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Optimizing Hydropower Plant Location with IoT: A Case Study of Kawa Engineering Ltd.
Technology Category
- Actuators - Hydraulic Actuators
- Analytics & Modeling - Digital Twin / Simulation
Applicable Industries
- Cement
- Renewable Energy
Applicable Functions
- Product Research & Development
Use Cases
- Construction Management
- Virtual Prototyping & Product Testing
The Challenge
Kawa Engineering Ltd. was faced with the challenge of locating a powerhouse close to a waterfall for a client in an area with minimal flood risk. The stakes were high as any occurrence of flooding in the powerhouse would result in significant costs. The ideal location would not only mitigate the risk of flooding but also reduce the need for additional components to protect electrical equipment such as generators, turbines, and switch boxes. Furthermore, the right location would determine the cut and fill required for construction, thereby conserving construction resources.
About The Customer
Kawa Engineering Ltd., based in Vancouver, Canada, is a provider of engineering consulting services. While their expertise is not limited to any specific field, they primarily focus on the design of hydropower projects. They leverage state-of-the-art computational software, finite element analysis, and computer-aided design to add value to their customers. Their services span from conceptual design to final design and construction management of hydroelectric schemes. Their commitment to harnessing renewable energy sources responsibly and effectively is evident in their work.
The Solution
Kawa Engineering Ltd. employed a series of technological solutions to address this challenge. Firstly, they created a model of the riverbed’s surface and shores, near where the powerhouse would be positioned, using data collected via laser scanning. This data was then imported into CAD software and then ANSYS® DesignModeler®. They then used the Eulerian−Eulerian multiphase model in ANSYS CFD to define the interaction between flood water and the ambient air for open channel flow. Transient simulation was employed to determine the initial hydraulic jump from flood-water flow through the waterfall. The CFD simulation was run on a 32-core cluster machine and repeated multiple times using different river conditions to determine the maximum hydraulic jump.
Operational Impact
Quantitative Benefit
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