To meet the fault prediction needs of hydro-generator units in the context of big data, combining the characteristics of the attention mechanism with good feature extraction ability and the advantages of model robustness for multi-sensor information driving, this paper proposed a fault prediction system of hydro-generating units based on the attention mechanism and multi-sensor information driving. The system was applied to on-line monitoring of unit ^#8 in August for a hydropower station in Hunan Province. The actual operation results show that the system can effectively predict the vibration trend of the hydro-generator set and realize the intelligent prediction of the hydro-generator.

Phasor measurement unit (PMU) can measure phasors directly, which provides an important technology for dynamic safety monitoring. Aiming at PMU measurements experience errors, a dynamic state estimation method for generators based on cubature Kalman filter (CKF) was proposed. In this method, the fourth order dynamic equations of generators were taken as the system function. The fading factor was introduced into CKF to keep the residual sequence orthogonal at all times, which improves the adaptability of the estimation algorithm. The adaptability of the estimation algorithm was improved, and the defect that the estimation result deviates from the real value due to the uncertain parameters of the generator model was overcome. Simulation results verified the effectiveness of the algorithm.

In order to clarify the hydraulic performance of the submersible tubular pump device in Yangzhou Gate Pumping Station, the internal flow and hydraulic performance of the submersible tubular pump device were analyzed by numerical simulation combined with physical model test. The influence of the front and rear bulbs body on the energy performance of the pump device was compared and analyzed through the comprehensive characteristic index C.P.I, and the scheme of the submersible tubular pump device with the rear bulb body was optimized. The maximum efficiency of the submersible tubular pump device with the rear bulb body is 78.86 %, the flow rate is 314.86 L/s, the lift is 3.594 m, and the blade placement angle is +2°. When the blade angle is -4°, the runway speed of the prototype pump device is 295.19 r/min, which is 1.75 times the rated speed of the prototype pump device. The streamline of straight pipe inlet is smooth under each flow rate conditions, the local area of guide vane appears backflow and the spiral flow inside straight outlet conduit is obvious under small flow rate conditions. With the increase of flow rate, the proportion of hydraulic loss of bulb body and outlet conduit decreases firstly and then increases, and the proportion of hydraulic loss of bulb body and outlet conduit in the whole flow conduits of pump device is the largest. The research results can provide reference for pumping station engineering.

As a large steel structure in the open environment, the miter gate will form a non-uniform time-varying temperature field under the solar radiation, resulting in complex temperature effect on the structure. If not paid attention to the project, it may lead to safety problems such as weld cracking and structure instability. The temperature field of the structure was analyzed by changing the surface coating and using finite element software. The results show that under solar radiation, the gate panel and the top beam form a multi-temperature area array distribution of temperature field, and the beam system temperature distribution is relatively uniform. The surface coating has great influence on the temperature field of the gate. The coating with low radiation absorption rate can reduce the temperature rise of the gate components, and the maximum temperature can be reduced by about 25%. The distribution of temperature field is greatly improved, which can effectively prevent local stress concentration or excessive deformation in the stress field and deformation field of the gate.

In order to review the power generation capacity of the Three Gorges Reservoir under normal operation conditions, and explore the impact of different dispatch modes and upstream reservoir regulation, the preliminary design scheme, optimized operation scheme, and 2015/2019 edition scheme were taken as the calculation model. Considering the main control reservoirs in the upstream, the natural runoff series in Yichang station from 1946 to 1975 used in the preliminary design were selected to calculate the natural flow derivation for reflecting the inflow runoff characteristics of the Three Gorges Reservoir in the current stage. Using natural/return runoff as four dispatch models’ scenarios, the power generation capacity was analyzed. The results show that under current stage, the power generation capacity of the Three Gorges Reservoir is 100.8 billion kW·h, 14.3% higher than the design value; By optimizing the dispatch mode, the full storage rate in October can be improved. Compared with the design mode, the power generation capacity is increased by 5.5-9 billion kW·h; By the regulation of the upstream reservoir, the inflow runoff and the utilization rate of water resources is improved. The power generation capacity is increased by 0.8-2.8 billion kW·h.

Aiming at the problem of power system structure vulnerability, the advantage of multi-index evaluation can be combined with Pajek tool to identify the key nodes of power grid. First of all, based on the complex network theory, considering the power network topology characteristics, structural vulnerability evaluation index system of integrated power system was established. Secondly, in terms of evaluation methods, fuzzy comprehensive evaluation method and CRITIC method were used to calculate the subjective and objective weights of each evaluation index. Finally, combination weighting VIKOR was proposed to calculate the weight value of each node and obtain the ranking result of importance. Taking IEEE-118 system as an example and comparing with different evaluation methods, the results show that this method is feasible.

Drought prediction is an important non-engineering measure to improve drought prevention and resistance. This paper firstly evaluated the ability of multi-scalar standardized precipitation evapotranspiration index (S_SPEI) to identify drought events in Henan Province. Then a drought prediction model based on particle swarm algorithm optimized extreme learning machine (PSO-ELM) was constructed, which used S_SPEI as model outputs and major drought-causing climate system indices selected by Information Changing Rate and Conditional Mutual Information-Based Input Feature Selection Method (ICR-CMIFS) as model inputs. The applicability of the PSO-ELM model in drought prediction in Henan Province was verified by comparing the drought prediction results of this model with standard extreme learning machine (ELM) and differential evolutionary algorithm optimized extreme learning machine (DE-ELM) models. The results show that the S_SPEI-3 can effectively identify specific drought events in Henan Province and reflect the drought situation in Henan Province accurately in terms of time and space; The main drought-causing climate system indices in Henan Province screened by ICR-CMIFS are the western Pacific paratlantic area index and the NINO index; The PSO-ELM model can predict drought in Henan Province accurately, and the prediction accuracy is better than that of the DE-ELM model and standard ELM model, which has better applicability in drought prediction of Henan Province.

Aiming at the difference of the runoff fluctuation regime after the construction of reservoir, this paper adopted several fluctuation quantification methods to analyze the difference of downstream runoff fluctuation regime after the construction of Three Gorges reservoir from the dispersion, tendency and steepness change degrees on the basis of nearly 70-year long time series of runoff data at Yichang hydrologic station. Compared with the natural runoff regime, the results show that the dispersion degree of runoff decreases (mostly in flood control storage capacity reservation period), the tendency change degree of runoff increases and the steepness reduces (mainly in drawdown period), and totally the fluctuation regime changes intricately.

The research on water level prediction method of Fenshui River control station in Fenshui River basin that improves the prediction accuracy is of great significance to support regional flood control decision-making. The typical historical floods of Fenshuijiang hydrology station from 2012 to 2020 were selected and classified into category Ⅰ and Ⅱ flood based on systematic cluster analysis method, with the maximum 1-day flood volume, peak discharge, peak water level and the proportion of flood initiation duration as cluster indexes. The water level classification and prediction of water level stations were carried out by flow routing and water level and flow relation conversion method. The upper and lower boundaries of the water level and flow relationship of different flood types were constructed, and a classified interval prediction method of flood level was proposed. The results show that the accuracy of flood peak water level prediction for the two types of floods is improved effectively, the width of forecast interval is obviously reduced, and the availability of forecast results is improved.

Based on the GMS software, a numerical model of groundwater flow in the Linfen Basin was established to predict the groundwater level under different driving factor scenarios, and the impact of different driving factors on groundwater level changes was quantified. The results show that only in the precipitation scenarios (dry, normal, and wet), the variation of shallow groundwater is greater than that of confined groundwater. When the precipitation is from 458.8 mm to 568.0 mm, the absolute value of the difference in the annual average water level change rate of the shallow groundwater is 0.11 m; Only under the pressure extraction scenario (extraction volume in 2018 as the benchmark), both shallow groundwater and confined groundwater have great changes. When the pressure extraction increases from 0% to 50%, the absolute value of the annual average water level change rate difference between shallow groundwater and middle-deep confined water is 0.16 m and 0.25 m, respectively; Under the situation of the rising water level of the Fenhe River, only the shallow groundwater on both sides of the river will be affected to a certain extent. The research results can provide a certain scientific basis for the rational utilization of groundwater in the Linfen Basin.