Coordinated optimal operation of hydro–wind–solar integrated systems

Abstract 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.