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ABSTRACT APO reduces the amount of fuel used in compressor stations of transmission pipeline systems, thereby significantly reducing cost. APO phase 2 emulates transient optimization by incorporating "Black Box" logic, Transition and Administrative Tools. Of significance in the Administrative Tools package is "Measurement," where accurate cost savings are identified and validated through "Calibration" an automated method ensuring the coefficients of the modeling programs are properly "tuned." The APO process combines known engineering technologies into an on-line operational tool that minimizes fuel used in compressor stations by 10 to 15 percent. Chapter 1: Where we've been Background of System Initial APO has been operational since late 1999. Its purpose is to minimize fuel usage at compressor stations while operating the pipeline within required engineering and contractual constraints. APO is a process, which combines the software technologies of SCADA (Supervisory Control and Data Acquisition), steadystate fuel optimization and a model based supervisory controller working in conjunction with field compressor logic (Figure 1). Benefits of initial system The optimization software (Figure 3):Provides realistic fuel-efficient compressor configurations. It's an excellent product which determines the optimal stations to run and what type of compressor unit, by size, to operate. Provides realistic fuel-efficient discharge pressure targets. It's interesting to note that these solution targets are not necessarily intuitive. Provides the above stated optimal targets within programmed engineering and contractual constraints. Provides a fuel usage target to be used for measurement purposes. The advanced controller software:Handles "common" upsets (transients) and dynamics of supplies and deliveries. It's also an excellent product that "smoothes" the operation of the compressors' discharge pressures (optimal targets) by controlling the downstream stations suction pressure. Controls the compressor set points relatively close to the optimal steady-state targets. Automatically takes corrective action if a compressor stops. Provides the above stated supervisory controls within programmed engineering and contractual constraints. The initial system:Achieves increased fuel-efficient operations but was not well documented. Deficiencies of the initial system Larger upset conditions of supplies and deliveries usually led to high discharge pressures at the stations. Gas Control Operators would have to manually balance a "tight system." "Transition" (the process of shifting the pipeline 1 See "Figures" for enlargements of all exhibits system to a new optimal solution, usually involving a change in the configuration of units running) was deactivated due to inappropriate methodology of the algorithms. Deactivation of Transition led to inefficient fuel consumption during the change process and/or timing problems to accept increased supplies. The pipeline system, on occasion, had too high a pressure to accept an increase in supplies on a timely basis. Measurements of results were not captured. We didn't know conclusively what initial APO saved the company in fuel efficiency. No tools existed to aid the engineer in calibration of the models. Not user-friendly to expand the product throughout the DTI system. The system required weekly re-booting.
ABSTRACT Natural gas is increasingly being used as an energy source. Natural gas transmission pipelines transport large quantities of natural gas across long distances. They operate at high pressures and utilize a series of compressor stations at frequent intervals along the pipeline to move the gas over long distances. The operating costs of transmission pipelines can be significant because of compressor station fuel costs, emission minimization, etc. The analysis of these pipelines is very complex. This paper details techniques that can be used to determine optimal operating regions, schedule changes to move the pipeline from one optimal state to another, and automatically implement these changes using model predictive controllers. The optimal operating conditions that meet all constraints and minimize fuel consumption for the pipeline are determined by deciding (1) which compressor units need to be run at each compressor station and (2) the best suction pressure set point for each compressor station. The optimizer used is capable of running through a multitude of cases. It then selects the most optimal unit allocation and pressure profile found. Automated controls designed to move a pipeline towards optimal conditions are a very new feature in the process control industry and non-existent in the gas pipeline industry. Each controller sets the conditions, if necessary, for a unit to come on or go off. Each controller then moves a segment of the pipeline from one set of optimal conditions at one flow to the next set of optimal conditions at the new flow. Process limitations are considered and the Scheduler provides a transition schedule to facilitate the flow change gracefully. The Gas Dispatcher either approves or rejects the schedule. Upon approval, the controllers, over a few hours, move the pipeline to the new set of optimal conditions for the new flow with the correct allocation of units. If necessary, whole stations are brought up or down. INTRODUCTION On September 17, 1898, for a fee of $61, West Virginia's secretary of state granted Standard Oil of New Jersey a certificate of incorporation for the Hope Natural Gas Company. Now, 101 years later, the transmission pipeline segment of Hope, after many organization changes, has evolved into CNG Transmission Corporation (CNGT) a subsidiary of Pittsburgh-based Consolidated Natural Gas Company, one of the largest producers, transporters, distributors and marketers of natural gas in the United States. CNG Transmission Corporation (Figure 1) owns and operates 10,000 miles of pipeline, 68 compressor stations, 3,362 production wells, 1,510 storage wells in 15 storage pools, 300 pipeline interconnects, and an extraction and fractionating plant. All the above is operating by two busy Gas Dispatchers around the clock. Lebanon, Ohio to the Leidy hub located in north central Pennsylvania. It resulted from an agreement CNG Transmission had signed with the Transco Energy Company to provide 250 million cubic feet per day of firm capacity on the company's lines from the Texas Gas terminus at Lebanon to Transcontinental Gas Pipeline Corporation's Leidy line.
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