HydroGIS 96: Application of Geographic Information Systems in Hydrology and Water Resources Management (Proceedings of the Vienna Conference, April 1996). IAHS Publ. no. 235, 1996. 235

Development of an integrated simulation and optimization system of river power plants and river reservoirs

T. ACKERMANN Institute of Hydraulic Engineering and Water Resources Management, Aachen University of Technology, Kreuzherrenstrasse, D-52056 Aachen, Germany

L. KONS RWE Energie Aktiengesellschaft, Head Office, Renewable Power Production, Department Hydro Power, D-45117 Essen, Germany

J. KÔNGETER Institute of Hydraulic Engineering and Water Resources Management, Aachen University of Technology, Mies-van-der-Rohe-Strasse I, D-52056 Aachen, Germany

Abstract An object-oriented GIS with its topological database and a powerful engine to visualize data in a geographic context is coupled with a two-dimensional finite element program to solve the Navier Stokes equations. Not only the generation of the finite element mesh, but also the administration of pre- and post-processing of simulation data is managed by the GIS. The simulation can be started on the local CPU or on a remote host, thus enabling parallel processing of the GIS and the simulation program. A case study on the River Mosel shows how this model is applied with regard to the optimization of a river power plant.

PROBLEM IDENTIFICATION

The River Mosel has its source at an altitude of 735 m a.m.s.l. at the Col de Bussang in the Vosges mountains, France. Over a distance of 58 km it forms the border between Germany and Luxembourg between Apach and Trier. From Trier it passes through German territory for 206 km. After a total distance of 520 km it flows into the River Rhine (59 m a.m.s.l.) near the city of Koblenz.

The River Mosel, the largest tributary of the Rhine, with a catchment area of 28 000 km2, has a wide range of discharge, with very small discharges during dry periods and floods mostly during winter time. The following data have been determined at the gauging station Trier since 1931: - catchment area: 23 775 km2; - maximum flood discharge: 3950 m3 s'1 (December 1993); - mean discharge: 282 m3 s"1; and - minimum drought discharge: 27 m3 s4 (July 1976).

In the years 1958 to 1964, the River Mosel was canalized between Thionville (France) and Koblenz. This construction was followed by the canalization of the upper Mosel in the late 1960s and 1970s and the canalization of the River Saar, finished in 1989. The resulting system of water highways has become a very important European transport way.

236 T. Ackermann et al.

The subject of the case study described in this paper is the section of the River Mosel between Trier and Koblenz, especially the Trier impoundment. It is seen in Fig. 1 that in this area there are 10 weirs. Each (except the Koblenz weir) consists of one navigation lock (20 X 170 m), one lock for sporting boats, four adjustable sector gates (40 m), one fish pass, and one run-of-river power plant.

Between Trier and Koblenz, the River Mosel is navigable for ships with a maximum draught of 2.70 m, the minimum navigable width is 40 m. The hydroelectric power potential of the impoundments is exploited by 10 run-of-river power plants owned by Moselkraftwerke GmbH, a subsidiary of RWE Energie, Germany. The power stations are similarly designed (except in Koblenz). They consist of four Kaplan units, tube turbines with adjustable runner blades, adjustable guide vanes with a planetary gear and a synchronous generator. The nominal discharge of the power plants is 4 x 100 m3 s"1, their nominal heads vary from 4.00 m (Zeltingen) to 6.85 m (Detzem). The 10 power plants with a total capacity of 180 MW have an average annual production of 800 GWh year1 of renewable energy.

The Koblenz weir including the hydroelectric power plant was constructed from 1941 to 1951 and varies from the other nine. Main differences are: two locks instead of one, vertical Kaplan turbines instead of tube turbines, and a nominal discharge of 380 m3 s"1 instead of 400 m3 s"1.

The Mosel power stations are equipped for fully automatic operation. The machine sets are operated by means of level control equipment, depending on the water level of the River Mosel. A central control station situated at the Fankel power plant supervises and controls, amongst other hydroelectric power stations, the operation of the power stations mentioned above. The main task of the operator (up to a river discharge of 400 m3 s"1) is to keep the water levels of the impoundments within the very narrow tolerance of ±0.05 m, granted by the public waterway authorities.

The operation of the Trier power station differs from these rules. Due to a very unsteady discharge from the upper Mosel and the confluence of the rivers Mosel and Sauer and Mosel and Saar, the two main tributaries, the constraint of the tolerance of +0.05 m cannot be met in the reservoirs downstream. Therefore, the Trier river section has been used as a buffer, thus allowing a controlled discharge downstream. The water level in Trier has been manually managed by the control station within a maximum range of 0.60 m.

On account of the significant increase of transport capacity within the last years, especially since the accomplishment of the Saar canalization, the international Mosel commission decided to deepen the Mosel channel by 30 cm. This is planned to be done by excavating the river bed. To avoid the enormous expenditure of an excavation in Trier the idea of reducing the 60 cm tolerance to 30 cm (Fig. 2) was conceived. By this measure the water level should be kept within the upper 30 cm of the range granted, so that ships with an increased draught of 3 m instead of 2.70 m could pass through the impoundment and enter the Mertert harbour, the only harbour of Luxembourg.

On the other hand, this alternative implies that the operational volume of the Trier impoundment would be reduced significantly. As a result of this, the manual management of the Trier power station could not be continued. First tests of operation with reduced volume resulted in impairments of the steady turbine discharge in the Trier power station and the downstream plants. Therefore the operating company RWE Energie commissioned the Institute of Hydraulic Engineering and Water Resources

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INTEGRATED SIMULATION MODEL

The model to simulate the flow in the reservoir and control the calculation consists of a two-dimensional finite element program to solve the Navier Stokes equations and a Geographical Information System. The former is managed by the GIS and exchanges data via ASCII files. The authors decided to use the Smallworld GIS for its object-oriented structure. A detailed description of the advantages gained by the application of this kind of GIS can be found inRuland (1993). The objective of this paper is to describe experiences and identify problems in applying the GIS for the project mentioned above.

Simulation data are stored and managed in a relational database. It can be classified into two types: permanent data and variable data. The first category incorporates the mesh geometry (coordinates of elements and nodes) and the boundary conditions as raw data, whereas the second class includes temporal data like calculated boundary conditions and results derived from the calculation. They require a powerful and flexible management system that is operated by the GIS.

Mesh generation

The design of the finite element mesh is carried out mainly in the GIS environment. The topographic background information consists of sampling points of the bottom elevation of the river bed and raster maps of the modelled river section. A network of triangular and quadrilateral elements, with its corner nodes lying on top of selected elevation points, is digitized on the screen. The exchange of information on bottom elevation between the corner nodes and the sampling points is guided by a spatial scanner. It performs a search in the topological database on the basis of coordinates rather than on alphabetical content. Since the geometrical data are stored in the database in its geographical environment this is a very efficient query method. The bottom elevation of the sampling point derived from the spatial scanning is copied to the corner node of

Development of an integrated simulation and optimization system 239

the network. This mesh will later be used to assign the bottom elevation to the nodes of the finite element mesh.

A coarse finite element mesh is digitized on the screen. This procedure has the advantage that the raster map shows the course of the river with the exact location of the confluence of rivers and hydraulic details, such as bridges, harbours, weirs and river power plants. Appropriate parameters for local refinement of the mesh can thus be determined. The objects fe_elements mdfenodes derive their geographical coordinates from the raster map, and the bottom elevation of the fejiodes is interpolated from the network described above.

Integration of the simulation model into the GIS

The flow in the reservoir is calculated using a two-dimensional finite element approach. The simulation program RISMO (River Simulation MOdel) was developed at the Insti­tute of Hydraulic Engineering and Water Resources Management, Aachen University of Technology. The program is encoded in C and runs in a UNIX shell. The input data consist of: — a control file setting the directory path, convergence parameters, turbulence models,

etc; — mesh geometry files; and — a boundary conditions file.

For more information about the program refer to Rouvé & Schroder (1994) and Ackermann & Kôngeter (1995). The control file and the boundary condition file are subject to frequent changes. The GIS provides major support in the development and maintenance of these files (discussed later). On starting the simulation they are created within the GIS and passed to the flow simulation program (pre-processing). Calculated data are re-imported and stored in a database for further evaluation (post-processing).

Management of the integrated information system

The management of the integrated information system requires a flexible database and a powerful visualization tool. The access to the database and the control of the representation of simulation data in a geographical context is supported by two main editors. A short description of these editors is given below.

Pre-processing editor The pre-processing editor supervises the simulation model. An identification code for the simulation coordinates the access to different sets of input data (simulated time interval, length of time steps, etc.) in the database. The boundary condition file and the control file can be assembled using editors invoked from the pre­processing editor and stored under a corresponding id.

Both the GIS and the simulation program require powerful work stations. On a work station with two CPUs, parallel processing is recommended. If only one processor is available, or to perform the calculation on a more powerful computer, a remote host can be selected from the editor.

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Post-processing editor The calculated simulation data are re-imported into the GIS. This leads to a large number of data sets that are stored in the database under different identification codes for the different runs of the simulation (run id). The post-processing editor allows one to choose a run id and to display the results from it. Drawjnethods are sent to the fe_elements and fejiodes to calculate the colour coding for the visualiza­tion of the water level and to set up vector geometries for velocity representation (Fig. 3).

To display the water level along an arbitrary trail, a data_section object queries the database on the water elevation of fejiodes that are connected to the trail by their topology.

Administration of boundary conditions

The time series data of the inflow to the reservoir and the outflow (the water level at the weir), constitute the boundary conditions of the model. The raw data derived from recordings of water gauges are stored in special boundary condition objects in the GIS. By a symbol located on the screen at the respective boundary, an object editor can be opened that allows the management of the data.

The time series can be visualized in a diagram, in order to permit effective control and judgment of the results. Due to the strong variation of the inflow, a new boundary condition set is calculated for each time step and the boundary condition file is assembled according to previously determined parameters.

CASE STUDY: RIVER MOSEL, TRIER RESERVOIR

The integrated model is applied for the design of on optimized regulation of the reservoir described above. Figure 4 shows a schematic overview of the modelled section of the Mosel. The finite element mesh was assembled on the basis of 28 000 sampling points of the elevation of the river bed and 17 raster maps on a scale of 1:1000. The flow of

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242 T. Ackermann et al.

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data from the background information to the finite elements and nodes is supported by the topological database, which makes queries concerning geographic data very efficient.

The simulation is carried out on a work station with two CPUs. Pre- and post­processing of the data is organized with appropriate identification codes (ids). A simulation code controls the input data. The results of the calculation for each time step are managed by run ids.

The regulation of the turbines in the river power station is based on the water level registered at a water gauge about 50 m upstream. In the process of setting up the simulation and optimization model a constant comparison of historical data and proposed data is essential. A water gauge object placed at the location of the water gauge shows the time series of calculated water level versus measured water level within the permitted range of 130.15-130.45 m if invoked. Figure 5 shows the good agreement in the case of the Trier reservoir.

The GIS implementation of a model to simulate the flow in the River Mosel with respect to a future optimization of the operation of the river power plant proves to be an efficient approach. The object-oriented structure of the GIS provides powerful tools to support the implementation. Such a simulation model sets a high demand upon the hardware. Parallel processing on two powerful work stations is beneficial.

REFERENCES

Ackermann, T. & Kongeter, J. (1995) Strômungs- und Stofftransportsimulation in Flieligewassern (Flow and transport simulation in free surface flow). 10. Symposium: Mathematik in der Umwelttechnik (19-20 June 1995), 44-48. Schriftenreihe des Fachbereichs Mathematik der Gerhard Mercator UniversitatDuisburg, Arbeitskreis: Mathematik in Forschung und Praxis.

Rouvé, G. & Schroder, M. (1994) Entwicklung eines mathematisch-numerischen Verfahrens zur Berechnung naturnaher Flieligewasser (Development of a mathematical-numerical code to calculate natural free surface flow). Final Report of the DFG-Project Ro 365/31-6.

Ruland, P. (1993) Numerische Simulation des Sedimenttransports unter Verwendung eines objektorientierten Geogra-phischen Informationssystems (Numerical simulation of sediment transport using a geographic information system). Mitteilung des Instituts fur Wasserbau und Wasserwirtschaft, RWTH Aachen, Germany.