Francis Turbine Upgrade for the Lushui Generating Station by Using Computational Fluid Dynamics - A Case Study
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1 Francis Turbine Upgrade for the Lushui Generating Station by Using Computational Fluid Dynamics - A Case Study J. Huang, Ph.D., Hydraulic Energy Group, Sustainable Buildings and Communities, CANMET Energy Technology Centre - Ottawa, Natural Resources Canada, Ottawa, Ontario, Canada Tel: , fax: , jhuang@nrcan.gc.ca J. Swiderski, P. Eng.,, Ottawa, Ontario, Canada Tel: , fax: , jacek@keynetz.net J. Ji, Lushui Pivot Management Bureau, Ministry of Water Resources, Chibi City, Hubei, China Tel: , fax: , jijinting@163.com T. Tung, Hydraulic Energy Group, Sustainable Buildings and Communities, CANMET Energy Technology Centre - Ottawa, Natural Resources Canada, Ottawa, Ontario, Canada Tel: , fax: M. Riley, Sustainable Buildings and Communities, CANMET Energy Technology Centre - Ottawa, Natural Resources Canada, Ottawa, Ontario, Canada Tel: , fax: , mriley@nrcan.gc.ca Abstract Canada-China project Transferring Small Hydro technologies to China focuses on supporting environmentally sustainable development in China by improving technical and economic viability of small-hydro technologies to increase power production from small hydro and displace greenhouse gases emissions. The Turbine Design Enhancement is one of the Canadian technologies transferred in this project. A Francis turbine unit at the Lushui Generation Station of the Lushui Pivot management Bureau has been identified to apply this technology. The oversized generator and runner cavitation with turbine s large head and flow variations at the dam were taken into consideration. Hydrological conditions of the site, the Computational Fluid Dynamics (CFD) design approach and methodology used to optimize the Francis runner design will be described. The appropriateness of CFD use for the design of small-hydro turbines, and the replication potential of this technology in China will be discussed. Keywords Francis turbine, Design enhancement, Turbine upgrade, CFD, Small Hydro Operating conditions at the Lushui Generating Station The Lushui Generating Station (LGS) is located southeast of Wuhan in Hubei Province, China. The plant was originally built as a scaled down, semi-homologous model of the Three Gorges dam. Main powerhouse, built as a structural part of the main dam, is equipped with four large Kaplan turbines and provides energy to the national grid. The Francis turbine, which is a subject of this presentation, is located in the auxiliary powerhouse about 120 m downstream. The operating conditions of the plant are variable to a large degree as common in most dam-based hydropower installations. Relatively small head pond level fluctuations and large variations of the tailrace level are observed (Figure 1). The Lushui configuration and complex hydrological conditions result in large head and flow variations at the dam which affects operation of the power generating equipment. The most suitable type of turbine, capable of adjusting to radically changing operating conditions, would be a double regulated turbine (Kaplan type). General hydrology of the Lushui site Hydrology of the site according to the flow duration statistics and the water levels at the head pond and at the tailrace shows a large variation of the gross head ranging from 17 to 27 m [1]. It is assumed that the water supply for the Francis unit is always sufficient to perform operation at the full generator capacity because this 1
2 turbine unit uses only marginal amount of water. The site has characteristics of a mountain-type with large possible fluctuations of the headpond or tailrace levels. Large upstream reservoir allows stabilizing and limiting headpond level fluctuations, although the flow-through capacity of the tailrace is limited and creates large fluctuations of the water elevation. This affects the operating conditions of the turbine in two ways: a) changing exposure to cavitation, as the suction head changes; and, b) changing turbine unit speed (n 11 ), therefore varying runner inlet conditions. TWL(Tail Water Level), HWL(Head Water Level) [m] Lushui G.S. Water level fluctuations SWIDERSKI ENGINEERING INC Flow [cms] TWL HWL Hs Turbine Setting Hs [m] Flow [cms] River Flow Lushui G.S. Flow duration curve SWIDERSKI ENGINEERING INC. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Time exceedance [%] Figure 1: Tail water level fluctuation (left) and flow-duration curve (right) at Lushui site. Hgross Design Head Range Gross Head [m] Francis turbine unit The turbine unit is of a classical Francis turbine arrangement, having spiral case, set of 10 fixed stay vanes, movable and equally spaced 16 wicket gates, classical Francis runner equipped with 14 blades, aeration structure at the runner outlet and the conical draft tube. The turbine operates at full power most of the time. Numerical model of the turbine As each component of the turbine influences performances of the runner, the numerical model, for runner design purpose must include entire turbine flow passage from the butterfly valve to the exit of the draft tube. The computational domain is composed of several body-fitted grid blocks, each representing a section of the turbine flow passage. All grids are created with the TASCgrid software (part of the CFX-TASCflow commercial CFD package) and Swiderski Engineering (SE) s own subroutines, which determine shapes of each block s boundaries and nodes distributions within each block. After all blocks are created and stored on the disc, the script procedure performs automatic connections thus building a numerical image of the turbine s geometry. In order to create physical representation of the real flow passage, the TASCbob program is used to assign inlet and outlet boundary conditions as well as to define type of grids interface between rotating and non-rotating coordinate systems. For the design purposes the frozen rotor boundary conditions were applied at the distributor- runner and runner-draft tube interfaces to account for the non- axisymmetric flow domain [2]. Figure 2: All grids connected computational domain of the Lushui Francis turbine. 2
3 Flow simulation for the existing stationary components was conducted for a generic runner having close characteristics to the target design and for the custom optimized one for the Lushui project. Blade shape optimization general procedure The design methodology applied has been under development by SE for last 8 years [3]. Previous applications proven its efficiency and accuracy, however for the first time this method was applied to the Francis runner operating under so wide operating range. First design was created for the average operating conditions the first runner blade design generated would make the Lushui turbine to have peak efficiency between two extreme operating points. In the next step, the performances of the runner were checked at extreme expected net heads 20m and 27 m. Figure 3: Flow chart of the optimization process Where: Ψ x : quality factor; ξ x : active geometry parameter; x : rate of change of ξ x ; and, ε : proximity of the solution ( ε ~ Ψ target /1000 ). Quality factors used in couple optimisation processes included (a) turbine efficiency, (b) draft tube stability, and (c) cavitation. The final design was created as a result of multiple runs of optimisation processes. The multi-parameter optimisation, proven to be the most productive in the past, was conducted in a couple of phases. Special emphasize was put on the draft tube stability and the cavitation-free operation. The first optimisation phase was performed for the following definition of quality factors: Ψ 1 = LE_Inlet (1) Ψ 2 = η * V_DT_Inlet (2) Where: LE_Inlet : degree of uniformity of the flow field within the vicinity of the leading edge; η : hydraulic efficiency of the turbine; and, V_DT_Inlet : degree of uniformity of the flow field at the draft tube inlet. The final optimisation phase was performed for a more complex target definition, which consisted of three independent quality factors: Ψ 1 = LE_Inlet (3) Ψ 2 = η (4) Ψ 3 = V_DT_Exit (5) Where: V_DT_Exit is the degree of uniformity of the flow field at the draft tube outlet. 3
4 Blade shape optimization leading edge As the automatic design process applied finds a general shape of the blade without attempting to change thickness distribution of the blade, the analysis of the flow at extreme operating points immediately disclosed deficiency of the first design. The following were noticed: 1. Severe cavitation at the leading edge the highest head operating point; and, 2. Significant drop in efficiency and power for the lowest head operating point. Observation of the flow pattern led to a conclusion that the leading edge profile must be modified in order to lower local pressure gradients to eliminate cavitation and flow separation on both sides of the leading edge. Then series of leading edge profile modifications undertaken resulted in a new thickness distribution, which again was applied for the optimization procedure as conducted at the beginning. The design peak efficiency point was also slightly modified and it was placed closer to the high-head operating point. Figure 4: Leading edge flow for maximum net head H net = 27 m, design net head H net = 23.5 m and the minimum net head H net = 20 m (from left to right) Draft tube flow Due to the fact that the relatively long conical draft tube has large expansion angle of 6 deg, special emphasis has been put into the runner design to avoid from the possibility of flow separation at the wall. Furthermore, draft tube flow uniformity was defined as one of the key optimisation criteria for the runner design. Figure 5: Draft tube flow at the H net = 23.5m.. Surfaces of constant velocity (iso-velocity surfaces) illustrate uniformity of the draft tube flow. When the results were analysed from the aeration structure viewpoint, the following are general qualitative indicators: Power lost due to flow interference with the aeration structure is 1.5% and hydraulic efficiency lost is 0.75 %. It is also highly possible that there are locally favourable conditions for the severe cavitation, as the peripheral section of all four spokes is exposed to a high velocity flow. As the newly designed runner locates peak efficiency of the turbine between the extreme operating points, the circumferential velocity component at the draft tube entrance is expected to be significantly smaller when compared with the flow induced by the old runner. Based on the simulation results, this structure will be nothing but obstruction. Figure 6: Flow around the aeration system structure best efficiency operating point for the newly designed runner 4
5 Spiral case - distributor flow The existing spiral case is of a classical design. Flow analysis conducted confirms a good hydraulic design of the spiral case and cascades of stay vanes and wicket gates. Anticipated head losses are small and the flow pattern at the runner inlet is uniform, therefore no modifications to these turbine components were suggested. Figure 7: Distributor flow at the optimum operating point (H net = 23.5 m). Final design of the runner It was determined that the peak efficiency of the existing turbine is located close to the operating point corresponding to approximate 20m of Net head. This means that the majority of time the runner might be exposed to the leading edge cavitation, as the operation is on the left side of the peak, therefore at the too-lowspeed range. Therefore, for the new turbine design, the operating range is shifted to the higher heads (lower Q 11 and n 11 ) compared to that for the existing turbine. 1.8 Lushui Project Hill chart position - NEW and OLD runners SWIDERSKI ENGINEERING INC. 1.6 OLD 1.4 NEW Q OPERATING RANGE n11 Figure 8: (8a) Hill charts comparison of the turbine equipped with the existing (OLD) and the newly designed (NEW) runners; (8b) pressure distribution on runner surface of the newly designed turbine. 5
6 Summary of the blade optimisation As presented, the final stage of the optimisation process was conducted by means of the automatic procedure. 200 to 400 shapes modifications were undertaken during the search for solution. The general blade shape was defined, prior to this optimisation process, as an initial guess based on general formulas estimating blade inlet and outlet angles, as well as based on two similar projects completed recently by Swiderski Engineering. Charts shown on Figure 9 present history of convergence as well as selected pictures of pressure distribution on the runner blade along with the streaklines representing flow at the draft tube inlet. Figure 9: Second stage optimisation process CFD role in design for small-hydro, the technology potential in China China has abundant resources of small hydropower. It has built over 40,000 small hydro power plants with a total installed capacity of over 30,000 MW, but this presents merely more than a quarter of the total exploitable capacity [4]. Due to the high rate of increase in energy demand especially clean energy due to the fast growing economy, there is still a large market for small hydro development. In China many old aging (30-40 years) power stations were designed using old technologies and are very energy inefficient, which needs to be upgraded in order to increase energy efficiency and output. Also, the refurbishment of these old small hydro power stations will provide a significant impetus to ecological, social and economical benefits. While small hydro sites equipment in China is well-standardised giving very good perspectives for replications, for numbers of occasions, case-by-case design according to the sites conditions is necessary to maximize the utilization of water resources. The Lushui project undertaken under the Canada-China small hydro technologies transferring project demonstrates the effectiveness and perfect applicability of the technologies developed by the authors for refurbishments and modernizations of small hydro stations based on CFD. There are good replication opportunities in China for both of new and existing small hydro sites with these technologies. 6
7 References [1] Francis Turbine Upgrade, J. Swiderski, Technical report to Public Works and government Services Canada, J. Swiderski,, Ottawa, August 2005 [2] CFX TASCflow, Ver. 2.12, users manual, ANSYS, 2003 [3] Design optimisation of replacement Francis runner CFD application in an optimization algorithm, J. Swiderski, 13th International on Hydropower Plants, Vienna 2004 [4] Small Hydro Power: China s Practice, Tong Jiandong, China WaterPower Press,
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