Optimization of Fuel Consumption in Compressor Stations

Abstract

Natural gas passing through pipelines is transported by means of compressor stations that are installed in pipeline-network systems. These stations are usually installed at intervals greater than 60 miles to overcome pressure loss, and typically, they consume approximately 3 to 5% of the transported gas, making the problem of how to optimally operate the compressors driving the gas in a pipeline network important. The objective function of the optimization model is a nonlinear mathematical relationship. The model has been studied to minimize the fuel consumption in the compressor stations and to obtain suitable decision-making variables. Genetic algorithms are used as the optimization methodology, and the software program Lingo (Thompson 2011) is used to compare the optimization results. Two cases of centrifugal compressor stations with different performances are studied. The optimization model aims to improve the fuel consumption of the compressor stations in the pipeline network according to the conditions of the transmissions.

Optimization of a gas network fuel consumption with genetic algorithm

“…The presence of compressors in a loop means the summation of pressure loss for a loop would not be zero and it resulted in inadequate flow distribution, therefore the fitness function to determine flow should be studied for a better representation. The results from the optimization of Gas network two, agrees with other study that compressor speed is useful for fuel consumption minimization such studies include by Elshiekh (2015, by Zhang and Wu (2015), Zhang and Liu (2017), from Li et al (2011). And disagrees partially with the study of Habibvand and Behbahani (2012) because the summation of pressure drop for each compressor station loop is unsuitable to find the optimum flow flit among the compressor inlets.…”

“…• Agreement with results of Elshiekh (2015) which involved optimization of two compressor station with GA to obtain the optimal speeds of all six active compressors simultaneously, and consequently to obtain the minimum fuel-consumption rate subject compressor constraints. Similarly, from the optimization using GA on gas network two, the compressor speeds and fuel consumption were optimized, but the gas flow requires an improved algorithm.…”

“…Likewise, Elshiekh (2015) used GA to minimize the fuel consumption by optimizing the speed of two compressors stations each containing three compressors, the result was confirmed with results from Ling software. From the outcomes of GA and Lingo software, similar speed was obtained for the compressors in both stations.…”

“…The relationship between pressure loss and flow rate is described by flow equations, which is used to determine the pressure loss for a pipe segment. Mohring et al (2003) described the flow equation in equation (1), while Ekhtiari et al (2019), divided the flow equation into two, the first part was without elevation as shown in equation (2) and the elevation may be ignored if it is assumed as horizontal. In this paper, the flow equation will consider all the parameters in equations (1) and (2) except the numeric constant, all units will be converted to S.I units.…”

The method for optimisation of gas compressors performance in gas storage systems

“…Wong and Larson (1968) minimise the total fuel cost incurred by compressor stations via dynamic programming. The application of a genetic algorithm for optimisation of compressor gas performance is presented by Habibvand and Behbahan (2012), Elshiekh (2014) and Hawryluk et al (2010). Zhang and Wu (2015) discusses data from minimisation of compressor energy cost by means of modified genetic algorithms.…”