"Cost Optimization of Small Hydropower
"As the world economy grows, electricity demand grows along with it. In considering the possible future energy sources, hydropower provides several advantages: it is highly efficient, can be easily incorporated into multipurpose projects, has a low annual maintainence cost and a long life span. Although industrialized nations have already exploited most of their large-scale hydropower potential, there remains much room to construct large hydropower plants in the developing world. Small hydropower however, still has a place in both. The largest economic challenge facing a small hydropower project is the high initial investment cost relative to competing fossile fuel sources. This Thesis provides a new type of preliminary costing methodology which first optimizes preliminary design components of a small hydropower plant based on a limited set of site-specific data and then uses stochastic simulation to determine the cost uncertainty of four costing catagories and the resulting net present value (NPV) of the project.
First, the suitability of using the RETScreen formula-based costing method for four cost catagories is assessed using a Case Study in Neum¨uhle, Southern Germany. Next, the NPV is determined for a 30-year design life and optimized using a continuous Genetic Algorithm.
The final chapter of this work performs stochastic simulations using the Monte Carlo method comparing the expected prefeasibility cost accuracy against the Case Study results.
It was found that for the Case Study, the initial accuracy of the individual costing equations had the strongest affect on the outcome of the cost analysis. Additionally, the optimized design performed better then the original assessment in determining the preliminary values of design flowrate and operating head.