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Journal Articles IEEE Transactions on Power Systems Year : 2024

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

Abstract

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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hal-04584290 , version 1 (23-05-2024)

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Juan J Cuenca, Marta Vanin, Md. Umar Hashmi, Arpan Koirala, Hakan Ergun, et al.. Event-Informed Identification and Allocation of Distribution Network Planning Candidates With Influence Scores and Binary Linear Programming. IEEE Transactions on Power Systems, 2024, pp.1-12. ⟨10.1109/TPWRS.2024.3404115⟩. ⟨hal-04584290⟩
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