The present work concerns a systematic investigation of power sector portfolios through discrete scenarios of electricity and CO(2) allowance prices. The analysis is performed for different prices, from regulated to completely deregulated markets, thus representing different electricity market policies. The modelling approach is based on a stochastic programming algorithm without recourse, used for the optimisation of power sector economics under multiple uncertainties. A sequential quadratic programming routine is applied for the entire investigation period whilst the time-dependent objective function is subject to various social and production constraints, usually confronted in power sectors. The analysis indicated the optimal capacity additions that should be annually ordered from each competitive technology in order to substantially improve both the economy and the sustainability of the system. It is confirmed that higher electricity prices lead to higher financial yields of power production, irrespective of the CO(2) allowance price level. Moreover, by following the proposed licensing planning, a medium-term reduction of CO(2) emissions per MW h by 30% might be possible. Interestingly, the combination of electricity prices subsidisation with high CO(2) allowance prices may provide favourable conditions for investors willing to engage on renewable energy markets. (C) 2011 Elsevier Ltd. All rights reserved.