Department of Engineering Master's Defence: Jessica Nicole Ritchie
MSc in Sustainable Energy Science
On Friday, June 26th at 9:00 Jessica Nicole Ritchie will be defending her master's thesis project in MSc Sustainable Energy Science. Her research focus is on minimizing cost of algae Production by optimizing the lightning arrangement. The defence will be held on Zoom or in person in M209 at Reykjavík University.
Link to Zoom: https://us02web.zoom.us/j/3288249047
Author: Jessica Nicole Ritchie
Supervisor: Ari Ingimundarsson and Hlynur Stefansson
Examiner: Sigurður Brynjólfsson (from Iceland University)
Title: Minimizing Cost of Algae Production by Optimizing the Lighting Arrangement
Abstract
As a natural carbon capturing system, algae can play a major role in fighting climate change. Algaennovation, a company operational at the Hellisheidi, Iceland power station, is establishing an innovative technology for cultivation of Omega-3 and protein rich microalgae, including Spirulina. Expansion and increasing production calls for techno-economical optimization. Spacing between algae cultivation production units and lighting arrangements determine the production size, affecting building costs, and lighting determines algae production, affecting operation costs. Thus, the variables being optimized are the number of lights selected for one production unit and the distance between the lights and the production unit. This thesis works with Algaennovation to minimize production costs while maximizing biomass output by optimizing the lighting arrangements. The testing is done using two types of lights and multiple configurations given by Algaennovation. Using Matlab, the data is used to predict an optimal lighting arrangement that minimizes costs while maximizing algae production. Using Brute Force optimization, the model is able to determine a feasible cost solution space given specific constraints. It is concluded that from the feasible cost solution space, analysis can be done to determine the optimal lighting arrangement that minimizes production costs.
