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This study presents a risk‐assessment approach to the reactive power planning problem. Chance‐constrained programming is used to model the random equivalent availability of existing reactive power sources for a given confidence level. Load shedding because of random equivalent availability of those reactive power sources is implemented through conditional‐value‐at‐risk. Tap settings of under‐load tap‐changing transformers are considered as integer variables. Active and reactive demands are considered as probability distribution functions. The proposed mathematical formulation is a two‐stage stochastic, multi‐period mixed‐integer convex model. The tradeoff between risk mitigation and investment cost minimisation is analysed. The proposed methodology is applied to the CIGRE‐32 electric power system, using the optimisation solver CPLEX in AMPL. [ABSTRACT FROM AUTHOR]