Weather-forecast based optimal unit scheduling with solar power integration

In order to reduce the CO2 emission of electric power grid, renewable energy resources such as solar power has become an important source of energy in our daily life. When integrated into the power grid, both the randomness of solar power and the ramping capacity of the thermal generation units should be considered in order to provide a feasible and economic schedule. We consider this important problem in this paper, and make the following major contributions. First, we formulate the scheduling problem in the day-ahead market as a stochastic programming, which uses the weather forecasting as well as the ramping capability of the units. Second, we generate different scenarios for the weather and apply the scenario-tree method to approximately solve the problem. Third, we compare our method with existing methods. Numerical results show that our method can improve the integration of solar power while maintain the constraint on ramping capacity of thermal units.