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Multi-period electricity distribution network investment planning under demand coincidence in the smart grid.

Authors :
Rüde, Lenard
Gust, Gunther
Neumann, Dirk
Source :
Annals of Operations Research. Aug2024, p1-24.
Publication Year :
2024

Abstract

In recent years, new smart technologies like electric vehicles and active demand management have been introduced to reduce carbon emissions in electricity distribution networks, resulting in altered electricity consumption patterns. However, the impact of the technologies on electricity consumption remains uncertain due to a lack of rigorous evaluation methods and planning techniques accounting for these changes. Addressing these gaps, this paper contributes three key elements to information systems literature. First, this paper presents a policy to plan multi-period electricity distribution networks that are able to take into account changing electricity consumption patterns. This paper uses a policy to determine the impact of new technologies on distribution network investments. Second, this paper determines the effect of network topologies on distribution network investments with altered consumption patterns. Third, this paper develops and solves a novel optimization problem that formalizes the task of long-term distribution network planning under variable consumption patterns. This work holds implications for distribution network management, policy, and research. It offers recommendations for integrating our policies into practical procedures, emphasizing the need for more rigorous planning incentives for policymakers. Furthermore, the large effect of altered consumption patterns shows that actions are needed to design policies that work towards lowering load coincidence. For researchers, the presented problem and solution methods are generalizable and can help researchers in other domains (e.g. parcel delivery, water distribution) to solve comparable planning problems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02545330
Database :
Academic Search Index
Journal :
Annals of Operations Research
Publication Type :
Academic Journal
Accession number :
178985843
Full Text :
https://doi.org/10.1007/s10479-024-06107-0