Yadong Mei

The inherent variability and unpredictability of renewable energy output pose significant challenges to power grid stability. Pumped Storage Power Stations (PSPS) play a pivotal role in mitigating these challenges, enhancing the grid’s reliability and operational efficiency. This study proposes an advanced linear analytical method based on Mixed-Integer Linear Programming (MILP) to optimize the short-term scheduling of PSPSs. The goal is to simultaneously maximize the reduction in equivalent load fluctuations and improve power generation benefits. The model linearizes the objective functions, constraints, and decision variables, applying MILP to efficiently derive optimal dispatch solutions. Using the Heimifeng (HMF) PSPS in Hunan Province as a case study, data from four representative daily load scenarios in 2023 are employed to optimize both power output and pumping processes. The results highlight the following nonlinear, competitive relationship between load fluctuation improvements and power generation benefits: as power benefits increase the rate of improvement in load fluctuations tends to decrease. The optimal solutions demonstrate significant outcomes, with improvements exceeding 11.5% in equivalent load fluctuations across all scenarios and daily power benefits surpassing $41,100, reaching a peak of $55,700. This study introduces a robust linear analytical framework capable of simultaneously enhancing power benefits and stabilizing load fluctuations, thereby offering valuable technical support for decision-makers.

An analysis of the effect on the flow regime caused by reservoir operation is crucial to balancing the exploitation and protection of water resources. The long-term effect of this on the intraday scale and small storage capacity is considerable, but rarely analyzed. This study examines the world’s largest dual-cascade hydro-junction, the Three Gorges Dam and Gezhouba Dam junction, as a case study, adopting eight indices to characterize the reservoir’s inflow and outflow fluctuation. In doing this, we evaluate the alteration of the flow regime induced by an up-cascade reservoir and its alleviation caused by the down-cascade re-regulation. The results show: (1) an increment of the river flow fluctuation at the Three Gorges Dam, matched with hourly scale alleviation at the Gezhouba Dam; (2) a reduction (25.09~41.35%) in the quantitative indices of the river flow regime fluctuation; (3) perturbations on the power output. These findings provide references for developing methods to assess the re-regulation mechanisms in systems with upper- and lower-cascades.

The main objective for the Three Gorges Reservoir is to help control floods and to protect the Jingjiang and Chenglingji regions in the middle reach of the Yangtze River. Hydrological measurements have demonstrated that the character of flood propagation in the Jingjiang Reach has changed significantly since the Three Gorges Reservoir became operational, meaning that flood control management must be modified accordingly. To explore the effective flood control management, a hydraulic model was developed to simulate the potential causes and impacts. For a natural flood with gradually varying discharge propagated as a diffusive wave, the celerity downside the dam fasted due to the change of the dominant property of the flood wave. For a flood event controlled by a reservoir, the wave was propagated more quickly as a surge with rapidly varying discharge. The rating curve changed for flooding processes associated with a diffusive wave versus a surge event at a particular cross-section, which changed the flow capacity in the river channel. Observed flood events in 2016 and 2017 were also simulated in the hydraulic model using different management schemes, and the modified flood propagation trends along the lower river reach were analyzed. Lastly, from these simulations, we provide suggestions on how to optimize the operation of the Three Gorges Reservoir to control flood damage and protect the Jiangjiang Reach and Chenglingji areas more effectively.

Rivers provide a variety of ecosystem services to humans. However, human interference significantly impairs the rivers’ functions and poses a threat to river health. To increase the understanding of riverine health in Tibet, China from 2011 to 2014, this study used the Lhasa River as a case study and established a multiple indicator system incorporating both natural and social functions of the river. Weights of riverine health indicators were calculated using the entropy method. Moreover, to evaluate the coordination and development of natural and social functions, a coordinated development degree model was developed. The results showed that the entropy weights of natural and social functions in the target layer were 0.67 and 0.33, respectively. Natural functions, social functions, and riverine state index all decreased from upstream to downstream, and marked as “good” during the entire study period. In 2012, the coordinated development degree improved from previously “moderately coordinated” to “highly coordinated”. Furthermore, the development of natural and social functions was synchronized throughout the study period. Further analysis revealed that the construction of hydraulic projects had a significant effect on the hydrological regime, resulting in an increase in social functions of the river. Therefore, the coordinated development degree model is shown to provide new insight into assessing riverine health in terms of both natural and social functions.

With the development of the economy and urbanization, the contradiction between water use and supply is growing, and it is necessary to explore the relationship and evolutionary process of water flow in the water system from a systematic perspective. Although previous studies have analyzed the water system from a holistic point of view, a comprehensive system that considers virtual water flows is currently lacking. The present study establishes a seven-compartment virtual water system in Tibet in 2012 by combining ecological network analysis (ENA) with the input–output model. Socio-economic sectors and virtual water flows are expressed as network compartments and pathways. The information-based ENA is used to evaluate the characteristics of the virtual water system in Tibet, including its robustness and trade-offs between network efficiency and redundancy. Network control analysis is introduced to characterize the control and dependence intensities over the system, while ecological relationships between pairwise compartments are calculated using network utility analysis. The results indicate that Tibet’s virtual water system has close to optimal robustness, with higher redundancy and limited efficiency. The agriculture compartment is the main controller, while the energy supply compartment is the most dependent on the virtual water system. The overall systematic relationship that the system has is generally mutualistic and synergistic, the majority of which have a positive relationship, although the control and exploitation relationships are dominant. These results can be used to improve network robustness and are of great significance to the sustainable development of the virtual water system in Tibet.

Multi-objective evolutionary algorithms (MOEAs) are widely used to optimize multi-purpose reservoir operations. Considering that most outcomes of MOEAs are Pareto optimal sets with a large number of incomparable solutions, it is not a trivial task for decision-makers (DMs) to select a compromise solution for application purposes. Due to the increasing popularity of data-driven decision-making, we introduce a clustering-based decision-making method into the multi-objective reservoir operation optimization problem. Traditionally, solution selection has been conducted based on trade-off ranking in objective space, and solution characteristics in decision space have been ignored. In our work, reservoir operation processes were innovatively clustered into groups with unique properties in decision space, and the trade-off surfaces were analyzed via clustering in objective space. To attain a suitable performance, a new similarity measure, referred to as the Mei–Wang fluctuation similarity measure (MWFSM), was tailored to reservoir operation processes. This method describes time series in terms of both their shape and quantitative variation. Then, a compromise solution was selected via the joint use of two clustering results. A case study of the Three Gorges cascade reservoirs system under small and medium floods was investigated to verify the applicability of the proposed method. The results revealed that the MWFSM effectively distinguishes reservoir operation processes. Two more operation patterns with similar positions but different shapes were identified via MWFSM when compared with Euclidean distance and the dynamic time warping method. Furthermore, the proposed method decreased the selection range from the whole Pareto optimal set to a set containing relatively few solutions. Finally, a compromise solution was selected.

Wind speed and variability are the most critical climatic factors affecting sand/dust storms, which have not been sufficiently studied in the middle reaches of the Yarlung Tsangpo River (MYR). In this study, wind speed variability was investigated using the moving average over shifting horizon method (MASH), combined with the modified Mann–Kendall test and Sen’s slope based on data from the Tsetang, Lhasa, and Nyêmo meteorological stations during 1960–2015. The results indicated that annual wind speeds for the MYR wide valley regions declined significantly at decadal rates of − 0.216 m/s and underwent three stages from 1960 to 2015: an increasing trend from 1960 to 1975 (0.44 m/s per decade), a weakening until 2006 (− 0.46 m/s per decade), and a remarkable subsequent recovery (1.05 m/s per decade). Different variability trends were observed for the three stations: wind speed decreased significantly during all months at the Tsetang and Nyêmo stations, particularly in the spring, while for Lhasa, a non-significant wind speed increase was detected in summer, and the highest decline occurred in winter. The MASH method resulted in the effective visualization of different patterns, making seasonal process analysis and trend detection easier. In addition, the possible main causes for wind speed change were also discussed. The wind speed change in the study region was strongly associated with the large-scale atmospheric patterns, and the surface pressure gradient variability between the mid and low latitudes may have been a primary driving force. Positive/negative phases of the Pacific Decadal Oscillation (PDO) corresponded well with wind speed decreases/increases and were regarded as an indicator of wind speed variations. The effects of human activities associated with surface roughness change in the MYR were minor compared with the climatic changes.

The Ganjiang River is the largest tributary of Poyang Lake in China, and its hydrological regime variation greatly affects the utilization of regional water resources and the ecological environmental of the lake. In this study, a novel trend analysis method, the Moving Average over Shifting Horizon (MASH), was applied to investigate the inter- and intra-annual trends of flow and water level from 1976 to 2016 at the Xiajiang and the Waizhou hydrological stations in the Ganjiang River. The Significant Change Rate Method (SCRM) was proposed to determine the MASH averaging parameters. The trend analysis results show a statistically significant decrease in water level series throughout the year and the relationship of flow and water level have changed greatly at the Waizhou station. The sediment load reduction, large-scale sand mining and water level decrease of Poyang Lake are identified as the main causes for the water level decrease.