Gas generation has been the preferred non-renewable generation technology during the last few years due to its high efficiency, low emission,... Show moreGas generation has been the preferred non-renewable generation technology during the last few years due to its high efficiency, low emission, and good flexibility. As a result of increasing gas usage by gas fired power plant (GFPP), gas pipeline congestion becomes a big issue for GFPP. As non-electric natural gas consumers have higher priority in pipeline capacity usage, GFPP’s profit could be negatively impacted when non-electric gas consumption is extremely high. Natural gas storage directly connected to GFPP can supply gas when pipeline capacity is constrained. This thesis presents a model of evaluating the benefit of gas storage to GFPP. The model is formulated as a mixed-integer quadratic programming (MIQP) problem and solved using a commercial MIQP solver. A case study on one GFPP owning 4 natural gas generators is performed based on this model. It is observed that GFPP with gas storage directly connected can make more profit than GFPP without storage. A sensitivity study is conducted to analyze the relationship between the optimal gas storage capacity, as well as GFPP profit, and electricity price, non-electric gas consumption, and gas pipeline contract price. It is observed that the optimal gas storage capacity increases when electricity price increases and available pipeline capacity declines; however it does not change with the variation of gas pipeline contract price. It is also observed that the maximum profit of GFPP is most sensitive to electricity price, then non-electric gas consumption, and is least sensitive to gas pipeline contract price. The main application of this model is to help GFPP owner determine whether or not to install gas storage and, if yes, what the optimal capacity of gas storage should be. In addition, this model can also help GFPP owner plan gas purchase and gas pipeline capacity contract volume. M.S. in Electrical Engineering, December 2014 Show less
