Renewable Energy Research and Applications
Volume:4 Issue: 2, Summer-Autumn 2023

Demand of energy is increasing day by day worldwide. Also the use of non-renewable energy resources has created serious problems like global warming and air pollution. At the same time, these resources are fast depleting. So we have to look on renewable energy resources to meet the future energy needs. Geothermal energy resources are very versatile renewable energy resource and have wide range of potential use to fulfill the energy need of society in and around the regions of its availability. The present study critically examines the energy from geothermal resources and scope of its utilization in India. There are about 400 known thermal areas in India, each represented by hot spring. The potential geothermal resources exist all around these hot springs. The temperatures of these springs range from 34°C to 96oC. Based on cation’s and anions study, the water types are mostly NaHCO3Cl, NaCaHCO3Cl, CaMgHCO3 and NaHCO3ClSO4. The geothermal fluids from the shallow wells at Puga have been effectively applied to the refining of borax and sulphur as well as experimental space heating. India’s first power plant to produce estimated output power of 250MW will be setup at Puga. The helium content in the hot gases from Bakreswar geothermal sites varies from 1-3%. Helium exploration field stations were established in the above mentioned sites. The geothermal gradient varies from 0.7-2.5oC/m at Chhumathang geothermal field indicating the powerful geothermal region. There exists great scope to use this versatile resource for electrical as well as non-electrical applications in India.

Highly unstable absorber layers along with costly Hole Transport Materials(HTMs) have been the main problems in the perovskite-based photovoltaic industry recently. Here in this study, we intend to meet both these problems by introducing a non-toxic cesium-based absorber layer and low-cost material, Graphene Oxide (GO) as the Hole Transporting Layer (HTL). We use the Solar Cell Capacitance Simulator Program (SCAPS) to study the various output parameters of the device with the structure GO/Cs2TiBr6/TiO2. Physical properties like the thickness of the absorber and hole transporting layers, the role of the layer interfaces, the effect of electron affinity, optical properties like the band gap of the absorber and hole transporting layer, electrical properties like the parasitic resistance, and finally the influence of operating conditions like the temperature on the working of the device was found out. The results show that a thickness of 1 μm for absorber and 0.1 μm for HTL is suitable. Also, the optimum value for front and back interface layers were 1010 cm-3 and 1016 cm-3 respectively. Resistance values were fixed at 2 for series and 40 for shunt resistance. The electron affinity doesn’t seem to have much effect on the device performance while with the increase in temperature the performance of the device deteriorated. The highest efficiency that we obtained from the optimized device was 15.3%. In short, this unprecedented work shows that Cs2TiBr6 - GO based devices are suitable candidates to achieve highly efficient, eco-friendly, all-inorganic perovskite solar cells.

Plenty of works have treated the system expansion planning problem in the presence of intermittent renewable energy resources like solar. However, most of those proposals have been approached from scenarios of plenty of data, which is not the rule in developing countries, where principal investment actors have recently switched their focus. In contrast of operation problems where existing literature can be successfully applied since it requires short-term historical time-series gathered from the same studied plants, proposals for planning problems are almost impossible to apply because of a lack of information and measurement about renewable resources in places where no renewable plants have been previously installed. In order to fill this information gap, this paper presents a novel methodology to synthesize solar production time-series on an hourly time scale, taking as inputs aggregate data such as monthly average, maximum or minimum values of basic parameters like global horizontal insolation, air temperature, and surface albedo. The methodology comprises five steps, from data gathering to calculating electrical power produced by a solar photovoltaic system. Three application tests are performed for different places in Chile, Slovakia, and Peru to validate the proposed methodology. The results show that the methodology successfully synthesizes time-series of output power, correctly replicates typical solar resource behavior, and slightly underestimates the produced solar energy, having a discrepancy of 2.4% in the yearly total.

This paper analyses the VCR (variable compression ratio) engine's performance, combustion, and emission output responses. The experimental results were modelled using the Grey Taguchi method (GTM) for input parameters of compression ratio, load, and fuel blends. The objective is to find the optimal combination of input parameters in the minimum number of experiments for minimum emission, better performance, and combustion parameters. The Taguchi’s L9 orthogonal array with GTM is used to get the optimum combination of input parameters. The Taguchi was used to analyze the S/N ratio of experimental data and the gray-based method for optimization of multi-objective to single-objective optimization by assigning the suitable weighting factor to each response. The S/N ratio analysis of grey relational grade (GRG) shows the fuel B10, CR 16, and load at 100% of the optimal input factor level. This optimal level is further confirmed by the TOPSIS method. The analysis of variance (ANOVA) for input to GRG shows the highest influencing factor is the load with a 52.82% contribution, followed by CR at 28.38%, and fuel at 10.52%. The confirmatory results show an improvement of 56.1%. The novelty of this experimentation was to study feasibility of existing engine for alternative fuel with slight modification. At above optimal conditions, this biodiesel can be used efficiently in an unmodified compression ignition engine.

Dye-Sensitized solar cells (DSSCs) are among the family of third generation photovoltaic (PV). DSSCs are promising with the theoretical predicted value for power conversion efficiency (PCE) of 20%. In this paper, explicit equations for the single-diode equivalent circuit model parameters of a solar cell were modeled based on the characteristic points on the I-V curves that do not require the short-circuit and open-circuit slopes as input data. The equations were used to calculate the five model parameters (n, Rs, Rsh, Iph, Io) of a standard solar cell-based DSSCs composed of different natural photosensitizers. The results show that four(~28.5%) devices with natural photosensitizers (bitter gourd, sun flower, rose flower, tomato) manifest parameter irregularities i.e. they have negative series resistance or complex shunt resistance. Despite the occurrence of irregular parameters, there is still a good match between the calculated and measured photoelectric characteristics. This supports the idea that the nature of the parameter values does not matter provided there is a good match between measured and calculated I-V characteristics. The bitter gourd-based DSSC demonstrates the most promising photosensitizer for DSSC fabrication based on values of the parameters. Hence, the agreement of the calculated and measured parmeters suggests that modeling is good approach for extraction solar parameters.

Thermal comfort is one of the most important factors affecting the quality of outdoor space. This work investigates the effect of shade on outdoor thermal comfort during the hot season. For this purpose, meteorological measurement and questionnaire surveys are conducted simultaneously at four points of the university campus in the cold semi-arid climate of Shahrood, Iran. Then the ENVI-met V4 is validated and implemented to examine the impact of different shading scenarios on outdoor thermal comfort. The neutral physiological equivalent temperature (PET) and the upper boundary of the PET comfort range are obtained at 21.9 °C and 26.9 °C, respectively. The results demonstrate that the plant shade creates the most acceptable thermal environment. Also shading cause a significant reduction in the PET value and thermal stress, while increasing the comfort levels and the comfort hours during the sunny days. Furthermore, the simulation results indicate that creating shade in the open space by trees contribute to lower level of mean radiant temperature up to 24.79 °C and up to 13.7 °C for PET. Moreover, a maximum mitigation effect of an architectural shade is obtained at 32.6 °C for mean radiant temperature and 17 °C for PET. The highest reduction of PET (17.2 °C) is achieved by the combination of trees and the architectural shade. The outcomes of this research work provide useful design recommendations to improve outdoor thermal comfort.

Due to the lack of transmission and distribution network in remote and impassable areas due to the high cost of construction of the transmission line along with the unsuitable geographical conditions and taking into account the factors affecting sustainable energy production, the use of a hybrid system seems like a sensible solution. Designing hybrid systems in order to respond throughout the year is of paramount importance. In this research, this study investigates the participation of wind turbine, photovoltaic and hybrid system with demand response in the presence of energy storage. The participation of renewable energy in providing demand response will be presented in three seminars: 1: The role of wind turbine partnership with storage, 2: the role of photovoltaic with storage, 3: hybrid mode with storage. The best ways to generate electricity are sought from three different scenarios to select the best possible case. It can be said that renewable energy is economically competitive with fossil energy and this energy can be used and implemented along with distribution networks. While analyzing the participation of different hybrid systems and estimating the cost of optimization, the total price for each unit of energy production, energy storage, Net Present Cost (NPC) and participation in demand supply will be compared. Comparative results show that the hybrid design can have a more appropriate and desirable performance. HOMER software is used to determine the optimal possible modes for these systems, in the position of 37 degrees latitude and 42 degrees longitude.

countries need to use energy resources to achieve economic growth, but due to the limitation of fossil energy resources such as oil and coal, the increase in the price of these resources in recent years, as well as the resulting environmental pollution, the countries concerned The use of clean and renewable energy sources has increased. Considering the importance of using renewable energy for the sustainable economic growth of the country in the coming years and the novelty of this topic in domestic studies, therefore, in this research, the impact of renewable energy consumption on the growth of Iran's GDP has been investigated.The innovation of this research compared to previous studies is the use of influential variables such as fixed capital formation, employment rate, trade openness and sanctions in addition to the variable of renewable energy consumption on the country's economic growth. In fact, in this study, the investigated model has been expanded with effective variables according to Iran's economy, which has not been addressed in previous studies. We considered time series for variables including renewable energy consumption, GDP per capita, capital formation, employment rate, trade openness, and sanctions for the time period 2010–2020. In this research, the vector autoregression model with distributed intervals (ARDL) has been used to estimate the relationship between variables. The results show that there is a positive and significant relationship between renewable energy consumption, fixed capital formation, employment rate, trade openness and GDP growth, and sanctions have had a negative and significant impact on GDP growth.

Flap-type wave energy converter is one of the oscillating surge devices for generating electricity from the ocean wave source. It comprises a vertical plate pivoted on a hinged base that oscillates rotationally due to the exciting wave. Splitting a single flap into two separated flaps in a double arrangement may cause different dynamic characteristics. This can improve the output extracted power versus the excitation period. Therefore, this effect is investigated in the present study through a dynamic mathematical model. The hydrodynamic coefficients and exciting torques in the equation are calculated based on the Boundary Element-based software of ANSYS AQWA. In the next step, the rotational displacement is calculated through the frequency domain approach based on the assumption of the regular monochromatic and head-on waves, and consequently, the maximum power is computed regarding the optimum power take-off damping strategy. Finally, in the same procedure as the single flap, the output power for the double arrangement is derived. The results show that decreasing the natural period for each flap can potentially cause a wideband response of the total power for the double configuration compared to the single one.

In recent years, the growing demand for energy and environmental requirements has focused much attention on solar energy as a renewable source. The building rooftops are the most suitable places for installing photovoltaic panels in urban and rural areas. In large districts, accurate estimation of radiation received by the rooftops requires the existence of detailed 3D information about them. This research aims to provide an efficient method to estimate solar energy production potential from the rooftops using the UAV photogrammetry method and GIS. The proposed method considers both the factors of the geometric features of the rooftops (slope and azimuth) and the shadow of the adjacent features. A threshold for minimum separated suitable rooftops for installing photovoltaic panels received radiation and rooftop area. Converting received radiation into electrical energy was made based on the average level of current world technology for solar panels. Providing a comparison between the amount of electricity produced during the four seasons and throughout the year as an effective parameter related to the consumption pattern is another achievement of this research. The findings of this research can be used in various fields, such as electricity and the construction industry, as well as macro planning, to benefit from clean energy. The results of implementing the proposed method for a rural area showed that out of a total of 543 existing roofs, 422 roofs are suitable for installing solar panels. Also, for these rooftops, the potential to produce 5741 MWh of electricity will be available in one year.

Compliant offshore tension leg platforms (TLP) are adaptive platforms with a vertical mooring system. These types of platforms are usually used in deep water. Adding sufficient initial tension to the mooring, the vertical movements of the structure will be reduced. Tendons, body, and deck are different components of this platform, with the body being the most important in terms of hydrodynamic forces, weight, and cost. In this study, an investigation is done on a TLP with a wind turbine by numerical analysis. The boundary element and the finite volume method were carried out in this work in the Caspian Sea. Then the platform was analyzed at a depth of 150 meters, under the influence of wind, current, and irregular waves with one and 100-year return period, and at a zero-degree wave angle. The results of the two numerical approaches are very close and almost identical. The tension leg platform was stable in the different irregular waves. Also, the response amplitude operator calculated using two numerical methods has a good agreement.

Due to the growing demand in the electricity sector and the shift to the operation of renewable sources, the use of solar arrays has been at the forefront of consumers' interests. In the meantime, since the production capacity of each solar cell is limited, in order to increase the production capacity of photovoltaic (PV) arrays, several cells are arranged in parallel or in series to form a panel in order to obtain the expected power. Short circuit (SC) and open circuit (OC) faults in the solar PV systems are the main factors that reduce the amount of solar power generation, which has different types. Partial shadow, cable rot, un-achieved maximum power point tracking (MPPT) and ground faults are some of these malfunctions that should be detected and located as soon as possible. Therefore, effective fault detection strategy is very essential to maintain the proper performance of PV systems to minimize network interruptions. The detection method must also be able to detect, locate and differentiate between SC and OC modules in irradiated PV arrays and non-uniform temperature distributions. In this paper, based on artificial intelligence (AI) and neural networks (NN), neutrons can be utilized, as they have been trained in machine learning process, to detect various types of faults in PV networks. The proposed technique is faster than other artificial neural networks (ANN) methods, since it uses an additional hidden layer that can also increase processing accuracy. The output results prove the superiority of this claim.