Optimal planning of wind and PV capacity in provincial power systems based on two-stage optimization algorithm

With the rapid development of wind power and photovoltaic (PV) power industry, the curtailment of wind power or PV power in `Three North' areas is serious, due to their short planning and construction time period, as well as being disjoined with the regional generation and grid plan. A novel formulation based on two-stage optimization under low-carbon economy is proposed in present paper to optimize the proportion of wind and PV capacity for provincial power systems, in which, carbon emissions of generator units and features of renewable resources are all taken into account. In the lower-level formulation, a time-sequence production simulation (TSPS) model that is suitable for actual power system has been adopted. In order to maximize benefits of energy-saving and emissions reduction resulted from renewable power generation, General Algebraic Modeling System (GAMS), a commercial software, is employed to optimize the annual operation of the power system. In the upper-level formulation, a hybrid bacterial foraging algorithm and particle swarm optimization (BFAPSO) algorithm is utilized to optimize the proportion of wind and PV capacity. The objective of the upper-level formulation is to maximize benefits of energy conservation and carbon emissions reductions optimized in the lower-level problem. Simulation results in practical provincial power systems validate the proposed model and corresponding solving algorithms. The optimization results can provide support to policy makers to make renewable energy related policies.