In the last decade, Poland has become one of the most active markets for unconventional hydrocarbon deposits exploration. At present, there are twenty concessions for the exploration and/or discovery of reserves, including shale gas. The area covered by exploration concessions constitutes ca. 7.5% of the country’s area. Four main stages can be distinguished In the shale gas development and exploitation project: the selection and preparation of the place of development of the wells, hydraulic drilling and fracturing, exploitation (production) and marketing, exploitation suppression and land reclamation. In the paper, the concept of cost analysis of an investment project related to the exploration and development of a shale gas field/area was presented. The first two stages related to the preparatory work, carried out on the selected site, as well as drilling and hydraulic fracturing were analyzed. For economic reasons, the only rational way to make shale gas reserves available is to use horizontal drilling, either singly or in groups. The number of drilling pads covering the concession area is a fundamental determinant of the development cost of the deposit. In the paper, the results of the cost analysis of various types of reaming method with an area of 25,000,000 m2 were presented. Cost estimates were prepared for two variants: group drilling for three types of drilling pads: with three, five and seven wells and for single wells. The results show that, as the number of horizontal wells increases, the total cost of the development of the deposit is reduced. For tree-wells pad, these costs are 7% lower than in the second variant, for five-well pads they are 11% lower, and for seven-well pads they are 11.5% smaller than in the second variant. Authors, using applied methodology, indicate the direction of further research that will enable the optimization of shale gas drilling operations.
This paper presents the resolution of the optimal reactive power dispatch (ORPD) problem and the control of voltages in an electrical energy system by using a hybrid algorithm based on the particle swarmoptimization (PSO) method and interior point method (IPM). The IPM is based on the logarithmic barrier (LB-IPM) technique while respecting the non-linear equality and inequality constraints. The particle swarmoptimization-logarithmic barrier-interior point method (PSO-LB-IPM) is used to adjust the control variables, namely the reactive powers, the generator voltages and the load controllers of the transformers, in order to ensure convergence towards a better solution with the probability of reaching the global optimum. The proposed method was first tested and validated on a two-variable mathematical function using MATLAB as a calculation and execution tool, and then it is applied to the ORPD problem to minimize the total active losses in an electrical energy network. To validate the method a testwas carried out on the IEEE electrical energy network of 57 buses.
Accurate network fault diagnosis in smart substations is key to strengthening grid security. To solve fault classification problems and enhance classification accuracy, we propose a hybrid optimization algorithm consisting of three parts: anti-noise processing (ANP), an improved separation interval method (ISIM), and a genetic algorithm-particle swarm optimization (GA-PSO) method. ANP cleans out the outliers and noise in the dataset. ISIM uses a support vector machine (SVM) architecture to optimize SVM kernel parameters. Finally, we propose the GA-PSO algorithm, which combines the advantages of both genetic and particle swarm optimization algorithms to optimize the penalty parameter. The experimental results show that our proposed hybrid optimization algorithm enhances the classification accuracy of smart substation network faults and shows stronger performance compared with existing methods.