نشریه انرژی ایران
سال بیست و پنجم شماره 3 (پیاپی 96، پاییز 1401)

Nowadays, with the use of devices such as fossil distributed generation and renewable energy resources and energy storage systems that are operated at the level of distribution networks, the problem of optimal reconfiguration has faced major challenges, so any change in the power of this resources can have different results in reconfiguration. Similarly, load changes during the day can lead to different results in reconfiguration, so it is necessary to provide a model that dynamically considers the daily load and models the uncertainties in renewable energy resources. The main issue is the reconfiguration that the distribution system operator must consider in the next 24 hours. This paper presents a mixed-integer second-order cone programming model to solve the problem of stochastic dynamic reconfiguration in distribution networks by including fossil and renewable energy resources, battery, electric vehicle parking lots, and demand-side management programs. The objective is to reduce the cost of load curtailment, reduce the cost of losses, reduce the cost of purchasing energy and reduce the cost of cutting off the power of renewable energy resources. The 33-bus distribution network is presented by defining different cases for the analysis of the proposed model, the results of which show the efficiency of the proposed model.

The high power coefficient of the Darrius vertical axis wind turbine lift regime has prompted researchers to concentrate their efforts on this regime, despite the fact that these turbines suffer from major problems in the drag-lift regime. In the present study, in addition to exploring the performance of the Darrius type wind turbine at blade tip speeds above 1, the effect of design factors on its performance at TSRs below 1 is also investigated. The results were extracted from numerical analysis recruiting Fluent software and the k-w SST turbulence model. The effect of blade type, thickness, and chord length on turbine performance has been investigated. The blade angle at TSR less than one was calculated using a new equation, and the results were evaluated. The numerical simulation results showed that increasing the chord length for symmetric and asymmetric airfoils from 0.1 to 0.2 m enhances the turbine performance in drag-lift regime, whereas decreasing chord length improves turbine performance at higher TSRs. The blade with a curvature of 4% and a chord length of 0.1 m has the best performance at TSR 2.25. Increasing the thickness exerts a negative influence on the turbine's performance in both regimes, and at lower TSRs, NACA0018 airfoil with a chord length of 0.2 m was of the optimum performance in the drag-lift regime.

A novel scramjet multi-stage open cooling cycle for electricity and hydrogen co-production is proposed in which the fuel of scramjet is used as coolant of cooling cycle. Thermodynamic and exergetic examination of the advanced system have been conducted to appraise the system’s performance, electricity and hydrogen productions and multi-expansion effects. For the fuel mass flow rate of 0.4 kg/s, the cooling capacity of the new proposed cycle is computed 9.16 MW, the net electricity output is calculated about 3.38 MW and the hydrogen production is attained 42.16 kg/h. On the other hand, the exergetic results have proved the fact that PEM electrolyzer has the highest exergy destruction ratio by 44% among different components of the cycle. Moreover, the results of exergy analysis exhibited that employing the multi-expansion process concept outstandingly decline the overall exergy destruction of the system. In this case, the energy and exergy efficiencies of the overall set-up are acquired by 13.01% and 22.12%, correspondingly.

Due to the high share of electricity consumption in the country's industries, in recent years, various projects have been implemented, including reducing the amount of load by implementing nationwide blackouts during peak consumption times. Today, data mining is widely used as a process of discovering useful patterns from the database and one of the effective methods for analyzing, modeling and predicting energy consumption. In this study, an integrated clustering-association data mining model has been designed to investigate power consumption behavior to discover and extract the pattern from the power consumption data set of industrial units located in one of the industrial towns of Tehran province. Observations show that during the warm months of the year, the average consumption of high-consumption cluster units, which includes about 34% of the studied industrial units, is about 4.2 times the consumption of low-consumption clusters and about 1.7 times the consumption of medium clusters. By using the proposed model in this study, in addition to identifying high-consumption units and implementing smart and fair policies in forced shutdowns, it is possible to prevent damage caused by forced shutdowns and industrial units can be encouraged to optimize energy consumption. The innovative approach of this model is able to control large volumes of data for planning different areas with the aim of optimizing its energy consumption.

High energy consumption in Iran along with the high emission of air pollutants (local pollutants and greenhouse gases) are among the main problems in Iran's transportation sector. Nowadays, in the developed countries of the world, the use of low-consumption and low-emission cars, along with the use of fuel mixed with ethanol or the use of hybrid and electric cars, are on the agenda as ways to deal with the problems of the energy sector. In our country, due to the fact that most of the electricity produced is obtained from the burning of fossil resources, some believe that the use of electric cars will result in the emission of pollutants. Therefore, in this article, the analysis of wheel wells for all types of cars (internal combustion, electric and hybrid) in the country is discussed. In the discussion of electric cars, the amount of energy consumption and emission of pollutants in the production of lithium-ion batteries is also considered.