Abstract:

Under the high penetration of new energy sources, the stable operation of the power grids over multiple consecutive days is increasingly affected by the volatility and uncertainty of large-scale wind and solar power output during the daytime, which exacerbates the difficulty of power supply guarantee. This paper proposes a medium-term optimal dispatching method for wind-solar-hydro-thermal multi-energy complementary regional power grids considering the uncertainty of wind and solar power generation. The covariance matrix is adopted to characterize the time-varying characteristics of the wind and solar power generation prediction errors, and the hybrid Gaussian sampling is integrated to generate the scenario set of wind and solar power output. Meanwhile, a conditional sampling strategy is utilized to retain the statistical characteristics of the prediction errors while reasonably reducing the number of scenarios. With the objectives of minimizing the sum of squares of grid-wide power shortage and curtailment as well as minimizing the thermal power operating cost, a multi-objective optimization model for wind-PV-hydro-thermal complementary operation is established. A hierarchical weight optimization method is proposed to balance the target priorities and the relative importance of each objective, thus achieving efficient solution. Simulation scheduling based on the actual data of East China Power Grid shows that, compared with conventional methods, the proposed method can reduce the overall power shortage of the system by more than 33.3%, while ensuring high reliability of grid dispatching plans. The daily maximum power shortage/curtailment only accounts for 1.3% and 1.7% of the load, respectively, which provides an effective approach for the formulation of multi-day consecutive dispatching plans of power grids under high renewable energy penetration.

Key words: time-varying characteristics, regional power grid, medium-term dispatching, hierarchical weight optimization method