Development of an Engineering, Economic and Environmental Design Tool for Planetary Scale Sustainable Power Systems

Abstract

There are plenty of fossil fuels for hundreds of years. The importance of moving toward sustainable energy stems from global climate change and the need to provide access to affordable energy to all of humanity. The way forward is to help the developing world that dominates the future emissions (90% solution) with “clean” energy, rather than reducing the emissions for the developed world to make it clean (10% solution). The 90% solution has to be done consistent with appropriate technologies, sound business plan, and market economy. The ultimate goal of information presented in this dissertation is to satisfy a country’s national load demand by establishing multiple utility grid connections to various geographic locations of high wind or solar energy resources. This is done by building a new optimization design tool which investigates the engineering, economic feasibility and the environmental impacts. This tool is applied in Jordan as a case validation. This is done using single figure of merit (SFOM) optimizations. A mathematical modeling is developed for each component, and the optimal configuration is determined for each city. The annual system cost of energy (ASCE) is optimized to be 32.57% less than the grid energy price, and the CO2 emissions are reduced by 80.13%. These are excellent indications for the economic feasibility and the environmental benefits of the designed system. The levelized cost of energy (LCOE), total net present cost (TNPC), renewable penetration (RP) and annual emission indicator (AEI) are 0.058212 $/kWh, $8.713857 billion, 59.49817% and 4.576 Megatonne/year respectively. Multi-figure of merits (MFOM) optimization cases based on a non-sorting genetic algorithm (NSGA) are investigated such as: AEI vs. ASCE, AEI vs. LCOE, AEI vs. RP and (RP, LCOE, AEI). The MFOM optimization results are either 2D or 3D Pareto frontier, where exists various competitive non-dominant solutions. The sweet spot selection (triple-S) procedure is proposed to help select the sweet spot in the two figure of merits Pareto frontier in order to have both environmental and feasible solutions. This design tool will be versatile enough for the application to any on-grid renewable power system worldwide. It will be made available on the internet as a public service of Texas A&M University Renewable Energy Program at the Power Electronics and Motor Drives Laboratory of the Electrical Engineering Department.