Decision support tool for the development of power distribution networks based on AI planning

Sandra Castellanos; Marie-Cécile Alvarez-Herault; Philippe Lalanda

doi:10.1049/icp.2023.0759

Decision support tool for the development of power distribution networks based on AI planning

Sandra Castellanos, Marie-Cécile Alvarez-Herault, Philippe Lalanda

Grenoble Alps University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Long-term planning of interconnected electrical distribution networks consists in imagining the evolution of the existing network towards a target network, respecting the objectives and constraints set by the DSO, according to national and local energy evolution scenarios and with a time horizon of several decades. At present, there is no tool that can automatically and optimally propose target networks, as well as the annual intermediate networks that would allow reaching them. Automated planning (AI planning), a sub-field of Artificial Intelligence, is a model-based approach to action selection. The objective of this paper is a first attempt of a decision support tool for DSOs, based on AI planning and electrical computations, to help them finding the aforementioned intermediate networks.

Original language	English
Title of host publication	27th International Conference on Electricity Distribution (CIRED 2023)
Publisher	IEEE
Number of pages	5
ISBN (Electronic)	9781839538551
DOIs	https://doi.org/10.1049/icp.2023.0759
Publication status	Published - 29 Sept 2023
Externally published	Yes
Event	27th International Conference on Electricity Distribution - Rome, Italy Duration: 12 Jun 2023 → 15 Jun 2023 https://web.archive.org/web/20230607231522/https://www.cired2023.org/

Conference

Conference	27th International Conference on Electricity Distribution
Abbreviated title	CIRED 2023
Country/Territory	Italy
City	Rome
Period	12/06/23 → 15/06/23
Internet address	https://web.archive.org/web/20230607231522/https://www.cired2023.org/

Access to Document

10.1049/icp.2023.0759Licence: Unspecified

Cite this

@inproceedings{a004222c5f394fa5a7ecc78bd0de6b9a,

title = "Decision support tool for the development of power distribution networks based on AI planning",

abstract = "Long-term planning of interconnected electrical distribution networks consists in imagining the evolution of the existing network towards a target network, respecting the objectives and constraints set by the DSO, according to national and local energy evolution scenarios and with a time horizon of several decades. At present, there is no tool that can automatically and optimally propose target networks, as well as the annual intermediate networks that would allow reaching them. Automated planning (AI planning), a sub-field of Artificial Intelligence, is a model-based approach to action selection. The objective of this paper is a first attempt of a decision support tool for DSOs, based on AI planning and electrical computations, to help them finding the aforementioned intermediate networks.",

keywords = "Decision Support, Distribution Network, Distribution System Operator, Intermediate Network, Power System, Network Topology, Model Domain, Problem Instances, Target Network, Economic Constraints, Planning Model, Technical Constraints, Open Lines, Planning Algorithm, Dynamic Domain, Topological Constraints, Main Feeding",

author = "Sandra Castellanos and Marie-C{\'e}cile Alvarez-Herault and Philippe Lalanda",

year = "2023",

month = sep,

day = "29",

doi = "10.1049/icp.2023.0759",

language = "English",

booktitle = "27th International Conference on Electricity Distribution (CIRED 2023)",

publisher = "IEEE",

address = "United States",

note = "27th International Conference on Electricity Distribution, CIRED 2023 ; Conference date: 12-06-2023 Through 15-06-2023",

url = "https://web.archive.org/web/20230607231522/https://www.cired2023.org/",

}

TY - GEN

T1 - Decision support tool for the development of power distribution networks based on AI planning

AU - Castellanos, Sandra

AU - Alvarez-Herault, Marie-Cécile

AU - Lalanda, Philippe

PY - 2023/9/29

Y1 - 2023/9/29

N2 - Long-term planning of interconnected electrical distribution networks consists in imagining the evolution of the existing network towards a target network, respecting the objectives and constraints set by the DSO, according to national and local energy evolution scenarios and with a time horizon of several decades. At present, there is no tool that can automatically and optimally propose target networks, as well as the annual intermediate networks that would allow reaching them. Automated planning (AI planning), a sub-field of Artificial Intelligence, is a model-based approach to action selection. The objective of this paper is a first attempt of a decision support tool for DSOs, based on AI planning and electrical computations, to help them finding the aforementioned intermediate networks.

AB - Long-term planning of interconnected electrical distribution networks consists in imagining the evolution of the existing network towards a target network, respecting the objectives and constraints set by the DSO, according to national and local energy evolution scenarios and with a time horizon of several decades. At present, there is no tool that can automatically and optimally propose target networks, as well as the annual intermediate networks that would allow reaching them. Automated planning (AI planning), a sub-field of Artificial Intelligence, is a model-based approach to action selection. The objective of this paper is a first attempt of a decision support tool for DSOs, based on AI planning and electrical computations, to help them finding the aforementioned intermediate networks.

KW - Decision Support

KW - Distribution Network

KW - Distribution System Operator

KW - Intermediate Network

KW - Power System

KW - Network Topology

KW - Model Domain

KW - Problem Instances

KW - Target Network

KW - Economic Constraints

KW - Planning Model

KW - Technical Constraints

KW - Open Lines

KW - Planning Algorithm

KW - Dynamic Domain

KW - Topological Constraints

KW - Main Feeding

UR - https://www.scopus.com/pages/publications/85181539349

U2 - 10.1049/icp.2023.0759

DO - 10.1049/icp.2023.0759

M3 - Conference contribution

BT - 27th International Conference on Electricity Distribution (CIRED 2023)

PB - IEEE

T2 - 27th International Conference on Electricity Distribution

Y2 - 12 June 2023 through 15 June 2023

ER -

Decision support tool for the development of power distribution networks based on AI planning

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this