Ampacity Monitoring Using Probabilistic Temperature Risk Models

The patent transforms the deterministic calculation approach into a probabilistic one by changing the nature of parameters from fixed values to probability distributions. The ampacity is no longer a single deterministic value but a probabilistic estimate that accounts for the statistical variability of meteorological parameters, thereby improving precision while maintaining computational feasibility through iterative optimization.

The patent implements an iterative feedback mechanism where the ampacity calculation is continuously refined by comparing the probability of exceeding distribution temperature against a target probability. The monitoring device adjusts the ampacity estimate based on feedback from the probabilistic model, progressively improving the precision of the estimation until convergence is achieved.

The patent replaces the static, a priori selection of unfavorable meteorological parameters with a dynamic probabilistic model that continuously evaluates the likelihood of temperature exceedance. The system adaptively determines ampacity based on the probabilistic distribution of meteorological parameters rather than relying on fixed worst-case scenarios, thereby improving reliability while managing complexity through iterative computation.

The patent uses simplified probabilistic models and iterative calculations that can be computed efficiently without requiring complex real-time sensor systems. The approach replaces expensive, complex real-time monitoring infrastructure with computationally inexpensive probabilistic assessments that provide reliable risk control through statistical analysis rather than continuous physical measurement.

The patent replaces the mechanical sensor-based real-time monitoring system with a computational probabilistic model. Instead of using physical sensors to continuously measure meteorological parameters and process the data in real-time, the system uses mathematical probability distributions and iterative calculations to estimate instantaneous ampacity, thereby maintaining precision while dramatically reducing device complexity and economic cost.

The patent creates a computational model that replicates the behavior of complex sensor-based systems without requiring the actual sensors. The probabilistic model copies the essential relationships between meteorological parameters and conductor temperature through mathematical formulations, providing accurate ampacity estimates without the need for expensive real-time measurement infrastructure.