Energy Equipment and Systems
Volume:4 Issue: 2, Autumn 2016

In this research paper, a 10 minute period measured wind speed data at 10 m, 30 m, and 40 m heights are presented for one of the major provinces of Iran. Four stations in Khuzestan- Abadan, Hosseyneh, Mahshahr, and Shushtar- are analyzed to determine the potential of wind power generation in this province. From the primary evaluation and by determining mean wind speed and also the Weibull function, the results show that the measurement site falls under class 2 of the International System Wind Classification for Abadan, Hosseyneh, and Mahshahr and class 1 for Shushtar station. It means that the first three stations have mediocre conditions for installing and operating wind farms, but Shushtar does not have a significant condition for connection to national power grid applications. By using wind roses of speed, turbulence, and the power distribution, the best direction of installing wind turbines for each station was determined. Finally, by utilizing power curves of five typical wind turbines, the annual wind energy, which is produced by a typical wind turbine for one of four stations, Mahshahr, was determined for showing the appropriate annual energy received from a wind turbine.

The present study investigated the effect of distilled-water/ silver nanofluid on heat transfer in a closed cooling system of one of the electrical energy generation units at Isfahan power plant. The difference between this study and previous researches refers to silver properties which have a high thermal conductivity and is non-toxic, hydrophilic and eco-friendly. Distilled water/ silver nanofluid with 20 nm average diameter and 0.1% volume fraction was purchased from Iranian nanomaterials’ Pishgaman company. The volume fractions 0.01%, 0.025%, 0.05%, 0.075% were prepared in the laboratory and thermophysical properties were practically measured in the laboratory. Nanofluids with flow rates from 0.14 to 0.26 kg/s and volume fraction from 0.01% to 0.1% passed through the tubes of heat exchanger and were evaluated in the Reynolds number range of 1500 to 4000. This study was aimed to achieve the overall heat transfer coefficients and pressure drop of the system. According to the system performance index, the results showed that nanofluid can be used to increase the efficiency of heat exchangers and, as an appropriate method, to reduce the dimensions of the exchangers. The results showed that nanofluid increased heat transfer coefficient by 16%. Pressure drop of nanofluid, however, have no significant change compared with the pressure drop of pure water.

One of the main problems in wind energy conversion system (WECS) is how to achieve maxim­u­m output power in different wind speeds. Maximum methods for maximum power point tracking in wind energy conversion syst­e­ms require the knowledge of system characteristics and mechanic sensors. So, using these methods practically will follow with high price and an abundant difficulties. In this paper, new method for maximum power point tracking based on fuzzy controller has been presented that is maximum power point tracking with high power coefficient without requiring mechanical sensors and knowing system characteristics. Wind energy conversion system is simulated by using tracking system based on fuzzy controller in MATLAB/SIMULINK and simulation results prove the advantages of suggested tracking method such as increase of power coefficient in wind turbine and decrease of fluctuations about maximum power point.

The geometry of a collector is one of the important factors that can increase the incident radiation on the collector surface. In the present study, the incident radiation for a stationary collector with cone geometry, i.e. a conical collector, is theoretically and experimentally investigated. This type of collector is always stable and does not need a fixture to install. Moreover, it has a symmetric geometry, with all its sides facing the sun. The main advantage of this collector is its ability to receive beam, diffuse, and ground-reflected radiation throughout the day. The variation of the incident radiation is theoretically estimated by using an isotropic sky model based on the available data. The theoretical data are validated by an experimental test of a conical collector of a specific size. The results show that the conical solar collector is more operative in receiving total solar radiations than a horizontal plate such as a flat-plate collector and can be a suitable option for solar water heating. A calculation of the incident radiation shows that the incident radiation is maximized when the cone angle of the conical collector is equal to the latitude of the site test.

Wind power has been widely considered in recent years as an available and a clean renewable energy source. The cost of wind energy production is currently the main issue, and increasing the size of wind turbines can reduce wind energy production costs. Hence, megawatt wind turbines are being rapidly developed in recent years. In this paper, an aerodynamic analysis of the NREL 5MW turbine is carried out using the modified blade element momentum theory (BEM). The genetic algorithm (GA) as an optimization method and the Bezier curve as a geometry parameterization technique are used to optimize the original design. The modified BEM results are compared with the NREL published results for verification. Cost of energy (COE) is considered an objective function, which is one of the most important and common choices of objective function for a megawatt wind turbine. Besides, the optimization variables involve chord and twist distributions variation along the blade span. The optimal blade shape is investigated for the minimum cost of energy with considered constant rotor diameter and airfoil profiles. Then the objective function is improved and a new optimum geometry is compared with the original geometry. Although the Annual Energy Production and rated power are reduced by 2% and 3% respectively, the net cost of wind energy production is decreased by 15%, showing the importance of such optimization studies.

The purpose of this paper is multi-objective optimization of refrigeration cycle by optimization of all components of the cycle contains heat exchangers, air condenser, evaporator and super-heater. Studied refrigeration cycle is compression refrigeration cycle of unit 132 Third refineries in south pars that provide chilled water for cooling refinery equipments. Cycle will be performed by the genetic algorithm optimization. Thermodynamic purpose of the cycle Expressed by minimization of Exergy destruction or maximization or coefficient of performance (C.O.P), economic purpose of the cycle Expressed by minimization of cold water production cost by TRR method and environmental purpose of the cycle Expressed by minimization of NOx, CO2 and CO Which is produced by power consumption. Combination of objectives and decision variables with suitable engineering and physical constraints makes a set of the MINLP optimization problem. In EES software. Optimization programming is performed using NSGA-II algorithm. Four optimization scenarios including the thermodynamic single-objective, the economic single-objective, environmental single-objective by power electricity consumption and multi-objective optimizations are performed. The output of the multi-objective optimization is a Pareto frontier that yields a set of optimal points that the final optimal solution has been selected using two decision-making approaches including the LINMAP and TOPSIS methods.. It was shown that the best results in comparison to the simple cycle reduction in Exergy destruction from 264.8 kW to 127.6 kW(Increased coefficient of performance from 3.872 to 7.088), reduction in cold water production cost from 117.5 dollar/hour to 87.19 dollar/hour and reduction in NOx emission from 4958 kg/year to 2645 kg/year.

Energy harvesting from surrounding environment has been attractive for many researchers in recent years. Therefore, developing appropriate test apparatus to study energy harvesting mechanisms and their performance is of paramount importance. Due to their electromechanical characteristics, piezoelectric materials are used for harvesting energy from environmental vibrations. For optimum utilization of this system in harvesting and storing energy, the studies need to consider the environmental conditions. In this work, the electromechanical system is developed with the aim of conducting tests on piezoelectric materials. It is an integrated system which is developed and built after considering the limitations and sensitivity of piezoelectric material. In this research, the simple piezoelectric beam is also tested. Evaluation results via this system are analysed using Abaqus. The error value in receiving output voltage is 6% because an ideal open circuit state is considered by this software.

The energy efficiency, greenhouse gas (GHG) emissions, and carbon efficiency of paddy rice production were analysed in Sari in the Mazandaran province of Iran during 2011–2012. Data was collected through questionnaires and interviews with paddy producers. The results showed that the net energy gain was 27,932 MJ ha-1 and energy efficiency was 1.83 during production. The results of the Cobb-Douglas (CD) model showed that the energy inputs of machinery, diesel fuel, chemical fertilizers, and biocides had positive impacts on yield, while the impacts of seed and human labour were negative. For every 1 MJ increase in energy input, the inputs of seed, labour, machinery, diesel fuel, chemical fertilizers and biocides, changed the yield as -0.058, -0.992, 0.078, 0.004, 0.027, and 0.089 kg, respectively. The energy input of machinery with a high beta coefficient (0.64) had the most impact on crop yield (p≤0.01). The total GHG emission for paddy production was determined to be 1,936 kgCO2eq ha-1, with diesel fuel and machinery having the greatest contributions.Carbon efficiency was estimated to be 4.01.

This paper proposes a new method for transmission loss allocation. The share of each bus in the transmission line losses is determined using transmission line loss equations with respect to bus-injected currents. Then, it is applied to the total network transmission lines. In the proposed method, comparing with other methods, a solution to remove the negative loss allocation has been introduced. This algorithm is based on the electric network relations and the injected power in various buses considering the network topology. The proposed method is studied on a typical three-bus network, and applied to the IEEE 14-bus networks. In comparison with other methods, a new solution for removing negative loss allocation is proposed.

In this study, the performance of an irreversible regenerative Brayton cycle is sought through power maximizations using finite-time thermodynamic concept in finite-size components. Optimizations are performed using a genetic algorithm. In order to take into account the finite-time and finite-size concepts in the current problem, a dimensionless mass-flow rate parameter is used to deploy time variations. The results of maximum power state optimizations are investigated considering the impact of dimensionless mass-flow rate parameter variations. One can see that the system performance shows high values of the dimensionless mass-flow rate parameter because of low power production while the high total cost rate is not reasonable. The other objective (besides power maximization) of the current study is to prepare finite-time thermodynamics for studying more practical systems using new thermodynamic modelling, exergy, and cost analyses of the current system.

This paper presents a comprehensive theoretical, experimental, and economic study on the application of nanofluids as heat transfer fluid in waste heat recovery systems. The research work was conducted in a steel-making complex in which a plate heat exchanger had been used to recover heat from hot process water. The system was theoretically modelled and the effects of using nanofluids as heat transfer fluid were investigated. Nanofluids with ZnO, Al2O3, SiO2, and CuO as nanoparticles and water as base fluid were used in the analysis. It was found that the best performance is obtained with Al2O3 nanofluid. This can increase the effectiveness of the plate heat exchanger by up to four per cent. Based on this analysis, the existing heat transfer fluid (demineralized water) was replaced by Al2O3 nanofluid. The experiment confirmed the theoretically predicted increase of the heat exchanger’s effectiveness but this increase was a little lower than what was expected. Finally, an economic analysis was done using the net present value method. This economic analysis was performed twice: once with local market prices and once with global market prices. The results show that the project is economical based on global market prices.

This paper presents a simple model predictive control (MPC) approach to control the power injection system (PIS) for renewable energy applications. A DC voltage source and a single-phase inverter that is connected to the grid by an LCL filter form the PIS. Grid voltage is considered a disturbance for the system. For eliminating this disturbance, a modified model is proposed. It is usual to control output current to inject a desired power to grid. But due to the presence of the LCL filter, we face a third-order system and other states should be bounded during operation. In this work, we ensure the stability of other state variables and, consequently, system stability, by defining a proper cost function. In this regard, reference signals are calculated for all state variables. For getting the benefit of the switching nature of the inverter, we use a finite control set model predictive control (FCS-MPC). Proposed predictive control is implemented in a digital scheme and, thereby, the discrete model of the system is extracted. The proposed controller does not require any other control loop or modulation method. Simulation results show the effective performance of the proposed control scheme.

The present research proposes and optimizes the performance of a novel solar-driven combined cooling, heating, and power (CCHP) Kalina system for two seasons—winter and summer—based on exergy, exergo-economic, and exergo-environmental concepts applying a Non-dominated Sort Genetic Algorithm-II (NSGA-II) technique. Three criteria, i.e. daily exergy efficiency, total product cost rate, and total product environmental impact rate associated with the exergy of the system for each season are considered simultaneously for multi-objective optimization. The outcomes reveal that increments in turbine inlet pressure and mass flow rate of the vapour generator lower the environmental impact of system products as well as the total product cost rate in both seasons. The optimum value of daily exergy efficiency, total product environmental impact rate, and total product cost rate indicate improvements by 2.56%, 15.7%, and 15.3% respectively in summer and 36.34%, 7.39%, and 4.93% respectively in winter, relative to the base point.

The aim of this study is to find the optimal water pressure and percentage of supply vapour in the feed water heaters (fwhs) of steam power plants, such that they maximize the thermal efficiency of the Rankine cycle within pre-specified values of minimum and maximum pressures of the thermodynamic cycle. Thermal efficiency is defined as a function of unknown variables (fluid pressure and vapour percentage of each fwh), and it is maximized numerically using the nonlinear constraint optimization method. Precise values of enthalpy are used in computations of thermal efficiency during the nonlinear optimization process. The enthalpy and entropy values at different points of the thermodynamic cycle are calculated utilizing the industrial formulation of IAPWS-IF97.

In the present study, the energetic and economic modeling of lentil and chickpea production in Esfahan province of Iran was conducted using adaptive neuro-fuzzy inference system (ANFIS) and linear regression. Data were taken by interviewing and visiting of 140 lentil farms and 110 chickpea farms during 2014-2015 production period. The results showed that the yield and total energy consumption were calculated 2,023 kgha-1 and 32,970.10 MJha-1, respectively for lentil; and 2,276 kg ha-1 and 33,211.18 MJ ha-1, respectively for chickpea. Energy use efficiency was found to be 0.9 for lentil and 1.02 for chickpea; while benefit-cost ratio (BCR) were obtained 1.60 for lentil and 1.74 for chickpea. Regression results demonstrated that the coefficient of determination (R2) were 0.92 for lentil and 0.89 for chickpea. In adittion, in regression estimated model in terms of BCR, R2 were obtained as 0.86 for lentil and 0.72 for chickpea. In modeling of yield using the best ANFIS model, R2 were calculated 0.99 and 0.98, respectively for lentil and chickpea. Finally, for evaluation of crops BCR by best ANFIS model, R2 were determinate as 0.94 and 0.91 for lentil and chickpea, respectively. It was concluded that ANFIS model could better predict the energy output and BCR than that of linear regression model.

Many researchers have investigated how to increase the overall efficiency of solar-driven thermal systems. Several key parameters, such as collector efficiency and storage tank characteristics, may impose some constraints on the annual solar fraction (ASF) of such systems. In this paper, the behaviour of integrating the phase change material (PCM) in SDHW systems is modelled and optimized numerically. Coupled collector and partly stratified PCM-embedded storage tank governing equations are utilized to simulate the overall performance of the system. The developed code presents the monthly behaviour of the system including the solar fraction and the storage tank temperature profile. The results indicate that the stratification of the storage tank will increase the ASF up to about 4.6%. Additionally, it is found that the optimum amount for the PCM and its melting temperature is changed as the tank stratification goes from the fully mixed to the fully stratified state. Integrating the PCM in the storage tank leads to increases of 5.3% in the ASF for a single-node tank, while a rise of only 0.7% is seen for the stratified storage tank.

Integrated energy systems utilizing renewable sources are sustainable and environmentally substitutes for conventional fossil-fired energy systems. A new multigeneration plant with two inputs, such as biomass and solar energy, and four useful outputs, such as cooling, heating, power, and distilled water, is presented and investigated in this paper. The proposed system includes evacuated tube solar collectors, biomass burners, the organic rankine cycle (ORC), absorption chillers, heaters, and a multi-effect desalination system (MED). The results showed that the proposed system can produce 802.5 kW for power, 10391 kW for heating, 5658 kW for cooling, and 9.328 kg/s for distilled water. The energy efficiency of the system is 61%, while the exergy efficiency is 7% and the main sources of exergy destructions are biomass burner, evacuated tube solar collectors, and the vapour generator. Exergy optimization is carried out to find the optimum point of the system.