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.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)