Event-Informed Identification and Allocation of Distribution Network Planning Candidates With Influence Scores and Binary Linear Programming

This article presents a novel numerical approach aimed at finding a distribution network expansion plan that prevents future congestion and voltage issues. Forecasted duration and intensity of thermal and voltage violation events are used to determine a pool of potential candidates for infrastructur...

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Published in:IEEE transactions on power systems Vol. 40; no. 1; pp. 492 - 504
Main Authors: Cuenca, Juan J., Vanin, Marta, Hashmi, Md. Umar, Koirala, Arpan, Ergun, Hakan, Hayes, Barry P.
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Subjects:
Algorithms
Battery energy systems
distribution network expansion planning
Distribution networks
Electric power
Energy storage
Engineering Sciences
flexibility
Investment
Linear programming
Planning
power distribution lines
power distribution planning
Regulators
Voltage
Voltage control
Voltage regulators
flexibility
power distribution lines
distribution network expansion planning
Battery energy systems
power distribution planning
ISSN:0885-8950, 1558-0679
Online Access:Get full text
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Summary:This article presents a novel numerical approach aimed at finding a distribution network expansion plan that prevents future congestion and voltage issues. Forecasted duration and intensity of thermal and voltage violation events are used to determine a pool of potential candidates for infrastructure (i.e., line/cable) upgrade, voltage regulator, and energy storage system installations. This is complemented with an algorithm to obtain the minimum-cost list of these candidates that solves all constraint violation events using binary linear programming. This approach is validated using the modified IEEE 33-bus network and a real 1171-bus feeder in the West of Ireland through numerous high-resolution quasi-static time series simulations. Three pools of candidates and three cost projections were considered to explore the method's sensitivity to different scenarios. Results show that the proposed methodology is a versatile tool for designers, planners and policymakers. The methodology can ensure that the investment plan solves all forecasted violation events. Nevertheless, we show that accepting a marginal degree of violations may be admissible and would significantly reduce investment costs.
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ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2024.3404115