MULTI-OBJECTIVE OPTIMIZATION STUDY OF AN AXIAL LOW HEAD TURBINE
Micro-hydro power plants (PLTMH) have great potential in Indonesia. With the increasing demand for electricity every year, also support the national policy that by 2050 at least 31% of the energy should come from new and renewable energy sources, the development of PLTMH is necessary, considering th...
Saved in:
| Main Author: | |
|---|---|
| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/77134 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Micro-hydro power plants (PLTMH) have great potential in Indonesia. With the increasing demand for electricity every year, also support the national policy that by 2050 at least 31% of the energy should come from new and renewable energy sources, the development of PLTMH is necessary, considering the conditions of rivers in Indonesia that have low head. In 2020, Raditya has conducted numerical simulations on an axial turbine design and obtained a maximum efficiency about 83%. This study focuses on the multi-objective optimization of this turbine design.
In this study, the objectives selected for optimization are the improving turbine efficiency and power. To obtain a set of solutions that represent all the objectives to be optimized, the NSGA-II multi-objective optimization method is used. To perform the optimization, a surrogate model is employed to approximate the actual problem model. The data used to build the surrogate model is obtained from various designs generated by sampling using the Latin Hypercube method. The fitness function values for each sample are obtained through CFD simulations.
Through the optimization process, three optimal designs are obtained, each with a tendency towards a different objective. Under the respective design conditions, each optimal designs 1, 2, and 3 achieve efficiencies of 89.04%, 88.42%, and 88.91%. Under the same design conditions, each optimal designs 1, 2, and 3 power output generated is 349.16 W, 362.30 W, and 354.06 W, respectively. |
|---|