Multi-objective optimizations were conducted for a compressor station comprising two dissimilar compressor units driven by two dissimilar gas turbines, two coolers of different size, and two parallel pipeline sections to the next station. Genetic Algorithms were used in this optimization along with detailed models of the performance characteristics of gas turbines, compressors, aerial coolers, and downstream pipeline section. Essential in these models is the heat transfer between the gas and soil as it affects the pressure drop along the pipeline, and hence relates back to the coolers and compressor flow/pressure settings. Further investigative techniques were developed to refine the methodology as well as to minimize the downstream gas temperature at the suction of the next station. Current operating conditions at the station were compared to the optimized settings, showing that there is room for improving the efficiency of operation (i.e. lower energy consumption) with minimum effort on the station control strategy. Two threshold throughput conditions were determined in so far as single vs. multi-unit operations due to the dissimilarity in the compressor units and associated gas turbine drivers. The results showed that savings in the energy consumption in the order of 5–6% is achievable with slight adjustment to unit load sharing and coolers by-pass/fan speed selections. It appears that most of the savings (around 70–75%) are derived from optimizing the load sharing between the two parallel compressors, while the balance of the savings is realized from optimizing the aerial coolers settings. In particular, operating the aerial coolers at 50% fan speed (if permitted) could lead to substantial savings in electric energy consumption in some cases.

Multi-objective optimizations were conducted for a compressor station comprising two dissimilar compressor units driven by two dissimilar gas turbines, two coolers of different size, and two parallel pipeline sections to the next station. Genetic algorithms were used in this optimization along with models describing the performance characteristics of gas turbines, compressors, aerial coolers, and downstream pipeline section. Essential in these models is the heat transfer between the gas and soil as it affects the pressure drop along the pipeline, and hence relates back to the coolers and compressor flow/pressure settings. Further investigative techniques were developed to also minimize NOx and CO2e emissions along with total energy consumption, i.e. fuel (used in the driver gas turbines) and electrical energy (used in the electrical fans of the aerial coolers). Two optimization scenarios were conducted: 1) Two-objective optimization of total energy consumption and NOx emission, and 2) Two-objective optimization of total energy consumption and CO2e emission. The results showed that savings in the energy consumption in the order of 5–6% is achievable with slight adjustment to unit load sharing and coolers by-pass/fan speed selections. It appears that most of the savings (around 70–75%) are derived from optimizing the load sharing between the two parallel compressors, while the balance of the savings is realized from optimizing the aerial coolers settings. In order to optimize operation for minimum NOx emission as well, a shift towards employing more of the aerial coolers is required. Preliminary cost analysis was conducted for valuation of balancing between energy consumption vs. emission loading in terms of both NOx and CO2e.

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Effective purging of air out of a pipeline section before commissioning by direct displacement with natural gas has been safely practiced for decades with the recognition that flammable interfacial mixing zone between the driving gas (behind) and the air (ahead) is inevitable. In cases when the purge velocity is below a threshold dictated by the gravity current velocity (defined in AGA Purging Principles and Practices, 2001), natural gas being lighter than air can in fact ride over air being the heavier gas and short circuit the flow path to the vent at the other end of the pipe section, thus trapping behind pockets of air that could potentially introduce risk of internal explosion with subsequent damage to the pipe section and pose a safety issue to field personnel. Therefore, maintaining the purge velocity above this threshold by a good margin has been a common practice in the purging procedure to-date. In fact, maintaining the purge velocity above the threshold can be controlled by the injection press or flow, where tools and dynamic purging models have been successfully developed and proven to be useful. However, AGA recommends that the drive purge gas pressure be limited to 689 kPag (100 psig) in the inlet purge line to the pipe section to avoid the risk of detonation. In some cases when the inlet purge line is relatively small compared to the main pipe section, this limit on the purge pressure would result in gas/air interfacial velocity much lower than the threshold velocity, hence stratification will occur. This paper provides insight into the possibility of increasing the purge pressure above AGA limit to avoid stratification, while conforming to the safety aspects related to detonation. A purge model is developed to overcome the shortcoming in AGA purge software that limits the purge pressure to maximum of 689 kPag (100 psig). Field trial was conducted to validate the model which demonstrated, as a proof of concept, a successful purge procedure with purge pressure = 5517 kPag (800 psig) in NPS 1.5 purge line to purge nitrogen out of NPS 42, 5.8 km section of a pipeline.

Noise is generated at gas turbine-based compressor stations from a number of sources, including turbomachinery (gas turbines and compressors), airflow through inlet ducts and scrubbers, exhaust stacks, aerial coolers, and auxiliary systems. Understanding these noise sources is necessary to ensure that the working conditions on site are safe and that the audible noise at neighbouring properties is acceptable. Each noise source has different frequency content, and the overall sound pressure level (OSPL) at any location in the station yard or inside the compressor building is the result of a superposition of these noise sources. This paper presents results of multiple-point spectral noise measurements at three of TransCanada’s compressor stations on the Alberta System. A method is described to determine the overall noise map of the station yard using Delaunay Triangulation and Natural-Neighbour Interpolation techniques. The results are presented in OSPL maps, as well as animated pictures of the sound pressure level (SPL) in frequency domain which will be shown on a video at the conference. The latter will be useful in future work to determine the culprit sources and the respective dominant frequency range that contributes the most to the OSPL.