Stochastic Optimization To Reduce Cost Of Energy In Parabolic Trough Solar Power Plants

The need for clean and cheap renewable energy is on the rise. Solar energy is one of the most clean and readily available technology with almost zero carbon emissions. Optimizing the resources to produce efficient power at low costs is the need of the day. In this thesis, we present a systematic method to optimize levelized cost of energy for 100 MW and 500 MW power plants. We use SAM, which is a simulation software to study the parabolic trough solar technology in detail and define the decision variables and uncertain variables for the problem. Then we use BONUS which is an optimization algorithm to optimize the cost using the samples of these variables. This theses analyzes the differences between the optimal and base solutions and shows the effect of uncertainty on the results. We present the optimal values for the various technical parameters which gives us the least cost of energy.