Optimal Design and Operation of Energy Polygeneration Systems by

Polygeneration is a concept where multiple energy products are generated in a single plant by tightly integrating multiple processes into one system. Compared to conventional single-product systems, polygeneration systems have many economic advantages, such as potentially high profitability and high viability when exposed to market fluctuations. The optimal design of an energy polygeneration system that converts coal and biomass to electricity, liquid fuels (naphtha and diesel) and chemical products (methanol) with carbon dioxide (CO2) capture under different economic scenarios is investigated. In this system, syngas is produced by gasification of coal and/or biomass; purified by a cleaning process to remove particles, mercury, sulfur and CO2; and then split to different downstream sections such as the gas turbine, FT process and the methanol process. In this thesis, the optimal design with the highest net present value (NPV) is determined by optimizing equipment capacities, stream flow rates and stream split fractions. The case study results for static polygeneration systems reveal that the optimal design of polygeneration systems is strongly influenced by economic conditions such as feedstock prices, product prices, and potential emissions penalties for CO2. Over the range of economic scenarios considered, it can be optimal to produce a mixture of electricity, liquid fuels, and methanol; only one each; or mixtures in-between. The optimal biomass/coal feed ratio significantly increases when the carbon tax increases or the biomass price decreases. An economic analysis of the optimal static polygeneration designs yielded a slightly higher NPV than comparable single-product plants. The flexible operation is then considered for the energy polygeneration system. In real applications, product prices can fluctuate significantly seasonally or even daily. The profitability of the polygeneration system can potentially be increased if some operational flexibility is introduced, such as adjusting the product mix in response to changing market prices. The major challenge of this flexible design is the determination of the optimal trade-off between flexibility and capital cost because higher flexibility typically implies both higher product revenues and larger equipment sizes.