  Integration of smart grid technologies in distribution systems, particularly
behind-the-meter initiatives, has a direct impact on transmission network
planning. This paper develops a coordinated expansion planning of transmission
and active distribution systems via a stochastic multistage mathematical
programming model. In the transmission level, in addition to lines, sitting and
sizing of utility-scale battery energy storage systems and wind power plants
under renewable portfolio standard policy are planned. Switchable feeders and
distributed generations are decision variables in the distribution level while
the impact of demand response programs as a sort of behind-the-meter
technologies is accommodated as well. Expansion of electric vehicle taxi
charging stations is included as a feasible option in both transmission and
distribution levels. In order to deal with short-term uncertainty of load
demand, renewable energy sources output power, and the charging pattern of
electric vehicle taxis in each station, a chronological time-period clustering
algorithm along with Monte Carlo simulation is utilized. The proposed model is
tackled by means of Benders Dual Decomposition (BDD) method. The IEEE RTS test
system (as the transmission system) along with four IEEE 33-node test feeders
(as distribution test systems) are examined to validate effectiveness of the
proposed model.
