(89e) Optimum Operation of Complex Combined Heat and Power Systems of Two Parallel Gas Facilities | AIChE

(89e) Optimum Operation of Complex Combined Heat and Power Systems of Two Parallel Gas Facilities

Authors 

Al-Utaibi, D., Saudi Aramco
Al-Dandan, H., Saudi Aramco

In the oil and gas industry, the energy demands of heat, steam, power and fuel is highly dependent to the oil or gas processed by the facility. The utilities’ system design for those facilities normally built to account for the maximum operating rates. However, the plants sometimes operate at partial loading and because of the reliability constraints, boilers operate at minimum loading resulting to having some wasted steam passing over finfan condensers. Current models for optimizing the operation of utilities’ systems (Combined heat and Power Models) of a facility were being developed to look at the available operational modification changes in a facility yields to better performance, but in the partial loading the operational modifications are limited and sometimes not available. Partial loading leads to high energy consumption and wasting of valuable energy even with using optimization tools sometimes. In this paper, a new optimization technique is being introduced so that the overall energy consumption for the whole system of parallel facilities would be minimized. The idea here is basically extending the boundary of the optimization problem from a facility level a lone to optimizing a system of similar facilities. In house models were being built to come up with our findings. The complete set of models developed composed of: (2) Standalone models for utilities optimization (CHP optimization models) for each facility interacting with a planning model for allocating oil and gas production to each facility to meet certain oil and gas production needed. Energy correlations to relate energy requirements of a facility with the amount of gas or crude processed. These correlations were built using historical data of actual operation of those facilities. The analysis resulted in around 3% to 5% more energy savings compared to individual plants optimization.