Design and performance evaluation of a solar tracking panel of single axis in Colombia

This paper presents the mechanical design of a single axis solar tracking system, as well as the electronic design of a system that to record in real time the electric power delivered by the solar tracker and to evaluate its performance. The interface was developed in Labview and it compares the power supplied by the tracker with the power supplied by static solar panel of the same characteristics. The performance is initially simulated using Pv-Syst software, and later validated with the data obtained by the interface. As a result, the use of the solar tracker increases the power delivered by a minimum of 19%, and it can go as high as 47.84%, with an average in increase in power of 19.5% in the monthly energy production. This experimental result was compared with the simulation by Pv-Syst software and shows a difference of only 2.5%, thus validating the reliability of the simulation. This behavior pattern coincides with previous studies carried out for equatorial latitudes

Summary of photovoltaic system performance models

A detailed overview of photovoltaics (PV) performance modeling capabilities developed for analyzing PV system and component design and policy issues is provided. A set of 10 performance models are selected which span a representative range of capabilities from generalized first order calculations to highly specialized electrical network simulations. A set of performance modeling topics and characteristics is defined and used to examine some of the major issues associated with photovoltaic performance modeling. Each of the models is described in the context of these topics and characteristics to assess its purpose, approach, and level of detail. The issues are discussed in terms of the range of model capabilities available and summarized in tabular form for quick reference. The models are grouped into categories to illustrate their purposes and perspectives

ACTIVE OPTIMAL CONTROL STRATEGIES FOR INCREASING THE EFFICIENCY OF PHOTOVOLTAIC CELLS

Energy consumption has increased drastically during the last century. Currently, the worldwide energy consumption is about 17.4 TW and is predicted to reach 25 TW by 2035. Solar energy has emerged as one of the potential renewable energy sources. Since its first physical recognition in 1887 by Adams and Day till nowadays, research in solar energy is continuously developing. This has lead to many achievements and milestones that introduced it as one of the most reliable and sustainable energy sources. Recently, the International Energy Agency declared that solar energy is predicted to be one of the major electricity production energy sources by 2035. Enhancing the efficiency and lifecycle of photovoltaic (PV) modules leads to significant cost reduction. Reducing the temperature of the PV module improves its efficiency and enhances its lifecycle. To better understand the PV module performance, it is important to study the interaction between the output power and the temperature. A model that is capable of predicting the PV module temperature and its effects on the output power considering the individual contribution of the solar spectrum wavelengths significantly advances the PV module designs toward higher efficiency. In this work, a thermoelectrical model is developed to predict the effects of the solar spectrum wavelengths on the PV module performance. The model is characterized and validated under real meteorological conditions where experimental temperature and output power of the PV module measurements are shown to agree with the predicted results. The model is used to validate the concept of active optical filtering. Since this model is wavelength-based, it is used to design an active optical filter for PV applications. Applying this filter to the PV module is expected to increase the output power of the module by filtering the spectrum wavelengths. The active filter performance is optimized, where different cutoff wavelengths are used to maximize the module output power. It is predicted that if the optimized active optical filter is applied to the PV module, the module efficiency is predicted to increase by about 1%. Different technologies are considered for physical implementation of the active optical filter

PV systems design optimization as function of the climatic conditions

The present work evaluates some of the weaknesses affecting the solar photovoltaic energy deployment in the frame of the Sustainable Developing Goals (SDG) of the UN. As one of the most promising renewable energy sources due to its resource availability, modularity and competitive costs, the rapid growth of the PV in terms of new designs and module technologies needs to be assessed. An adequate analysis of these developments requires not only the energy production to be evaluated, also technologic lifecycle, including economic and environmental costs, must be considered. To that end, an analysis of the photovoltaic systems designs, adequate technology selection and sizing methods is done as function of the climatic conditions. The suitability of installing solar trackers compared to fixed tilt racking designs is assessed as function of the diffuse fraction including the economic and energetic costs. This analysis is extrapolated to a worldwide extent as function of the Köppen climate classification. Besides, the behaviour of the different PV modules commercial technologies is evaluated as function of the climate. Finally, the limitations of the most frequent sizing methods for stand-alone PV systems are evaluated in terms of user consumption regimes and the climatic conditions. A simple algorithm allows to optimize the PV system sizing in terms of the economic and energetic costs

A Decision Support System to Analyze, Predict, and Evaluate Solar Energy System Performance: PVSysCO (photovoltaic System Comparison)

In 2010, the U.S. Department of Energy announced the SunShot Initiative, which aims to reduce the total installation cost of solar technologies by 75% between 2010 and 2020. This implies that solar energy is a top priority in the U.S. and many other countries. The purpose of this dissertation research is focused on creating a model to better understand the performance and reliability of photovoltaic (PV) energy systems over time. The model will be used to analyze, predict, and evaluate the performance of PV systems, taking into consideration technological and geographical location attributes. The overall research goal is to build a Solar Energy Blue Book, conceptually similar to the Kelley Blue Book, which allows consumers to estimate the value of a used car. The Solar Energy Blue Book, a solar energy system evaluation tool, will allow consumers to estimate the value of a used solar energy system, taking into consideration many factors, such as latitude (which determines the quantity of incoming sunlight) and zip code (which determines the approximate cost of electricity). The Solar Blue Book will allow potential solar energy system consumers the opportunity to understand the return on investment for new and in particular, used solar energy systems

Technical Energy Potential Of Floating PV Power Plants (FPV)

Energy demand is significantly expanding worldwide nowadays, as a result the capacity of the electricity generating units come into question. Based on the World Energy Balances Highlights (2020 edition) [19], it was found that the world electricity generation is about 26, 618, 881 GW h from all sources proposed i.e. "Fossil fuels, Nuclear, Renewable Energies". Consequently, there would be too much negative effects on the environment due to the continuous usage of fossil contents which are used later for the electricity generation. The electric sector obsessed about 42 % of the energy demand in 2015 and it is expected to raise to 47 % in the next 20 years. It is remarkable that the non-renewable sources of energy affect the environment negatively and increase the global warming when they are used for the generation of the electricity. Despite the constantly increasing of the electricity demand, the dependency of the non- renewable sources on energy must be reduced in order to lower the amount of the greenhouse gases. In 2018, the renewable energy generation share has became 13.5 % of the total world energy supply including (Solar PV, Solar thermal, Wind, Bio-fuels, Hydro, and Geothermal energies) [19]. The solar photovoltaic power generation has increased by about 22 % in 2019, and namely to 720 T W h. It can be considered by this increase as 3 % of the total world electricity generation share. In the meanwhile, the main challenge of installing normal ground-mounted PV power plants is the space. Large surface areas must be available in order to benefit well from such power plants. In order to tackle this issue, another generation of PV power plants came into question which is; Floating Photovoltaic (FPV). This technology depends on installing the PV modules over the surface of water, in order to profit not only from the extra space where water body is located, but also from the cooling effect, which improves the performance of PV modules and particularly, the performance ratio as well as the electrical efficiency. Furthermore, a tracking model can be easily applied to this kind of PV, since the surface of water offers a smooth medium for changing the modules orientation over the whole day. The floating photovoltaics have a lot of benefits over the ground-mounted type, for example; the land occupancy, as they do not require a land space, since they are installed and erected on the surface of water, except only the needed spaces which are demanded by the electrical equipment, switch gears. Although, FPV plants are considered relatively more expensive than the land-based photovoltaic power plants, but they empower the possibility to avoid competing with the agriculture and green zones. Moreover, to prevent the competing with the agriculture and green lands, some countries encourage the investors to install PV on the water bodies by increasing the rate of incentives. For instance, Japan has boosted the Feed-In-Tariff (FIT) for the floating photovoltaic over the FIT of the ground-mounted PV. In particular, the floating PV array in Sanuki, Kagawa prefecture, which has an installed capacity of 1.5 MW and expected to meet the consumption of more than 500 local households, will purchase the electricity at a Feed-In-Tariff of JPY 32 per kWh (0.26 e/kW h)[20]. In this work, two main models are built in order to calculate the PV module temperature and the surface temperature of the ground and water in order to; 1) determine the how the surface temperature of the ground and water affects the module temperature and namely the output power, 2) predict the temperature of both FPV, 3) calculate the to the instantaneous efficiency and power of the FPV and GPV modules, and 4) predict the annual yield of floating PV module

Origami and Kirigami Design Principles for Optical Tracking, Energy Harvesting, and Other Applications

Origami and kirigami (the folding and cutting of paper, respectively, to achieve a desired shape) have been used in engineering to develop airbags, optical components, deployable spaceborne solar arrays, reprogrammable metamaterials, and load-bearing metal structures. Despite these efforts however, little has been shown beyond the packaging and load-bearing advantages of these three-dimensional approaches to structural design. This dissertation describes the use of dynamic, three-dimensional design principles to develop multifunctional mechanical and optoelectronic devices with improved performance, decreased fabrication costs, and greater economic value. First, we introduce a novel method of integrated, low-profile solar tracking whereby a simple kirigami pattern in thin-film gallium-arsenide solar cells enables tracking at the substrate level simply by stretching the sheet. The new tracker is inherently lightweight and very low profile; it is less susceptible to wind loading, which greatly reduces tracking system complexity, size, and cost, while also enabling new applications. System performance is considered as a function of cut geometry, materials selection, and geographic location, and optimized trackers are shown to generate up to 40% more energy per solar cell area over the course of a day relative to a stationary, flat panel module. Electrical and mechanical robustness are also considered with implications towards long-term solar tracking applications (i.e. >10,000 actuation cycles). Subsequently, we discuss a multifunctional system that combines kirigami solar tracking and integrated concentration optics to further reduce the overall cost of solar electricity. Optical design, mechanical response, and materials selection are considered to maximize optical and power concentration factor while also maintaining a simple design philosophy. The final system is shown to provide ~60x solar concentration, and further modifications will enable power concentration factors greater than 100x. Finally, similar design principles are extended to develop new applications including textured surfaces for flow manipulation and drag steering, kirigami patterns for tunable antennas, and origami tessellations for novel forms of electrochemical energy storage.PHDMaterials Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136941/1/allamour_1.pd

Performance Analysis Of Hybrid Ai-Based Technique For Maximum Power Point Tracking In Solar Energy System Applications

Demand is increasing for a system based on renewable energy sources that can be employed to both fulfill rising electricity needs and mitigate climate change. Solar energy is the most prominent renewable energy option. However, only 30%-40% of the solar irradiance or sunlight intensity is converted into electrical energy by the solar panel system, which is low compared to other sources. This is because the solar power system\u27s output curve for power versus voltage has just one Global Maximum Power Point (GMPP) and several local Maximum Power Points (MPPs). For a long time, substantial research in Artificial Intelligence (AI) has been undertaken to build algorithms that can track the MPP more efficiently to acquire the most output from a Photovoltaic (PV) panel system because traditional Maximum Power Point Tracking (MPPT) techniques such as Incremental Conductance (INC) and Perturb and Observe (P&Q) are unable to track the GMPP under varying weather conditions. Literature (K. Y. Yap et al., 2020) has shown that most AIbased MPPT algorithms have a faster convergence time, reduced steady-state oscillation, and higher efficiency but need a lot of processing and are expensive to implement. However, hybrid MPPT has been shown to have a good performance-to-complexity ratio. It incorporates the benefits of traditional and AI-based MPPT methodologies but choosing the appropriate hybrid MPPT techniques is still a challenge since each has advantages and disadvantages. In this research work, we proposed a suitable hybrid AI-based MPPT technique that exhibited the right balance between performance and complexity when utilizing AI in MPPT for solar power system optimization. To achieve this, we looked at the basic concept of maximum power point tracking and compared some AI-based MPPT algorithms for GMPP estimation. After evaluating and comparing these approaches, the most practical and effective ones were chosen, modeled, and simulated in MATLAB Simulink to demonstrate the method\u27s correctness and dependability in estimating GMPP under various solar irradiation and PV cell temperature values. The AI-based MPPT techniques evaluated include Particle Swarm Optimization (PSO) trained Adaptive Neural Fuzzy Inference System (ANFIS) and PSO trained Neural Network (NN) MPPT. We compared these methods with Genetic Algorithm (GA)-trained ANFIS method. Simulation results demonstrated that the investigated technique could track the GMPP of the PV system and has a faster convergence time and more excellent stability. Lastly, we investigated the suitability of Buck, Boost, and Buck-Boost converter topologies for hybrid AI-based MPPT in solar energy systems under varying solar irradiance and temperature conditions. The simulation results provided valuable insights into the efficiency and performance of the different converter topologies in solar energy systems employing hybrid AI-based MPPT techniques. The Boost converter was identified as the optimal topology based on the results, surpassing the Buck and Buck-Boost converters in terms of efficiency and performance. Keywords—Maximum Power Point Tracking (MPPT), Genetic Algorithm, Adaptive Neural-Fuzzy Interference System (ANFIS), Particle Swarm Optimization (PSO