Probabilistic Emergency Demand Response Planning Considering Overhead Lines Time Varying Thermal Ratings for Reliability Enhancements

Abstract

Increasing operational flexibility in the face of uncertainties is an everlasting challenge for existing power networks, especially with rapid demand growth and high penetration of renewable energy resources (RES). This study proposes an innovative power network reliability evaluation framework that integrates a pre-defined demand response scheme employed under emergency conditions. This integration considers network uncertainties within a probabilistic approach to identify the operator's emergency demand response (EDR) contractual power participation and duration participation requirements. It implements an optimization technique to minimize the total costs from production, interruption, and EDR incentives, aiming to define the optimal EDR power reductions by considering customers' expected availability. The framework deploys an additional sequential Monte Carlo simulation, considering customers' load reduction availability and restoration duration constraints, as well as network topology, to design both their reduction and restoration schemes for improving network reliability. In addition, overhead lines (OHLs) are modeled by considering time-varying thermal ratings (TVTR) to increase network flexibility and address any demand response uncertainties. A set of case studies was performed by simulating realistic operating conditions of the proposed EDR model on extended versions of IEEE RTS79. The effects on the reliability performance indicate a significant reduction of approximately 35 % in the expected energy not supplied and interruption costs.