نشریه سیستم های انرژی پایدار
سال یکم شماره 1 (زمستان 1400)

Due to its availability, high efficiency, and low cost, wind energy plays a critical role in the transition from energy sources to renewable sources in order to achieve sustainable development. In many villages of Iran where the required electricity does not exceed a few kilowatts and relatively good wind potential exists in different seasons of the year, the application of micro wind turbines as an off-grid source for supplying electricity to these areas can be effective in reducing greenhouse gas emissions and diminish the usage of thermal power plants. numerical and computational methods are able to evaluate the performance of wind turbines while reducing the cost of fabrication and testing required and provide the opportunity for optimizing the geometry and design of turbine with higher efficiencies.. To this end, this study has utilized the computational fluid dynamics analysis to predict and improve the performance of a high-solidity vertical axis wind turbine.

The present study proposes a numerical simulation in Ansys 18 (commercial software), based on Computational Fluid dynamics (CFD) to predict the performance of a high-solidity, 3-blade, low-speed vertical axis wind turbine. In this regard, a two-dimensional fluid domain was generated, and a detailed meshing and a comprehensive mesh study were carried out. Various turbulence models were investigated and among them the Transition SST turbulence model showed the most acceptable results. Subsequently, other items including the boundary conditions, solver type, and time step were selected and optimized. To achieve a reliable solution to the problem and reduce the errors in the results, simulations were performed for 5 turbine rotation cycles.

Based on the results, The minimum and maximum torque of the turbine per unit length for 4th and 5th revolutions are -15.03 Nm and 45.33 Nm and the average is 10.80 N. The power coefficient and the output power of the turbine rises as the tip speed ratio (turbine rotational speed) increases, reaches its maximum value and then decreases. In order to validate the simulation results, respective curves based on simulation and experimental data are provided and the amount of deviations are investigated. Following the model’s results, The maximum turbine power coefficient is 0.29 at a blade tip speed ratio of 1.62, while laboratory data reports these values as 0.253 and 1.58. therefore, there is a 23.40% difference between experimental and model results in the maximum power coefficient. Moreover, the peak turbine power of the model occurs at a speed of 80 rpm, which is equal to 333.1 watts. However, laboratory data shows maximum turbine power as 290.6 watts at 100 rpm, which is 23.40% lower than the simulation result. According to the results, the two-dimensional simulation approach tends to overestimate the values compared to the actual data. Among the contributing factors to this inaccuracy are using 2D simulation and ignoring the gradient of velocity and pressure in the Z-axis, not considering the turbine’s axis and blade-axis connections in the fluid’s domain, not considering the blades tip vortices and interaction of vortices with blades in the third dimension. Since Supplying the electricity to off-grid areas in form of distributed generation by using renewable resources have been considered to be one of the main components of sustainable development in the field of energy, vertical axis wind turbines proposed in this study are viable alternatives to commonly used diesel generator for areas with appropriate wind potential.

Global energy demand is increasing for various reasons, including industrial development, economic growth, population growth, and lifestyle changes. On the other hand, fossil fuels cause many environmental problems, including global warming, climate change, ozone depletion, acid rain, water, and air and soil pollution. Incineration of fossil fuels since the beginning of the Industrial Revolution has emitted about 500 billion tons of carbon dioxide, about half of which remains in the atmosphere.

The faculty building consists of 4 floors. The total number of zones under the control of the faculty, which includes rooms, classrooms, workshops, laboratories, classrooms, toilets, and halls, is 152. The basement has 28 areas; the first floor has 39 areas, and the second and third floors have 34 and 51 areas, respectively. The peak load for the building's cooling needs during the year is 300 kW, and the maximum load required for heating is 155 kW. The faculty currently uses natural gas for heating and electricity for cooling systems.In this research, a vertical geothermal system is designed for this educational building. The pipes of the vertical geothermal system are of the borehole type and are wound vertically into the ground from top to bottom.By considering the standards of the systems and the fact that the maximum loads related to cooling and heating are 300 kW and 155 kW, respectively, the number of boreholes is 80. For this reason, the 80-hole geothermal heat pump system, which is also defined as standard in the software, is selected.

By installing the earth tube system in the building, the energy consumption of the building faces general changes. Figure 1 shows the energy consumption during a year while the geothermal system is responsible for providing the needs.As shown in Figure 1, the energy consumption of the geothermal system consists of three sections: fans, pumps, and cooling and heating sections. This whole new system uses less electricity, and by using geothermal energy, natural gas consumption is reduced to zero. Figure 9. Building energy consumption over a year (Earth tube system)The highest consumption is related to fans, and the lowest is related to pumps, equal to 92.07 and 3.36 MWh per year, respectively. The total energy consumption of this scenario is equal to 615.36 MWh per year, which produces 372.91 tons of carbon dioxide. By comparing the traditional system to this novel system, it is clear that the use of geothermal green energy has led to a significant reduction in energy consumption and carbon dioxide emissions. Total energy consumption decreased by 77.89 MW per year and carbon production by 20.83 tons.

This study aims to optimize energy consumption and reduce carbon emissions of buildings in Tehran province using a geothermal system. Therefore, the building of the Faculty of New Sciences and Technologies of the University of Tehran has been selected as the building under study. An 80-bore tube geothermal system installed vertically into the ground is designed for the building. The significant results of research and modeling are as follows:By using geothermal energy to provide the heating needs of the building, consumption of natural gas is reduced to zero.Replacing the traditional HVAC system and providing thermal comfort with the geothermal system is associated with a reduction in energy consumption of 77.89 MWh per year.The use of renewable geothermal energy reduces carbon production by 20.83 tons per year.

The fuel distribution network in the country has a vital role and is responsible for supplying the fuel chain from the refinery to the consumption stage at the refueling station. Due to the critical role of this network in providing the required fuel to vehicles, estimating the reliability and risk and the amount of unsupplied fuel in it is of particular importance. In this study, with the aim of evaluating the reliability of complex fuel distribution networks, a numerical model based on the route graph method in MATLAB software has been developed, and the fuel distribution network of Damavand city has been studied as a case study by the model. In this regard, first, the existing fuel stations in the city are identified and classified. While forming the general graph of the distribution network and naming its nodes, the communication lines between the stations are drawn according to common standards (supporting and adjacent stations), and the developed algorithm has calculated all the available routes from the source refinery to the destination sites. Finally, with the acquisition of the routes, the final assurance of fuel supply at the destination stations has been obtained. The results show that the fuel station "Velayat Abali " with 94% reliability has the minimum amount, and the fuel station "Besat" with 96% reliability has the maximum amount of reliability in the distribution network. Also, defining the configuration of supporting stations in the distribution network increases the reliability of the system.Introduction Reliability modeling and evaluation in distribution networks, including energy, water, and fuel distribution, has progressed significantly in recent years. The statistics show that water and energy distribution networks have the largest share in the unsupplied energy of subscribers. For example, power distribution networks contribute to consumer blackouts, and water distribution networks make a significant contribution to customer water outages. Energy and fuel networks may suffer from performance and failure due to various external and internal factors. External factors mainly include earthquakes, avalanches, special weather conditions, etc., and internal factors, depending on the type of network, are due to failure of control systems, manpower error and limited useful life of equipment. Due to the importance of maintaining network performance in such situations at the desired level, in recent years, several methods have been proposed to evaluate the performance of complex networks that express network reliability in conditions of uncertainty (critical conditions). Since energy and fuel distribution networks are generally complex systems, it is appropriate to use the concept of network equivalent graphs to simplify them.The primary purpose of this study is to introduce an algorithm to calculate the reliability of fuel distribution networks. Achieving this goal requires considering a range to generalize the proposed model and calculate the final reliability. In this regard, by considering the fuel distribution network in Damavand city as a case study, the final reliability of this network is calculated.

Numerous methods have been developed to calculate system reliability, especially in cases where the system cannot be considered in series. The most prominent methods developed are: conditional probability method, cut method, tree diagram method, logic diagram method, connection matrix method, and path graph method. Due to the appropriate approach of the path graph method and its ability to be developed in the software platform, this method has been used in the present study. In this method, all the paths that connect the system input to its output are considered and the reliability of each path is calculated; In other words, the conditions leading to the successful operation of the system are determined. This method is based on the concept of connection set; A connection set is a non-duplicate path of components, the failure of each of which leads to the failure of the connection set, and if any of the sets are in place, the system will function properly. Each set has a parallel connection with the other sets and its members are in series.

After determining the set of available routes developed by the algorithm and having the reliability of each fuel station, the overall reliability of the network is obtained according to Table 4. Table 4. Calculation of the final reliability of the fuel distribution network in Damavand citySelected route setReliabilityBreakabilityfuel not supplied (liters)Routes leading to station number 50.9402330.0597762988.4Routes leading to station number 60.9550310.0449691798.8Routes leading to station number 70.9581540.0418461673.8Routes leading to station number 80.9611560.0388441942.2  

 The summary of the results is as follows:Regarding the reliability of the fuel supply chain of the fuel station of Abali province, with 94% reliability, it has the minimum value. It is the critical point of the distribution network.Besat fuel station located on the south side of the central area with 96.1% reliability is the most reliable station in the fuel distribution network of Damavand city.The use of support stations and two-way communication between adjacent stations in the fuel supply management method increases the system's reliability.

Variable refrigerant flow systems are one of the most efficient and widely used air conditioning systems to reduce energy consumption while maintaining the desired level of thermal comfort. Variable refrigerant flow systems as an efficient and flexible solution for various heating/cooling applications are gaining more attention and are widely used in commercial and residential buildings. Variable refrigerant flow systems have many advantages over traditional air conditioning systems such as chillers and fan coils or air conditioning units, including satisfactory partial load performance, individual control capability at arbitrary temperature range, and no loss in duct transmission. Easy installation and maintenance. However, variable refrigerant flow systems require a dedicated outdoor air system with an additional ventilation unit.

This section first discusses the design of a variable refrigerant flow system. The next step is to model the building located in Cyprus with the heating system in question. The parts of this modeling include the characteristics of the selected location of the building, modeling of the relevant building, modeling of variable refrigerant air conditioning system and photovoltaic systems in detail.Variable refrigerant flow systemVariable refrigerant flow systems Among the various air conditioning systems is the DX system, based on the standard Rankin reverse steam compression cycle. Therefore, these systems are thermodynamically similar to conventional DX systems and have similar equipment such as compressor, expansion valve, condenser, and evaporator. Figure (1) shows the inside of the exterior of a variable refrigerant flow system that is installed outside the building.A 5-storey residential building with an area of ​​1061 square meters of space has been modeled in Design Builder software (on each floor, there are two residential units with ​​110 square meters). Each floor consists of two units with an equal area; the north-facing unit has two bedrooms, the south-facing unit has three bedrooms, and the ground floor is uninhabited and without air conditioning. In addition, the corridors between adjacent apartments on each floor are also without air conditioning. This research will focus on the power consumption of the variable refrigerant flow system as an electric charge. Figure (2) shows a schematic of an integrated photovoltaic variable refrigerant flow system.

In this section, energy consumption in variable refrigerant air conditioning, power generation of photovoltaic arrays, and carbon dioxide reduction due to photovoltaics are examined according to the results obtained from the design of builder designs.

The intensity of solar radiation in this city equals 1852kWh, and the annual electricity consumption of a refrigerant flow system varies around 18500kWh. The results show that according to the duration of sunlight during the day, the total daily electricity produced by photovoltaics provides only 54% of the daily electricity required for variable refrigerant current, which has a significant impact on reducing electricity consumption from the grid and a significant impact on Reduces carbon dioxide by 14 tons per year.    Figure 1. Internal view of the outer part of the variable refrigerant flow  Figure 2. Schematic of VRF-PV integrated system   Figure 3. DNI radiation status of the sun kW/m2 on July 21 Figure 4. Energy rate status of a building unit on July 21 Figure 5. External and indoor temperature status of a unit (dining room facing south on the 5th floor of the building), on July 21 Figure 6. Status of carbon dioxide emissions on 21 July Figure 7. DNI and DIF solar radiation conditions kW / m2 in summer and autumn Figure 8. Electricity status (Kw) required for cooling and photovoltaic power generation in summer and autumn Figure 9. External temperature and temperature of the dining room facing south on the 5th floor of the building, in summer and autumn

Despite the increasing penetration of renewable energy sources in recent decades, many countries are significantly dependent on fossil fuels. The emission of regional (such as oil spills) and global (such as global warming) environmental pollution is the result of the excessive use of fossil fuels. Considering the significant reduction in the investment cost of renewable resources, Development and exploitation of these resources is one of the effective solutions to overcome these problems. In 2020, about 3.1% of the world's electrical energy was supplied by photovoltaic panels. This amount of production has caused solar energy to rank third among renewable energy sources after water and wind.  In the past years, the levelized cost of electrical energy has decreased remarkably. This reduction is due to the decrease in the investment cost of solar power plant components, including photovoltaic panels. Although many papers have been published on the structure and control system of the solar tracker, few have investigated the performance of these systems in cloudy and semi-cloudy days. In this research, the solar tracker system developed is evaluated on cloudy and semi-cloudy days.

The solar tracker system investigated in this research uses a structure and a control system for the optimal placement of photovoltaic panels in two lateral - vertical and polar placements. Before this and in the researches of the authors of this article, this solar tracker has been mentioned. The number of photovoltaic panels installed on this structure will be multiple of two. The investigated system is a multi-input-multi-output system. In order to increase the reliability of the system, this system is divided into two separate systems.In order to evaluate the performance of the solar tracker, the power and electrical energy produced by photovoltaic panels installed on a mobile structure have been compared with a similar panel installed on a fixed structure with the ability to adjust the angle to the horizon. The installation angle of the panel on the fixed structure is adjusted on a monthly basis and has been chosen in such a way that the maximum electrical energy produced during that month is obtained.

The comparison of the tracking system and a fixed structure showed that the tracker would produce less energy on some hours of a cloudy day. The reason is the defined limitation on LDRs to follow the sun. However, on sunny days, the tracker would receive adequate solar radiation and be in optimal positioning. The results demonstrated this system increases electricity production by 18.2 % compared to the fixed one.

By the extensive presence of electric vehicles (EVs) in today’s communities, the smart management of EVs should be completely investigated. On the other hand, the integration of renewable energy sources (RESs) in the smart electric vehicles parking lot (SEVsPL) reduces the dependency on the upstream network and also the whole operation costs. So, under finite energy sources around the world, in order to supply various demands along with generating low greenhouse gas emissions (GHGEs), policymakers and different scholars seek to find cost-effective, eco-friendly, efficient, and sustainable solutions. With investigating the literature review in the field of management and optimal operation of SEVsPL can be obviously concluded that multiple approaches and strategies from different perspectives were used to improve the efficient usage of energy based on smart grids (SGs) framework in SEVsPL. It was indicated that none of the analyzed references, addressee the simultaneous effects of different uncertainties, i.e., the random behavior of EVs owners, RES, and the upstream network electricity price on the charging and discharging processes for the operation of SEVsPL. Certainly, applying the nature of such uncertainty sources in an appropriate path will have significant impacts on the bringing results as close as possible to the real-world solutions.

Therefore, in the current paper, a stochastic scheduling methodology for the optimal operation of SEVsPL has been proposed as an interactive user interface between the respective operator and EVs owners to facilitate charging and discharging activities and operation costs. The total capacity of SEVsPL is 50 in which three various EVs’ models with 10 scenarios for the arrival time, departure time, and initial state of energy (SoE) were considered. Furthermore, the other uncertainties oriented from RES and the upstream network electricity price have also taken into account with relative 10 scenarios. It is worth to mention that Mont Carlo simulation (MCS) implemented in MATLAB software to produce 1000 scenarios and then reduce them to 10 scenarios with the assistance of SCENRED algorithm in GAMS software. This stochastic optimization model of SEVsPL was formulated as mixed integer linear programming (MILP) problem, which was solved by CPLEX solver in GAMS software.

According to the obtained results in different scenarios, it was obviously seen that the lowest profit of SEVsPL was occurred in scenario 8, which can be considered as the worst case scenario, although, the highest profit has been achieved in scenario 9 and can be taken as the best case scenario. So, it can be mentioned that the optimal utilization of SEVsPL in the presence of RES uncertainty and the unpredictable behavior of EVs can be different. By considering the probabilities of the aforementioned uncertainties, the expected profit for SEVsPL was $ 1571.31. For the plotted figures of photovoltaic (PV) and wind turbine (WT) power plants in scenario 9, the generated WT power can be sold to the upstream network within the period in which EVs have not yet entered the SEVsPL and also for the PV generated power can be utilized to charge EVs. To realize the aim of the SEVsPL operator in maximizing his/her profit, the smart operating strategy was accomplished in purchased /sold power from /to the upstream network, which were indicated in relative figures for two worst case and best case scenarios. These outcomings highlighted that sold power has happened when electricity price is high (e.g., 10 o'clock in scenario 8 and 17 o'clock in scenario 9); however, the purchased power has taken place when electricity price is low (e.g., 10 o'clock in Scenario 9 and 12 o'clock in Scenario 8). This strategy is true for all EVs in all scenarios such that results to gain profit from electricity price arbitrage by the SEVsPL operator. If the EVs owners are looking for the maximum charge when leaving the SEVsPL, the respective operator will earn less profit according to different gamma coefficients presented in relevant expected SEVsPL profit’s figure. In other words, the chance of discharging EVs will be less when attending SEVsPL.

The proposed stochastic optimal operation strategy of SEVsPL in this paper has been accomplished to flatten charging and discharging processes along with operation costs. In the presence of different considered uncertainties, the optimal operation strategy of SEVsPL can be diverse for different scenarios such that the highest and lowest profits were equal to $1740.84 and $1359.22, respectively. Although by considering the probability of all scenarios, the expected profit was equal to $ 1571.31. These various uncertainties affect the obtained profit of SEVsPL which the respective operator seeks to charge EVs at low price hours and discharge EVs at high price hours under the smart performance strategy.