Energy Equipment and Systems
Volume:7 Issue: 3, Summer 2019

According to the energy crisis in the world, optimization of energy consumption is indispensable. Technological advances in constructions and application of renewable energy resources demand saving energy. Atrium, as one of the construction elements, catches sufficient daylight and acts as a passive solar element and results in a decline of energy consumption. This research seeks to evaluate the impact of different positions of atrium on its energy performance; this embraces modelling three groups of spatial configuration of atriums in a given four-story building. The total volume and area of atriums in all three groups are equal. DesignBuilder, the energy simulation software, is the platform for simulation and comparison. The results show that the number of atriums does not have a noticeable impact on energy consumption; however, the spatial configuration of atriums, specially the distance of atriums to external walls have a little impact on the annual energy consumption. Based on the purpose of a specific design, one can decide on whether to take into account the discrepancy.

In the present paper, the effect of water-CuO nanofluid on the radiator heat transfer of an automobile, Peugeot 405 XU7 engine type is investigated experimentally. The experiments are carried out for the radiator water (water-ethylene glycol with a volume fraction of 80-20, respectively) as a base fluid and water-CuO nanofluid with the volume fraction of 0.5% and 1%. Sodium Dodecyl Sulfate (SDS) is used to increase the stability of nanofluid. The results demonstrated that a significant increase in the heat transfer of the engine to the environment is obtained by adding CuO nanoparticles to the base fluid. For nanofluid volume fraction of 0.5 and 1% for a mass flow rate of 30 liters per minute, the heat transfer rate enhances 3% and 6.9%, respectively, in comparison with the base fluid. Although convective heat transfer coefficient increased by increasing the nanofluid volume fraction, the experiments showed that this coefficient increases with the mass flow rate up to 20 liters per minute and then decreases with the mass flow rate. Besides, the radiator pressure drop increases by increasing of the pressure of nanofluid. The results revealed that the ratio of heat transfer and pump power (merit parameter) decreases as the nanofluid pressure increases

In this research paper, ANFIS modeling and validation of Vestas 660 kW wind turbine based on actual data obtained from Eoun-Ebn-Ali wind farm in Tabriz, Iran, and FAST is performed. The turbine modeling is performed by deriving the non-linear dynamic equations of different subsystems. Then, the model parameters are identified to match the actual response. ANFIS is an artificial intelligent technique which creates a fuzzy inference system based on input and output information of the model. In this research, the ANFIS algorithm combines neural network and fuzzy logic with 5 layers which utilize different node functions for learning and setting fuzzy inference system parameters. After learning, by assuming constant parameters, a hybrid method is used to update the results. Employing the proposed method, computation time and complexity are remarkably reduced. Results of the proposed method are then compared and validated with the actual data of Eoun-Ebn-Ali wind farm in Tabriz. It is shown and concluded that the proposed model matches favorably well with the actual data and FAST model.

In this study, thermodynamic and economic analysis of a photovoltaic electricity generation system (PVEGS) with and without self-cleaning panels is reported. In the first part, thermodynamic analyses are used to characterize the performance of the system. In the second part, the economic comparison of photovoltaic electricity generation with and without self-cleaning panels is carried out for all climate zones of Iran. A computer simulation program using EES software is developed to model the solar photovoltaic electricity generation system in four different climates of Iran. The solar photovoltaic system provides electricity during the year. Our goal is to point out the potential of electricity production using conventional panels compared to self-cleaning panels under the same condition. The analysis involves the specification of the effects of varying solar radiation intensity (SRI) on the electricity generation rate of the photovoltaic electricity generation system. The average output power values for the solar photovoltaic system with self-cleaning panels and the solar photovoltaic system without self-cleaning panels are found to be 50767 and 48120 kWh/year, respectively, which means that the solar photovoltaic system with self-cleaning panels has the higher performance than the solar photovoltaic system without self-cleaning panels in all climate zones of Iran.

The Betz theory expresses that no horizontal axis wind turbine can extract more than 16/27 (59.3%) of the kinetic energy of the wind. The factor 16/27 (0.593) is known as the Betz limit. Horizontal Axis wind turbine designers try to improve the power performance to reach the Betz limit. Modern operational wind turbines achieve at peak 75% to 80% of the Betz limit. In 1919, Albert Betz used an analytical method to derive the Betz limit. He derived momentum equations of an Actuator Disc (AD) in the stream. In this research, an experimental and a numerical setup based on the Actuator Disc (AD) have been designed and tested to reach the Betz limit. A Plexiglass screen with the porosity of 0.5 mimics the wind turbine rotor. For the numerical study, a 2D flow filed is considered. The results of both experimental and numerical methods agree well with the analytical results of the Betz theory. From the experimental and numerical results, the relative errors in comparison with the Betz limit (which is 16/27) are 0.16% and 1.27%, respectively. The small amount of errors shows the possibility of reaching the Betz limit using either experimental or numerical methods. This approach can be used for modeling ideal wind turbines, ideal rotating devices or ideal wind farms either numerically or experimentally and gives the maximum possible power extractions; thus, any improvement to the performance of a system can be made by this method.

The LVRT (Low Voltage Ride Through) is the main characteristic of every power system in faulty conditions. When fault occurs, it is essential for power system such as microgrid to control the voltage and frequency normally. Naturally in fault status, the unbalanced voltage and current are inevitable, but with the aid of LVRT technique, microgrid can keep stability in main system parameters such as voltage and current of each phase. In this paper, the microgrid is proposed in islanded state and using the reactive power injection in faulty conditions, and the LVRT technique is applied. When reactive power is inserted, simultaneously the active power must be reduced, and so the current is limited, and overcurrent is controlled. Simulation results indicate that this strategy enhances the presentation of the structure in symmetric and asymmetric faults. That is noticeable declaring that the suggested approach has not degraded the power sharing among DGs both in faulty and faultless status and also plug and play property is kept using this suggested LVRT strategy.

There is an increasing need to forecast power generated by photovoltaic sources in day-ahead power system operation. The electrical energy generated by these renewable sources is an uncertain variable and depends on solar irradiance, which is out of control and depends on climate conditions. The stochastic programming based on various scenarios is an efficient way to deal with such uncertainties. In this research paper, the long term hourly recorded irradiance data in 15 past years are applied to generate the next day's irradiance scenarios. Irradiance determines the operating point of PV panel as well as the generated electrical power. Also, the scenario generation method based on autoregressive and moving average time series is proposed. For decreasing the number of scenarios, backward reduction based on Kantorovich distance is applied. The obtained results confirm the accuracy and ability of the proposed method in forecasting the relevant data. ling ideal wind turbines, ideal rotating devices or ideal wind farms either numerically or experimentally and gives the maximum possible power extractions; thus, any improvement to the performance of a system can be made by this method.