An Efficient Line Ratings Program With Probabilistic Considerations for Real Time Operations

Many utilities desire to widen their system operation margin through increasing transmission line loading while ensuring that the lines are not overloaded. It is impractical to monitor loading (via temperature) over the length of all transmission lines so many methods have been developed to estimate line temperatures. Estimate inaccuracies result from not knowing the weather conditions along all segments of the line; and from inaccuracies in empirical estimating equations. The statistical approach to safe line loading presented here associates confidence levels with maximum line temperatures for fixed, current and conversly associates confidence levels with currents for a safe line temperature. Steady state and transient operating conditions are considered. The methodology presented is useful and computationally efficient for automated power systems operations, as well as useful to design engineers.