COST MINIMIZATION MODEL FOR GAS DISTRIBUTION NETWORK BY USING LINEAR PROGRAMMING METHOD

It is normal for gas production sites to be located far from consumers. The gas needs to be distributed to the users, usually located in the towns and cities. The normal practices in distributing gas from sources to consumers are using the gas pipeline. Since the distribution cost is high, an important issue is to minimize the cost of distribution. Mathematical programming and spreadsheet modeling are used to minimize the distribution cost. This study presents a linear programming model to minimize the gas distribution network cost from production sites to consumers. The model considers the capacity of gas produced at the production sites, the capacity of receiving and refining of gas at the refinery stations, the capacity of compressor stations and the amount of consumer demands. The modeling consists of two models. The first model covers between production sites, refinery stations, and consumers. The second model covers between refinery station, compressor stations, and consumers. The models were based on unit cost and the quantities of gas distribution from the gas production sites to the consumers through refinery stations and compressor stations. The constraints for the models consist of the capacities of production sites, refinery stations, compressor stations and the quantities of consumer demands. The spreadsheet model was used to solve the models by using the case study data. Iranian natural gas network was used as a case study. The case study comprises 16 active gas production sites, seven gas refinery stations, four compressor stations and 24 cities. The data of the gas network of Iran was acquired from Iranian Natural Gas Company. Comparison between the models and case study revealed the cost of gas distribution for the first model could save approximately 21 percent of the actual cost. For the second model, the case study shows saving of 23 per cent from that of actual. The models could be useful to analyze the cost of distribution from production sites to consumers incorporating the refineries and compressor stations capacities. These models also could be adapted for water and oil distribution network with minor adjustments