Sensitivity-based chance-constrained Generation Expansion Planning

• We formulate a Generation Expansion Planning problem using joint chance-constrained programming.
• We propose algorithms that incorporate sensitivity.
• The sensitivity makes it possible to distinguish the contribution of each bus to the system reliability.
• The use of sensitivity ensures that uncertain loads are correctly estimated.
• The results using the new algorithms are compared with those of previous algorithms for this problem that also use chance constraints.

A Generation Expansion Planning problem with load uncertainty is formulated based on joint chance-constrained programming (CCP) and is solved by incorporating sensitivity into iterative algorithms. These algorithms exploit the characteristics of the system and its response to load variations. Sensitivities help to classify buses according to stress level, and sensitivity-based iterative algorithms distinguish each bus based on its contribution to the overall system reliability. The use of sensitivity overcomes some of the mathematical obstacles to solving joint CCP problems and, in addition, leads to optimal expansion solutions because uncertain loads are correctly estimated. The IEEE 30- and 118-bus test systems are used to demonstrate the proposed algorithms, and the results of these algorithms are compared with those of other algorithms for solving the joint CCP problem.