A validated grid data pipeline plus a fairness-aware optimal power flow that quantifies the cost of spatially fair PV hosting capacity.
Measurement-Based Line-Impedance Estimation in the Absence of Phasor Measurement Units
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abstract
This paper proposes and compares experimentally several methods to estimate the series resistance and reactance (i.e., the transversal components of the $\pi$-model of a line) of low-voltage lines in distribution grids. It first shows that if phasor measurements are available and the grid nodal voltages and power injections are known, the problem can be formulated and solved as a conventional load flow with properly adjusted unknowns. To solve this problem, we propose an analytical derivation of the Jacobian matrix. If only RMS values are available, such as from smart meters, integrating information from multiple intervals becomes necessary, ultimately opening to least-squares estimations, widely adopted in the literature. In this context, applying the proposed Jacobian contributes to accelerating the problem resolution of existing algorithms. The methods are compared in terms of estimation performance and convergence by using measurements from an experimental distribution grid interfacing real-world components and with realistic size implemented at the Gridlab at HES-SO Valais.
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Large-Scale Processing and Validation of Grid Data for Assessing the Fair Spatial Distribution of PV Hosting Capacity
A validated grid data pipeline plus a fairness-aware optimal power flow that quantifies the cost of spatially fair PV hosting capacity.