering and technology7. Clean energyAutomotive engineeringReduction (complexity)JEL: C - Mathematical and Quantitative Methods/C.C4 - Econometric and Statistical Methods: Special Topics/C.C4.C45 - Neural Networks and Related Topicsbenchmarking methodologies11. Sustainability0202 electrical engineering electronic engineering information engineeringdistrict heatingbusiness.industry020208 electrical & electronic engineeringdata miningBenchmarkingJEL: O - Economic Development Innovation Technological Change and Growth/O.O1 - Economic Development/O.O1.O13 - Agriculture • Natural Resources • Energy • Environment • Other Primary Products[SHS.ECO]Humanities and Social Sciences/Economics and FinanceNetwork planning and designVariable (computer science)Transmission (telecommunications)13. Climate actionHeat generationKey (cryptography)Environmental sciencebusinessJEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C24 - Truncated and Censored Models • Switching Regression Models • Threshold Regression ModelsThermal energy

description

International audience; During the decades the district heating's (DH) advantages (more cost-efficient heat generation and reduced air pollution) overcompensated the additional costs of transmission and distribution of the centrally produced thermal energy to consumers. Rapid increase in the efficiency of low-power heaters, development of separated low heat density areas in cities reduce the competitiveness of the large centralized DH systems in comparison with the distributed cluster-size networks and even local heating. Reduction of transmission costs, enhancement of the network efficiency by optimization of the design of the DH networks become a critical issue. The methodology for determination of the key drivers of the cost-efficiency of the DH networks to implement the most efficient (cost-minimal) thermal energy transmission was developed in this study. An inductive benchmarking modelling was applied; the general causal regularity is based on the observations of specific cases, thus determining the relationships between the network's design and thermal indicators as predictors and transmission costs as the target variable. The key drivers of the network efficiency were disclosed-the network length and the largest inner diameter of the pipes. The methodology is applicable for use by municipalities and heat providers for the heating planning of the new housing developments as well as renovation and/or expansion of the existing DH networks.

yearjournalcountryeditionlanguage
2019-09-30Insights into Regional Development
https://doi.org/10.9770/ird.2019.1.3(2)