فصلنامه مهندسی و مدیریت انرژی
سال دهم شماره 3 (پیاپی 37، پاییز 1399)

This paper presents a reliability assessment algorithm for radial distribution systems such as microgrids and distributed generation units. The effects of these units and system reconfigurations on distribution system reliability can be evaluated by using the proposed algorithm. The impacts of the location and capacity of the distributed energy resources of microgrids and sectionalizing switches on reliability indices are determined. Moreover, proper location is determined by the classification of load points in distribution system. An approach to identifying the out of the service section after a fault event is presented based on the adjacency matrices. The classification of nodes is obtained by identifying different adjacency matrices based on protective devices. At last, the reliability indices of radial distribution system are calculated.

Flexible AC transmission systems (FACTS) devices have shown efficient capability in alleviating the problems of power systems. The aim of FACTS devices allocation is determining the type, location, and the appropriate characteristics of these devices in order to improve the power system technical parameters. This problem is a non-linear optimization problem with many variables and constraints which requires the deployment of proper optimizing algorithms. Usually, the optimization problems are implemented in MATLAB or GAMS softwares. On the other hand, electric companies usually perform the power system studies in DIgSILENT software. Therefore, for the sake of optimization, it is required to export the power system’s data to optimizing softwares, which means a difficult and time-consuming task for the engineers. In this paper, a discrete particle swarm optimization algorithm (DPSO) is employed for the optimal allocation of FACTS devices on Gilan regional electric company’s (GilREC) network. The DPSO algorithm has been programmed in DPL (DIgSILENT Programming Language) environment of DIgSILENT software so that there will be no need for data exchange between DIgSILENT and optimizing softwares. The obtained results verify the effectiveness of the proposed methodology in power flow control and the improvement of system’s technical parameters.

Resilience is defined as the system ability both to keep an acceptable performance level against a severe disturbance and to return to a stable condition in a suitable time. Occurrence of inconvenient weather conditions and natural disasters, which are growing in numbers and severity during the last years, has always led to damages and wide outage throughout the distribution network. Therefore, the assessment of distribution network resilience and its return ability against severe weather condition and the reduction of the vulnerability of distribution network against those events should take priority in the planning and operation of these networks. In this paper, the resilience concept and its characteristics are determined; afterwards, by modeling natural disasters such as flood and storm, a new index for resilience assessment of distribution networks in the presence of distributed generators is introduced. The proposed model has been applied to a real network and the effects of distributed generators on the resilience of distribution networks have been studied using the new introduced index.

Specialists in the field of oil and gas such as reservoir engineers, geologists, and geophysicists have found that achieving optimal or maximum production returns is essential to the success of the oil industry and should be considered as one of the most important macroeconomic policies of the country. The need to improve the recovery of a large volume of residual oil and gas in hydrocarbon reservoirs, along with global competition for further  production, demands  reservoir management for planning in this area as well as an accurate determination of  the production strategy. Such special attention to these issues and the future of the development of related technologies will, thus, lead to the production of such resources and the targeted ones. A clearer and more accurate understanding of the flow of fluid in the porous environment during the harvesting of hydrocarbon reserves is one of the important issues in the steady production of the countrychr('39')s oil and gas industries. In this research, various technologies in simulating flow in a porous environment have been analyzed, yet the application of the superior technology for simulation of the Boltzmann network using X-ray tomography, having recently attracted attention of the scientific communities in the field of computational fluid dynamics, has been domenstrated. For this Purpose, the geometry of the porous medium was entered into a computational code using a text file, and the flow of the natural gas cavity was solved directly on 3D geometry using the Boltzmann grid model with multiple repositioning time. In this way, the permeability of the present porous media was calculated in a ratio of different pressures. The results of the simulation comply satisfactorily with the experimental and numerical results presented in the related technical texts.

Climate change and the increase in population of countries have foregrounded the importance greenhouses for future food security. One of the most important considerations in greenhouse production is the need for energy to create suitable greenhouse conditions. Therefore, this paper will investigate the problem of greenhouse energy planning with a focus on renewable energies. To this end, at first, the optimal numbers of renewable energy units and storage units are modeled in order to reduce costs in the micro-grid mode. Afterwards, it analyzes the proposed mixed integer nonlinear problem (MINLP) by using the average wind speed data and the monthly amount of sunlight in the Makran region and by considering different combinations of parameters Cost-wise in 16 different problems. One of the most important results drawn is the determination of the cost-effectiveness of solar energy utilization, which is economically justified, if the investment cost is twice as high as the CHP investment cost. The results also show that the impact of different renewable energy sources in the geographical area-- studied along with the costs of their investment and maintenance costs-- can lead to the unjustifiable technical-economic use of different renewable resources.

In recent years, due to the limitation of fossil fuels and the environmental impacts of using such fuels, focusing on renewable energy sources has significantly increased. In developed countries, using clean energy such as wind power has been considered as an alternative source. Monitoring the performance of wind turbines and controlling their output power quality is one of the important issues for managing wind farm. One of the influential characteristics of a wind turbine is the power curve which depicts the relationship between output power and hub height wind speed. Therefore, accurate models of power curves can play an important role in improving the performance of wind-energy-based systems. Hence, this paper has carried out the parametric techniques for power curve modeling. First, the following parametric equations are introduced to represent the power curves of wind turbines: polynomial power curve, exponential power curve, cubic power curve and approximate cubic power curve. Next, the models have been applied to a wind turbine, and, then, they were compared with manufacturer’s normal power curves by using the goodness of fit test. The results have shown that the exponential method for modeling of power curve is more desirable compared with three other models.

Solar energy is a desirable type of renewable energies. However, it should be stored due to the sun radiation discontinuity. Phase-change materials (PCMs) store the thermal energy through their phase transitions, and the optimization of their thermal properties leads to more efficient thermal storage. In this study, paraffin wax was used as a PCM and aluminum oxide, and copper nanoparticles were used to improve its thermal properties. The morphology of the nanocomposites was studied with Field Emission Scanning Electron Microscopy (FESEM). Experiments were conducted in a factorial arrangement in a completely randomized design with three main factors, including: the weight percentage of nanoparticles (three levels), the type of nanoparticles (two levels), and the size of the nanoparticles (three levels), and pure Paraffin wax as a control sample. The melting point and the latent heat of each sample were measured with differential scanning calorimetery (DSC). The results showed that by an increase in nanoparticles concentration, the melting point of nanocomposites decreased slightly. On the other hand, the type and size of nanoparticles had no significant effect on the melting point. The addition of nanoparticles increased the latent heat of nanocomposites noteworthy in an optimal concentration. With a decrease in the nanoparticles size, the latent heat of nanocomposites increased. The nanocomposite sample which was filled with copper nanoparticle at the concentration and size of 1% and 30 nm respectively, had the highest latent heat.

Reducing building energy consumption is one of the sustainable architecture principles. Since nearly half of consumed energy in the buildings is lost through windows, many studies have been conducted to find solutions for energy conservation and solar radiation control. Application of electrochromic smart glass is one of those solutions. In order to have optimum building selection, the evaluation of the effectiveness of this type of glasses in various climates in Iran is necessary. So far no research has been conducted on this issue. In the present study, the effect of using electrochromic smart glass on the cooling load of an office building is investigated in three cities of Bushehr (with hot-humid climate), Shiraz (with hot-dry climate), and Tabriz (with cold climate). For this purpose, a three-storey office building is simulated in Design Builder software and the annual cooling load of the building is calculated in three modes with 6mm plain glass, double-glazed glass and electrochromic smart glass. The results show that in Bushehr, Shiraz, and Tabriz, the application of electrochromic glass has a significant effect on the reduction of cooling load and, thus, is appropriate. In Bushehr, the application of electrochromic glass has reduced the cooling load of the building by 19% and 8% compared with the ordinary glass and the double-glazed one, respectively. In Shiraz and Tabriz, the cooling load also decreases by 28% and 10%. These results show that the efficiency of electrochromic glass in hot-dry and cold climate is higher than hot-humid climate.

Producing potable water is a challenge for Middle Eastern countries including Iran. Hence, desalination technology has become one of the interesting subjects for researchers, especially in the last decade. In this field, capacitive deionization (CDI) has increasingly been studied. Advantages such as low energy usage, low cost, and smaller footprint, in fact, have made studies on such systems unavoidable. In recent years, throughout the world, many experimental studies have been conducted, and, thus, some sub models have been suggested and developed based on EDL theorem for adsorption of ions. However, in Iran, in spite of water crisis, no serious study has been reported on the capacitive desalination. In the first part of the present study, the apparatus for the capacitive desalination is introduced, and studies in this field are reviewed. In the second part, the results of an experimental feasibility study on coupling of flow-electrode CDI (FCDI) to solar energy is presented. In this regards, the FCDI cell is introduced. This study deployed solar panels directly to provide the energy required for the adsorption of ions. The results show that sea water is desalinated up to 50% in the first step by connecting a 2 W solar panel to an open mode FCDI;   afterwards, to achieve drinkable water, it was processed for 1 hour under a 0.75 W solar panel in a batch mode.

In the present paper, a two-phase simulation of atmospheric aerosol (air, pollution, fine particles of dust, and vehicles pollutants) is carried out to investigate the pollutants dispersion and heat transfer (conduction-convection-radiation) in urban street canyons under haze-fog conditions. Numerical calculations were considered for four time periods during the day, including: 10 am, 1 pm, 4 pm, and 8 pm on the first days of April, July, October, and January. For this purpose, Computational Fluid Dynamics (CFD) method and the simulation are used and dynamic characteristics of airflow and heat transfer have been obtained. The results show that the trend of the ground temperature variation in different months is the same and the maximum value of it has always occurred at 1 pm. In addition, in all the hours and months that examined in the present study, the natural convection for the fluid flow than the forced convection is insignificant, and the main of the fluid flow and pollutants is due to the wind velocity at the inlet boundary condition and the pollutants velocity. In cases with higher windward wall and small aspect ratio between buildings and street, the lowest pollutant concentration in passengerchr('39')s level is achieved.