The increment integration of renewable distributed energies means the desired operation of the electric power system will significantly depend on the performance of primary energy. In this order, an integrated approach for mutual interaction between the electricity and natural gas systems has been considered for the purpose of ensuring optimal energy exchanging between the electric power system...

in this paper, a model based on gmdh type neural network, is used to predict gas price in the spot market while using oil spot market price, gas spot market price, gas future market price, oil future market price and average temperature of the weather. the results suggest that gmdh neural network model, according to the root mean squared error (rmse) and direction statistics (dstat) statistics ...

compressibility factor and viscosity of natural gasses are of great importance in petroleum and chemical engineering. to calculate the natural gas properties in the pipelines, storage systems and reservoirs, the exact values of gas compressibility factor and viscosity are required. a new method that allows accurate determination of compressibility factor and gas viscosity for all types of: swee...

Sustainable supply chain has become an integral part of the corporate strategy. In this paper, a real case study of the natural gas supply chain has been investigated. Using concepts related to natural gas industry and the relations among the compo-nents of gas and oil wells, refineries, storage tanks, dispatching, transmission and distribution network, a seven-level supply chain has been intro...

Power-to-gas is a promising option for storing interment renewables, nuclear baseload power, and distributed energy and it is a novel concept for the transition to increased renewable content of current fuels with an ultimate goal of transition to a sustainable low-carbon future energy system that interconnects power, transportation sectors and thermal energy demand all together. The aim of thi...

Prediction of viscosity of natural gas is an important parameter in the energy industries such as natural gas storage and transportation. In this study viscosity of different compositions of natural gas is modeled by using an artificial neural network (ANN) based on back-propagation method. A reliable database including more than 3841 experimental data of viscosity for testing and training of A...

In this paper we present an algorithm for the valuation and optimal operation of natural gas storage facilities. Real options theory is used to derive nonlinear partial-integro-differential equations (PIDEs) for the valuation and optimal operating strategies. The equations are designed to incorporate a wide class of spot price models that can exhibit the same time-dependent, mean-reverting dyna...