Coordinated operations of large-scale UHVDC hydropower and conventional hydro energies about regional power grid

• The study comes from the real demands of hydropower system operations in China.
• A framework for coordinated operations of UHVDC hydropower and conventional hydro energies is given.
• The framework has been applied to China's largest regional power grid since 2014.
• It is effective and efficient to coordinate UHVDC hydropower with conventional hydro energies.
• It fully uses differences among provincial load curves to respond to peak demands.

The bulk hydropower transmission with one-fourth of its total capacity in China via UHVDC (ultra-high-voltage direct current) lines brings a new challenge for receiving power grids. There is an urgent need for coordinated operations about the receiving regional power grids which operate outside energy and their own large plants linked in the AC/DC network. A great operating concern is how to shave peak loads from subordinate provincial power grids using their load differences and various energy source characteristics. The East China Grid, a main receiver of Chinese hydropower transmission and the largest regional power grid, is taken as the example. An integrated framework for coordinating large-scale UHVDC hydropower and conventional hydro energies for power grid peak operation is presented. It divides the original problem into several subproblems according to the types of energy sources. An EPSA (exterior point search algorithm), a heuristic method, and a multi-step optimization algorithm are developed to respectively solve the UHVDC hydropower subproblem, the pumped-storage subproblem, and the conventional hydropower subproblem. These algorithms are integrated into an iterative solution procedure between all subproblems, wherein the EPSA is also applied to allocate power generation among provincial power grids. The proposed method is effective and efficient for coordinating large-scale UHVDC hydropower with conventional hydro energies and for fully responding to different peak loads among provinces, as demonstrated in two case studies.