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The high proportional integration of variable renewable energy sources (RESs) has greatly challenged traditional approaches to the safe and stable operation of power systems. Considering the complementary characteristics of various RESs, an optimization model is proposed in this study for cascade hydropower stations coupled with renewable-energy-based power generation methods such as wind and photovoltaics (PV). Building on the autoregressive moving average (ARMA) model and improved vine-copula theory, a joint distribution model for wind and PV power is built with measured data to capture the spatial and temporal correlations between wind and solar plants, and sufficiently representative scenarios for renewable energy generation are explored. Due to nonlinearities in the forebay elevation vs. reservoir volume, tailwater elevation vs. water flow, and head-sensitive power generation in hydropower stations, several linearization approaches are used to reformulate the optimization model into a more tractable form. The hydraulic relationship and time delay of water flow between cascade reservoirs are established to make full use of the controllable complementarity of hydropower generation. Optimized coefficients of coordinated operations in different seasons are obtained by a heuristic algorithm for cascade reservoirs. A detailed case study is undertaken in a basin with wind farms and solar arrays in Southwest China, and the simulation results demonstrate the potential of a large-scale hydro–wind–solar hybrid system to meet export power transmission demands. Finally, the optimal capacity of wind and PV plants is determined to inform the future planning and construction of actual systems.

Due to the clear differences in the characteristics of different power sources, it is necessary to take both the economic and security requirements of the power grid into account simultaneously to achieve an optimal operation strategy for a multienergy power system. This paper focuses on the optimal day-ahead dispatching of a hybrid power system that includes wind power, solar photovoltaic power, cascade hydropower, thermal power, and pumped-storage power. Considering the complementary characteristics of these different sources, a day-ahead joint optimal dispatching model of the multi-energy power system is established, with objectives of maximizing the security level, economic benefits and renewable energy consumption. A three-stage method based on Benders decomposition is proposed to solve this complex multiobjective problem. By decoupling the security and economic problems of the hybrid power system, an efficient solution for the scheduling strategy is achieved. The influences of factors such as the diversity of natural scenarios and the security requirements of system operation on the scheduling results are fully discussed in the case study section. The computational efficiencies of the proposed three-stage method and of the direct method are also comparatively analyzed. The simulation results verify the superiority of the proposed scheduling strategy and algorithm.

Renewable Energy Production Simulation Platform (REPS) is developed by China Electric Power Research Institute (CEPRI) to simulate the operation of renewable energy in the power system. REPS takes into account the characteristics of China’s electric power system, it can assess the accommodation of renewable energy power and simulate the impact of different renewable energy capacity on the operation of power system. Assessment model and calculation process of REPS V1.3 is introduced in this article, and annual consumptive capacity in one provincial power grid of China is evaluated with the platform. REPS is of great guiding significance to electrical source planning. With the sustained and rapid growth of renewable energy in China, power system will be more and more dependent on REPS.