Tiejian Li

Hydro Unit Commitment via Mixed Integer Linear Programming: A Case Study of the Three Gorges Project, China

This paper develops a methodology for optimizing the hydro unit commitment (HUC) for the Three Gorges Project (TGP) in China. The TGP is the worlds largest and most complex hydropower system in operation. The objective is to minimize the total operational cost. The decision variables are the startup or shutdown of each of the available units in the system and the power releases from the online units. The mathematical formulation must take into account the head variation over the operation periods as the net head changes from hour to hour and affects power generation. Additionally, the formulation must consider the operation of 32 heterogeneous generating units and the nonlinear power generation function of each unit. A three-dimensional interpolation technique is used to accurately represent the nonlinear power generation function of each individual unit, taking into account the time-varying head as well as the non-smooth limitations for power output and power release. With the aid of integer variables that represent the on/off and operation partition statuses of a unit, the developed HUC model for the TGP conforms to a standard mixed integer linear programming (MILP) formulation. We demonstrate the performance and utility of the model by analyzing the results from several scenarios for the TGP.

A common parallel computing framework for modeling hydrological processes of river basins

Restricted computing power has become one of the primary factors obstructing advancement in basin simulations for majority of hydrological models. Parallel computing is one of the most available approaches to solve this problem. Using binary-tree theory, we present in this study a common parallel computing framework based on the message passing interface (MPI) protocol for modeling hydrological processes of river basins. A practical and dynamic spatial domain decomposition method, based on the binary-tree structure of the drainage network, is proposed. This framework is computationally efficient, and is independent of the type of physical models chosen. The framework is tested in the Chabagou river basin of China, where two years of runoff processes of the entire basin were simulated. Results demonstrate that the system may provide efficient computing performance. However, primarily because of the constraint of the binary-tree structure for drainage network, this study finds that unlimited enhancement of computing efficiency is impossible to realize.

Spatial distribution of monthly potential evaporation over mountainous regions: case of the Lhasa River basin, China

Abstract This paper develops an algorithm for computing spatially-distributed monthly potential evaporation (PE) over a mountainous region, the Lhasa River basin in China. To develop the algorithm, first, correlation analysis of different meteorological variables was conducted. It was observed that PE is significantly correlated with vapour pressure and temperature differences between the land surface and the atmosphere. Second, the Dalton model, which was developed based on the mass transfer mechanism, was modified by including the influence of the related meteorological variables. Third, the influence of elevation on monthly temperature, vapour pressure and wind velocity was analysed, and functions for extending these meteorological variables to any given altitude were developed. Fourth, the inverse distance weighting method was applied to integrate the extended meteorological variables from five stations adjacent to and within the Lhasa River basin. Finally, using the modified Dalton model and the integrated meteorological variables, we computed the spatially-distributed monthly PE. This study indicated that spatially-distributed PE can be obtained using data from sparse meteorological stations, even if only one station is available; the results show that in the Lhasa River basin PE decreases when elevation increases. The new algorithm, including the modified model and the method for spatially extending meteorological variables can provide the basic inputs for distributed hydrological models. Editor Z.W. Kundzewicz

Temporal and spatial variations of potential evaporation and the driving mechanism over Tibet during 1961–2001

ABSTRACT Potential evaporation (PE) is the basic component of the global hydrological cycle and energy balance. This study detected the temporal and spatial variations of PE and related driving factors in Tibet, China, for the period 1961–2001, based on observed data recorded at 22 meteorological stations. The results showed that (1) Tibet experienced a statistically significant decrease of PE between 1961 and 2001, which started mainly in the 1980s, along with accelerated warming; (2) the mean annual PE in Tibet showed an east–west increasing trend, and the annual PE at most stations presented decreasing trends; (3) an inverse correlation of mean annual PE with elevation was detected (low–high decreasing trend), and the statistical equations to estimate PE were established based on longitude, latitude and elevation; and (4) PE in Tibet can be well expressed by related meteorological variables, with vapour pressure deficit the dominant factor in determining PE. EDITOR Z. W. Kundzewicz ASSOCIATE EDITOR not assigned

Fault-tolerant technique in the cluster computation of the digital watershed model

Abstract This paper describes a parallel computing platform using the existing facilities for the digital watershed model. In this paper, distributed multi-layered structure is applied to the computer cluster system, and the MPI-2 is adopted as a mature parallel programming standard. An agent is introduced which makes it possible to be multi-level fault-tolerant in software development. The communication protocol based on checkpointing and rollback recovery mechanism can realize the transaction reprocessing. Compared with conventional platform, the new system is able to make better use of the computing resource. Experimental results show the speedup ratio of the platform is almost 4 times as that of the conventional one, which dem-onstrates the high efficiency and good performance of the new approach.

Watershed Sediment Dynamics and Modeling: A Watershed Modeling System for Yellow River

Soil erosion is the root cause of environmental and ecological degradation in the Loess Plateau of the Yellow River. Watershed sediment dynamics was fully analyzed here, and a physically based, distributed, and continuous erosion model at the watershed scale, named the Digital Yellow River Integrated Model (DYRIM), was developed. The framework, the key supporting techniques, and the formulation for natural processes were described. The physical processes of sediment yield and transport in the Loess Plateau are divided into three subprocesses, including the water yield and soil erosion on hillslopes, gravitational erosion in gullies, and hyperconcentrated flow routing in channels. For each subprocess, a physically based simulation model was developed and embedded into the whole model system. The model system was applied to simulate the sediment yield and transport in several typical years in different watersheds of the Yellow River, and the simulation results indicated that this model system is capable of simulating the physical processes of sediment yield and transport in a large-scale watershed.

Evaluating and optimizing the operation of the hydropower system in the Upper Yellow River: A general LINGO-based integrated framework

The hydropower system in the Upper Yellow River (UYR), one of the largest hydropower bases in China, plays a vital role in the energy structure of the Qinghai Power Grid. Due to management difficulties, there is still considerable room for improvement in the joint operation of this system. This paper presents a general LINGO-based integrated framework to study the operation of the UYR hydropower system. The framework is easy to use for operators with little experience in mathematical modeling, takes full advantage of LINGO’s capabilities (such as its solving capacity and multi-threading ability), and packs its three layers (the user layer, the coordination layer, and the base layer) together into an integrated solution that is robust and efficient and represents an effective tool for data/scenario management and analysis. The framework is general and can be easily transferred to other hydropower systems with minimal effort, and it can be extended as the base layer is enriched. The multi-objective model that represents the trade-off between power quantity (i.e., maximum energy production) and power reliability (i.e., firm output) of hydropower operation has been formulated. With equivalent transformations, the optimization problem can be solved by the nonlinear programming (NLP) solvers embedded in the LINGO software, such as the General Solver, the Multi-start Solver, and the Global Solver. Both simulation and optimization are performed to verify the model’s accuracy and to evaluate the operation of the UYR hydropower system. A total of 13 hydropower plants currently in operation are involved, including two pivotal storage reservoirs on the Yellow River, which are the Longyangxia Reservoir and the Liujiaxia Reservoir. Historical hydrological data from multiple years (2000–2010) are provided as input to the model for analysis. The results are as follows. 1) Assuming that the reservoirs are all in operation (in fact, some reservoirs were not operational or did not collect all of the relevant data during the study period), the energy production is estimated as 267.7, 357.5, and 358.3×108 KWh for the Qinghai Power Grid during dry, normal, and wet years, respectively. 2) Assuming that the hydropower system is operated jointly, the firm output can reach 3110 MW (reliability of 100%) and 3510 MW (reliability of 90%). Moreover, a decrease in energy production from the Longyangxia Reservoir can bring about a very large increase in firm output from the hydropower system. 3) The maximum energy production can reach 297.7, 363.9, and 411.4×108 KWh during dry, normal, and wet years, respectively. The trade-off curve between maximum energy production and firm output is also provided for reference.

Investigation of the relationship between runoff and atmospheric oscillations, sea surface temperature, and local-scale climate variables in the Yellow River headwaters region

The Yellow River headwaters region (YRHR) contributes nearly 40% of total flow in the Yellow River basin, which is suffering from a serious water shortage problem. Investigation of the relationship between runoff and climate variables is important for understanding the variation trend of runoff in the YRHR under global climate change. Global and local climate variables, including the West Pacific subtropical high; northern hemisphere polar vortex (NH); Tibetan Plateau Index B (TPI‐B); southern oscillation index; sea surface temperature; and precipitation, evaporation, and temperature, were fully considered to explore the relationship with runoff at Jimai, Maqu, and Tangnaihai stations from 1956 to 2014. The results reveal that runoff had a decreasing trend, which will likely be maintained in the future, and there was a significant change in runoff around 1995 at all stations. Correlation analysis indicated that runoff was dominated by precipitation, NH, temperature, and TPI‐B, and a substantial correlation was observed with sea surface temperature and evaporation, but there was little correlation with West Pacific subtropical high and southern oscillation index. Furthermore, impacts of climate change on runoff variations were distinctly different at different temporal scales. Three dominant runoff periodicities were identified by a singular spectrum analysis‐multitaper method and continuous wavelet transform, that is, 1.0‐, 6.9‐, and 24.8‐year runoff periodicities. In addition, runoff was positively correlated with temperature at a 1‐year periodicity, negatively correlated with TPI‐B at a 6.9‐year periodicity, and positively correlated with NH at a 24.8‐year periodicity, that is, temperature, TPI‐B, and NH‐controlled runoff at annual, interannual, and interdecadal scales. Further, all analyses of the stations in the YRHR showed excellent consistency. The results will provide valuable information for water resource management in the YRHR.