The multi-objective optimal operation and the joint scheduling of giant-scale reservoir systems are of great significance for water resource management; the interactions and mechanisms between the objectives are the key points. Taking the reservoir system composed of 30 reservoirs in the upper reaches of the Yangtze River as the research object, this paper constructs a multi-objective optimal operation model integrating four objectives of power generation, ecology, water supply, and shipping under the constraints of flood control to analyze the inside interaction mechanisms among the objectives. The results are as follows. (1) Compared with single power generation optimization, multi-objective optimization improves the benefits of the system. The total power generation is reduced by only 4.09% at most, but the water supply, ecology, and shipping targets are increased by 98.52%, 35.09%, and 100% at most under different inflow conditions, respectively. (2) The competition between power generation and the other targets is the most obvious; the relationship between water supply and ecology depends on the magnitude of flow required by the control section for both targets, and the restriction effect of the shipping target is limited. (3) Joint operation has greatly increased the overall benefits. Compared with the separate operation of each basin, the benefits of power generation, water supply, ecology, and shipping increased by 5.50%, 45.99%, 98.49%, and 100.00% respectively in the equilibrium scheme. This study provides a widely used method to analyze the multi-objective relationship mechanism, and can be used to guide the actual scheduling rules.

The lower reaches of Jinsha River host the richest hydropower energy sources in China. With the construction of Wudongde and Baihetan, the multi-objective optimization for cascade reservoirs (along with Xiluodu and Xiangjia Dam) in the lower reaches of Jinsha River will create significant benefits. This paper focuses on the competitive relationship between flood control and power generation, and attaches attention to the measurement of different objective functions and their competitive relationship. With observations of the flood in 1974, 1981, and 1985, a 100-year return period flood with peak-3d volume pair as different inputs for the optimal model is approached by NSGA-II. Different flood seasons divided by flood feature is applied to figure out specific competitive relationship. The results can be concluded as the following: (1) Strong competitive relationship mainly occurs in pre-flood season. (2) Whether it shows a strong competitive relationship depends on the amount of discharge. If the turbine is set to full capacity, power generation is fulfilled certainly, which means that there exists a weak competitive relationship between multi-objectives. (3) The different processes of floods have an effect on the duration of a competitive relationship. A flood with a late peak causes the extension of strong competition in the pre-flood season, which lends itself to a strong competition relationship in the post-flood season. (4) The intensity of competition in the pre-flood season is higher than that in the post-flood season because it has a larger range.