A framework for heat energy community planning with a special focus on cost sharing

While electricity-based energy communities (ECs) have received significant scientific attention, heat-based ECs have not gotten the attention they deserve. This paper builds upon the hypothesis that ECs could be a lever to increase the adoption rates of district heating and thus contribute significantly to decarbonise the heating sector. In order to unleash this presumed potential and close a research gap, a conceptual planning framework is introduced, encompassing EC-tailored heat infrastructure planning and cost sharing mechanisms to distribute the financial burden between individual participants based on transparent criteria. For the efficient and EC-suitable planning of a district heating grid, a shortest path problem is solved using Dijkstra’s algorithm. To address the issue of distributing investment costs among EC participants, eight different cost sharing scenarios are developed. These distinguish between costs for heat generation devices and costs for the heating grid, the latter being further sub-categorised into grid lines on the properties of participating parties and common/third property. The developed framework is then applied to a case study of eight residential buildings and three heat generation sites in a city area. Thereby it is found that the cost variance between different cost sharing scenarios lies between 19.1% and 42.6%. From converting heat infrastructure costs per property to annuities for a time horizon of 30 years, it can be concluded that such investments could remain a significant hurdle for private building owners unless suitable investment incentives are proposed by policy decision makers.

Authors

Publication Details

Journal
Energy Strategy Reviews
Published
2024-10-18
DOI
https://doi.org/10.1016/j.esr.2024.101556
Citations
6
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
1.25

Funders

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article

A framework for heat energy community planning with a special focus on cost sharing

Bernadette Fina
6 citations
Energy Strategy Reviews
Integrated Energy Systems Optimization
1.25
article

A framework for heat energy community planning with a special focus on cost sharing

Bernadette Fina
article en
6 citations

Abstract

While electricity-based energy communities (ECs) have received significant scientific attention, heat-based ECs have not gotten the attention they deserve. This paper builds upon the hypothesis that ECs could be a lever to increase the adoption rates of district heating and thus contribute significantly to decarbonise the heating sector. In order to unleash this presumed potential and close a research gap, a conceptual planning framework is introduced, encompassing EC-tailored heat infrastructure planning and cost sharing mechanisms to distribute the financial burden between individual participants based on transparent criteria. For the efficient and EC-suitable planning of a district heating grid, a shortest path problem is solved using Dijkstra’s algorithm. To address the issue of distributing investment costs among EC participants, eight different cost sharing scenarios are developed. These distinguish between costs for heat generation devices and costs for the heating grid, the latter being further sub-categorised into grid lines on the properties of participating parties and common/third property. The developed framework is then applied to a case study of eight residential buildings and three heat generation sites in a city area. Thereby it is found that the cost variance between different cost sharing scenarios lies between 19.1% and 42.6%. From converting heat infrastructure costs per property to annuities for a time horizon of 30 years, it can be concluded that such investments could remain a significant hurdle for private building owners unless suitable investment incentives are proposed by policy decision makers.

Energy Strategy ReviewsVol. 56
Österreichische Forschungsförderungsgesellschaft
Openalex Percentile: Top 20%
Integrated Energy Systems Optimization
1.25
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