A graph-theory-based dynamic programming planning method for distributed energy system planning: Campus area as a case study

Yan Ding, Qiaochu Wang, Zhe Tian, Yacong Lyu, Feng Li, Zhe Yan and Xi Xia

Applied Energy, 2023, vol. 329, issue C, No S030626192201515X

Abstract: Distributed energy systems are widely used in current regional energy planning because of their flexibility in terms of energy supply. However, the differentiated demand for various building loads increases the uncertainty of the energy supply. To reduce load fluctuation and hydraulic imbalance, a dynamic programming method based on graph theory was proposed in this study for energy station site selection and pipeline network layout deployment. The kernel density method was applied to distribute the regional building load for the site selection of energy stations. With the minimum load fluctuation rate as the goal, a 0–1 dynamic programming method was proposed to optimize the energy supply range of the energy station. Based on graph theory, an improved Prim algorithm was developed to determine the pipeline network layout. Taking a campus area as a case study, the proposed planning method was shown to reduce the initial investment, annual operating cost, and equivalent annual cost by 1.23%, 6.52%, and 5.04%, respectively. The optimized planning scheme not only balanced the load fluctuation in each energy station but also reduced the total pressure loss of the pipeline network by 19.86%.

Keywords: Distributed energy system; Energy station site selection; Pipeline network layout deployment; Graph theory; Dynamic programming (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030626192201515X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:329:y:2023:i:c:s030626192201515x

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2022.120258

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().