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A probabilistic methodology for optimal scheduling of load reductions recoveries in a day-ahead planning of transmission networks is proposed in the paper. The methodology recognizes several types of uncertainties. and finds optimal demand response scheduling using the network security and customer economics criteria. Impacts of wind generation and real-time thermal ratings of overhead lines are also studied. The developed case studies have demonstrated that the value of optimal demand scheduling combined with real-time thermal ratings can be significant when using nodal marginal prices compared to using the hourly loads only. In particular. both reliability and financial metrics can be improved by a factor of around 66% for expected energy not served and around 5% for value at risk for costs of demand. Improvements in other reliability indicators and expected generation costs were also observed. Nonetheless. the selection of the reliability indicator to base the operational decisions on demand scheduling can be of highest importance. having multiple indices can therefore help system operators to make more informed decisions on ‘best’ demand response practice. As a final comment. the consistent use of a probabilistic approach to model various network uncertainties and variability of nodal marginal prices provides a superior analysis compared to traditional analytical techniques. Future work considers inclusion of optimal energy storage scheduling to increase system reliability. Combined impact of energy storage. demand response and wind generation will be studied in greater detail.
