Robust voltage regulation for active distribution networks with imperfect observability

Mora, Edwin; Steinke, Florian

doi:10.1109/powertech46648.2021.9495084

Cited by 2 publications

(1 citation statement)

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“…VRs can alleviate voltage events up to the range of the regulation equipment (typically ±10% of the nominal voltage) on the subset of nodes N ν part of its area of influence. These regulators must have increased observability (i.e., the possibility to sense voltage drop/increase in the primary and secondary as discussed in [41]). Together, these IU and VR represent the candidates for the traditional expansion plan calculated by system operators, responding to forecasted issues.…”

Section: B Numerical Approachmentioning

confidence: 99%

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

Cuenca,

Vanin,

Hashmi

et al. 2024

IEEE Trans. Power Syst.

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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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Section: B Numerical Approachmentioning

confidence: 99%