Nested optimization method for solving unit combination problem of water-light complementary power station

Abstract

The invention provides a nested optimization method for solving a unit combination problem of a water-light complementary power station. The method is characterized by comprising the steps of 1, predicting a photoelectric output process, considering uncertainty of prediction, generating multiple photoelectric output scenes, and calculating a probability corresponding to each scene; 2, building a unit combination mathematic model of the water-light complementary power station, and determining an objective function, a constraint condition and a decision variable of the model, wherein an optimization objective of the unit combination mathematic model of the water-light complementary power station is minimum average water consumption of a hydropower unit, and a calculation formula is defined in the specification; and 3, constructing the nested optimization method, wherein an outer layer adopts an intelligent algorithm for optimizing a unit startup number, and an inner layer adopts a dynamic planning method for determining a load optimal allocation policy under a given unit startup number.

Description

technical field [0001] The invention belongs to the intersecting field of renewable energy utilization and reservoir scheduling, and specifically relates to a nested optimization method for solving the combination problem of hydro-solar complementary power station units. technical background [0002] Solar photovoltaic is a non-dispatchable renewable energy source, and its output is affected by factors such as day and night alternation, weather changes, cloud thickness, etc., and has obvious intermittency, volatility and randomness. The direct grid connection of large-scale photoelectricity will bring great pressure to the peak regulation and stable operation of the system. Implementing hydro-photovoltaic complementary power generation, transporting photoelectricity to hydropower stations, using the rapid adjustment capability of hydropower units to compensate photoelectricity, and packaging photoelectricity and hydropower together for the Internet is an effective way to pro...

AI Technical Summary

Problems solved by technology

Especially for large-scale hydropower stations (with a large number of units and large installed capacity), it is usually impossible to achieve the unity of calculation accuracy and efficiency when using existing optimization techniques: if the dynamic programming method can be used to obtain the global optimal solution of the problem, but this method It will take up a lot of computing inner layers, and cannot effectively deal with time-period coupling constraints (such as minimum start-stop constraints); using intelligent algorithms can handle time-period coupling constraints, but it will fall into local optimal solutions when there are many optimization variables, showing premature convergence

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