Tilt Angle Of Photovoltaic Modules Research Articles

Determining the influence of seasonal tilt angle on the efficiency of fixed solar photovoltaic modules

The object of this study is photovoltaic modules with different seasonal tilt angles at different geographical latitudes. The average annual efficiency of photovoltaic modules with different seasonal angles set at different geographical latitudes has been determined as the annual weighted average value of the cosine of the angle of incidence of solar rays on the plane of the photovoltaic module. The influence of seasonal tilt angles of photovoltaic modules at different geographical latitudes on their average annual efficiency was analyzed. Approximate values of the seasonal tilt angles of photovoltaic modules at different geographic latitudes take values that differ from the geographic latitude value by plus 15° for the winter period and minus 15° for the summer period. Modeling the average annual efficiency of photovoltaic modules depending on the seasonal tilt angles at different geographical latitudes made it possible to obtain refined values of the seasonal tilt angles of photovoltaic modules. Thus, at the latitude of 0°, 10°, 20°, 30°, 40°, 50°, and 60°, the tilt angle of photovoltaic modules for the winter period will be 14.8°, 24.6°, 34.5°. 44.4°, 54.1°, 63.6°, and 73°, respectively, and for summer ‒ minus 14.5°, minus 4.6°, 5°, 15.1°, 25.1°, 34.9°, and 44.7°. Dependences were obtained for determining the seasonal tilt angles of photovoltaic modules depending on the value of geographic latitude. The difference in the average annual efficiency of photovoltaic modules, which are installed at seasonal angles, and photovoltaic modules, which track the position of the Sun in the vertical plane, is 0.4 %. The results could be used as a basis for evaluating the efficiency of photovoltaic modules when determining the seasonal tilt angle at different geographic latitudes

Software for calculating the optimum tilt angle of PV modules in different latitudes of the Southern hemisphere and solar plant sizing

Through the development of photovoltaic technologies, the market related to this type of renewable energy grows constantly. In Brazil, the generated power through photovoltaic (PV) power stations approximates to 2.3 GW representing 1.3% of the total Brazilian energy mix. To supply the public it is necessary to offer tools that facilitate consumer decision making or even the work of a solar farm designer. By analyzing the user’s necessity, it is possible to determine that a great parcel needs a quick and simple response to help them with their questions, and programs that are already well established in the marketplace are complex for inexperienced users. For this reason, a software that calculates the best inclination for PV modules using the method proposed by Liu and Jordan in 1962 is developed. It also determines the number of modules that can be installed without any shading between arrays within a user-defined area. This calculation is possible through the standard dimensions provided by the module manufacturers and the solar height and declination study. Through a simple interface, the user quickly receives the optimum tilt angle of installation, the number of PV modules and the maximum generated power.

Research on optimum tilt angle of photovoltaic module based on regional clustering of influencing factors of power generation

This study proposes a methodology to optimize photovoltaic (PV) module tilt angle based on regional clustering and cost evaluation. The factors that affect the power generation of PV module have significant geographical differences and coupling characteristics, and the impact of each influencing factor varies at different installation parameters. Initially, this paper performs clustering analysis on the geographical regions of mainland China to obtain 10 geographic regional classifications based on the consistency of impact degree of influencing factors. A PV module power generation prediction model is constructed by considering the influence of environmental and installation factors comprehensively and then the optimum tilt angle is further obtained. Application results in Wuhan City verifies the accuracy and validity of the proposed model with a relative root mean square error (% RMSE) and mean absolute percentage error (MAPE) of 1.9% and 1.66%, respectively. Subsequently, the model is applied to the power generation prediction of PV module in Hangzhou City. The results indicate that the optimum angle of the PV module is affected by the cleaning cycle. To investigate the relationship between the cleaning cycle and the optimum tilt angle, a novel cost evaluation model that considers the power loss and cleaning costs is proposed. Based on this proposed model, the optimum combination of cleaning cycle and tilt angle in Hangzhou City, namely, 15 days and 22°, is determined. The results are suitable for all the regions that belong to the same regional category with Hangzhou City, Zhejiang Province. The model and analysis method given in this research can provide theoretical support for determining the optimum tilt angle and cleaning cycle of PV module in different clustering regions.

Techno-Economic Evaluation of a Grid-Connected Solar PV Plant in Syria

The main objective of this paper is to analyze the techno-economic feasibility of installing a 300 kW grid-connected solar photovoltaic (PV) plant in Syria. Umm Al-Zaytun village in As-Suwayda province was chosen as a location of the plant, because it is characterized by the high annual solar irradiance on the horizontal surface of about 1900 kW h/m2. Technical performance analysis, system configuration, detailed losses and energy yield simulation for a proposed PV plant were performed, using the PVsyst software. The simulation results show, that the annual optimal tilt angle of PV modules is 25°, energy production is 493 MWh/yr, the annual average performance ratio is 0.799 and the capacity factor is 18.7%. In addition, by considering, that the electric power consumption per capita in Syria is 2232 kW h/yr, so the proposed solar power plant with 493 MW h/yr can provide energy to 220 capita/yr and save about 42.4 tons of oil equivalent yearly with carbon emission reduction of about 320.45 tCO2/yr. The economic evaluation of the proposed PV plant was carried out by Excel software with consideration, that the discount rate is 9%, the lifetime of the project is 25 years and the selling price of electricity to Syrian electricity distribution establishment is 0.119 $/kW h. The results of economic calculations show, that levelized cost of electricity is 0.094 $/kW h, the discounted payback period is about 11 years, the internal rate of return is 14%, profitability index is 1.46 and the net present value is 190587.3 $. As a result, the proposed grid-connected PV solar plant is considered economically, technically and environmentally feasible in Syria.

Measuring PV Module Performance at Different Tilt Angles in Southern Iraq Based Simulation

This paper presented that how to calculate the tilt angles and solar irradiance on photovoltaic (PV) module in southern Iraq (latitude 30° N). The latitude and day number of the city is taken into account to calculate the tilt angle and solar irradiance by using a mathematical equation. The optimum tilt angles of PV module in southern Iraq are range from 38° to 84°. The yearly maximum total and average solar irradiance is needed to determine the optimum tilt angle of PV module. The result shows that 50° of tilt angle is the best performance of PV module in southern Iraq.

A Solar Tracking System Based on Local Solar Time Integrated to Photovoltaic Systems

The performance of photovoltaic (PV) systems is highly influenced by the tilt angle of PV modules and the incidence of global solar irradiance, which may change the solar to electrical conversion efficiency. Some authors have addressed these uncertainties arising from PV solar generation by using mechanisms and methods in which solar tracking systems are integrated to PV systems. Since the advent of the internet of things (IoT), this solar tracking strategy has yet to meet the requirements of scalable distributed power systems that can seamlessly support the PV solar generation, mainly for remote monitoring and control. In this context, this paper aims at developing a prospective study devoted to examine fundamental concepts to implement solar tracking algorithms based on local solar time by using embedded technology from the IoT platform. Preliminary results evidenced an improvement of up to 38% in power generation performance for algorithm-driven PV modules compared to fixed PV modules.

An Improved Methodology to Design Large-Scale Photovoltaic Power Plant

Abstract A secure and reliable supply of energy is important for economic stability and even in social life. Increasing human population, industrialization, and rising living standards lead to increased electrical energy demand. Uncertainties in oil prices, shortage of fossil fuel reserves, and environmental pollution from conventional fuels leads solar energy as an alternative resource for electricity production. The share of installed photovoltaic (PV) capacity as a percent of total installed power generating capacity is increasing every year. In this study, an improved methodology to design large-scale PV power plant is proposed. The proposed methodology is performed for designing optimal configurations of PV power plants. The design methodology is performed using commercially available PV modules and inverters. In addition, solar radiation, ambient temperature, wind speed, shadow effect, and location and shape of plant field are taken into consideration as input parameters. The alternatives and parameters are evaluated with the purpose of minimizing the levelized cost of generated electricity (LCOE). The methodology includes the use of a genetic algorithm (GA) for determining the optimal number of PV modules and inverters, optimum tilt angle of PV modules, required installation area for the plant and optimum cable cross section and lengths. In the paper, the methodology is implemented, and case studies and results using pvsyst software for the same case studies are compared with each other.

Optimal Tilt Angle for PV Modules Using the Neural-Genetic Algorithm Considering Mathematical Model of the Solar Orbit and Position

This paper presents a method which combines an artificial neural network and a genetic algorithm (ANNGA) in determining the tilt angle for photovoltaic (PV) modules. First, a Taguchi experiment was used to perform an efficient experimental design and analyze the robustness of the tilt angles for fixed south-facing PV modules. Following, the results from the Taguchi experiment were used as the learning data for an artificial neural network (ANN) model that could predict the tilt angles at discrete levels. Finally, a genetic algorithm method was applied to obtain a robust tilt angle setting of the tilt angle of PV modules with continuous variables. The objective is to maximize the electrical energy of the modules. In this study, three Taiwanese areas were selected for analysis. The position of the sun at any time and location was predicted by the mathematical procedure of Julian dating; then, the solar irradiation was obtained at each site under a clear sky. To confirm the computer simulation results, experimental system are conducted for determining the optimum tilt angle of the modules. The results show that the seasonal optimum angle is 26.4 (deg.) for February-March-April; -9.47(deg.) for May-June-July, 21.32(deg.) for August-September-October and 53.13(deg.) from November-December-January in the Taiwan area.

Optimal design of discrete-value tilt angle of PV using sequential neural-network approximation and orthogonal array

This report presents a method for combining sequential neural-network approximation and orthogonal arrays (SNAOA) to determine the tilt angle for photovoltaic (PV) modules. An orthogonal array is first conducted to obtain the initial solution set. The set is then treated as the initial training sample. Next, a back-propagation sequential neural network is trained to simulate the feasible domain for seeking the optimal tilt angle of PV modules. The size of the training sample is greatly reduced due to the use of the orthogonal array. In addition, a restart strategy is also incorporated into the SNAOA so that the searching process may have a better opportunity to reach a near global optimum. The objective is to maximize the output power energy of the modules. In this study, seven Taiwanese areas were selected for analysis. The sun’s position at any time and location was predicted by the mathematical procedure of Julian dating; then, the solar irradiation was obtained at each site under a clear sky. To confirm the computer simulation results, an experimental system is conducted for determining the optimal tilt angle of the PV modules. The results show that the annual optimal angle for the Taipei area is 23.25°; for Taichung, 22.25°; for Tainan, 21.25°; for Kaosiung, 20.75°; for Hengchung, 20.25°; for Hualian, 22.25°; and for Taitung, 21° in Taiwan, and the actual best annual tilt angles are close to the computer simulation results. Additional results related to SNAOA are also reported and discussed as well.