Development of an expert system for optimizing natural gas pipeline operations

Artificial intelligence for monitoring and supervisory control of process systems

“…Currently, expert systems have been adopted in many industrial applications, including equipment maintenance, diagnosis and control, plant safety, and other areas in engineering. For example, Srihari (1989) discussed a framework of knowledge-based system in industrial applications, using it for the tasks of diagnosis, supervision, and control; Xia and Rao (1999a, b) built an expert system for operation support of pulp and paper manufacturing industries; Sun et al (2000) and Uraikul et al (2000) developed an expert system for optimizing natural gas pipeline network operations; Kritpiphat et al (1998) implemented an expert system for intelligent monitoring and control of municipal water supply and distribution; Norvilas et al (2000) developed an intelligent process monitoring and fault diagnosis environment by interfacing knowledge-based systems with multivariate statistical process monitoring techniques; Rao et al (2000) developed an intelligent system for operation support for a boiler system and a chemical pulping process; Viharos and Monostori (2001) developed a hybrid system combining expert system and simulation for optimizing process chains and production planning; Wang et al (1998Wang et al ( , 2000 described the combination of expert system with neural networks for fault diagnosis of a transformer; and Prasad et al (1998) applied the technology for constructing an operations support system for diagnosis and maintenance of a fluidized catalytic cracking unit and a paraxylene production unit. Fig.…”

A comparison of automation techniques for optimization of compressor scheduling

“…The problem of compressor schedule optimization has been previously tackled using the expert system approach and reported in [22,24], so it will only be briefly presented here. The expert system addressed three tasks: (1) to determine the state of the current line pack to decide if compression needs to be added or reduced, (2) to determine the required brake horsepower (BHP), and (3) to select the combination of compressors from the two stations to meet the BHP requirement with minimal cost.…”

Applications of artificial intelligence for optimization of compressor scheduling

“…Instead, a heuristic method for calculating the required BHP, which can be used as a proxy for customer demand, was adopted in this study. According to Sun et al, 2000 andUraikul et al, 2000, the BHP requirement for satisfying customer demand can be estimated using flow rates from the two gas stations with the following heuristic equation:…”