Majlesi Journal of Energy Management
Volume:11 Issue: 2, Jun 2022

The purpose of this paper is to investigate the effect of the location of heat sources on the heat transfer of natural displacement inside a rectangular chamber with fixed dimensions, the walls of which are well insulated. Inside the chamber, two high-temperature heat sources are located on the lower surface and a coolingsource near the roof with a gentle slope. The coolingsource temperature is considered to be zero degrees Celsius and the hot source temperature is assumed to be equal to 60 degrees Celsius. This geometry has been selected for the purpose of modeling long cooling tunnels in cooling-moving refrigerators. The coolingsource is considered as an evaporator and the hot source is equivalent to pallets containing hot materials (which are intendedfor cooling). Based on this goal, the dimensions of the problem are assumed to be about one room, the values of which are listed below. The parameters studied in this study are: distance of hot sources from each other, distance and angle of coolingsource which is modeled for several different values in Ensys Fluent software and the effect of changes in each parameter on the pattern of flow lines, temperature and heat transfer rate. The general result obtained for different modeling conditions of this problem shows that the total flow consists of six zones inside the chamber and each zonehas its own characteristics in terms of flow that if this system is used in systems Combined, the overall efficiency of the system will be greatly increased.

Iran is holding 33.5 billion cubic meters of gas, with an 18% share of oil and gas reservoirs worldwide. Productive hydrocarbon reservoirs are among the most important competitive advantages of Iran and a specific geographic location. In this study, the likely and credible future of Iran’s fossil energy (gas) on the horizon of 2035 is presented in the four-part state. Using the Maleki-Abbaszadeh-Norouzi (MAN) model, among the 300 scenarios, ten scenarios with the maximum adaptability were obtained, which is presented in two scenarios: The eternal blossoming and the Marshland. Moreover, projections show that Iranian gas production reaches 7.8 million barrels of oil equivalent per day in the eternal blossoming and 120 thousand barrels of oil equivalent per day in the Marshland scenario by 2035. This paper shows that the geopolitical status of the Middle East is highly effective in the gas industry

Artificial neural network (ANN) techniques have been recently suggested for short-term electric loadforecasting by a large number of researchers,This paper presents an artificial neural network(ANN) approach to electric load forecasting. The ANN is used to learn the relationship among past, current and futuretemperatures and loads. In order to provide the forecasted load, the ANN interpolates among the load andtemperature data in a training data set. The ANN load forecasting models are trainedon historical data that obtained from a real substation in Mashhadof Iran. Final results indicate averageerrors of developed models and prove that these models canbe applied to the prediction of load in real case.

Energy crisis is one of the issues that is of great interest to today's societies. Optimizing the energy system in terms of resource diversity and the size of each unit can greatly improve the economic and technical efficiency of the feeding system. In this paper, a feasibility study and also economic optimization for a systemindependent of the network for the central regions of Iran is presented (Case Study of Varzaneh Region). HOMER software has been used for measurement as well as optimization tools. Renewable and non-renewable energy sources (fossil fuels), energy storage methods, and the ability to use them on a cost-efficient basis. Sensitivity analysis is performed for wind speed, solar radiation and fuel costs. An agricultural farm with an energy consumption of 10 kWh/d and a maximum load of 1 kW load is considered as an autonomous load.

This article proposes a new modulation strategy that can minimize the stator current distortion and powers ripples for a doubly fed induction generator (DFIG) controlled by neuro-second order sliding mode controller (NSOSMC). The proposed five-level space vector modulation (5L-SVM) strategy is a hybrid technique which consists of 5L-SVM strategy and the intelligence technique (neural networks (NNs) and Fuzzy logic controller (FLC)). The former provides low current distortion and reduce powers ripples. On the other hand, the NSOSMC method with classical 5L-SVM strategy gives more powers ripples and harmonic distortion of stator current. For the proposed techniques, in the simulation region of neural space vector modulation (NSVM) technique, fuzzy space vector modulation (FSVM) is used to reduce the stator current distortion and powers ripples. Comparison ofsimulation results derived from a Matlab/Simulink software based controlled inverter is included. The work demonstrates that using the proposed hybrid 5L-SVM strategy, the three-phase current signals of the inverter can be reconstructed even under very low modulation index range while providing a low current harmonic distortion of the five-level inverter output

An adaptive hysteresis current controller for single-phase single-stage photovoltaic central inverters is presented. The designed controller is able to eliminate harmonic distortion and to control switching frequency and to inject the current into power grid with good power quality. The simulation model of the system is developed in SIMULINK/MATLAB environment. The controller is found effective in obtaining the desired goal when the switching frequency is adequately high which leads to the synchronization of power grid voltage and inverter current and near to unity power factor.