Multi-objective Optimization of PV & Greenroof

Pareto Front Solutions | FALL 2015, Master’s Thesis Project | Prof. Volker Hartkopt

PV production has been doubling every two years, making it the world’s fastest-growing energy source. Module price is currently $2.5-3.8 per peak watt ($/Wp), which leads to a Levelized Cost of Electricity (LCOE) of approximately 21 U.S. cents per kWh. Green roofs reduce operation temperature of the PV system, PV array offers shading for green roof, thus improving growth of plants and increasing number of species. To utilize both PV and Green surface, I selected 16 different types of roof structure on campus. Those roof surfaces could be manipulated by orientation, angle, and areas, applicable areas can be calculated into cost and electricity production. 



The workflow was designed through the use of existing plugins for Rhino: Grasshopper fro geometry, Octopus for multi objective optimization. Grasshopper was chosen as a platform for parametric geometry modeling. The design generation is carried out in GH and performance evaluation in simulation software respectively. Octopus creates a Pareto ranking to identify potentially well-performing solutions. 

No bias in the objectives is included as part of the optimization search from the outset to produce the widest possible range of solutions for the given design problem. The solution’s quantitative data and 3D geometry is recorded and stored in GH.  The results are displayed as 3D Geometry, after finishing selection of objectives and We can calculate each benefit from plotted categories of buildings.