Search

This paper analytically derives a stability test for the probability distribution of a random variable that follows the Edgeworth–Sargan density, also called Gram–Charlier. The distribution of the test is a weighted sum of Chi-squared densities of increasing degrees of freedom, starting with the standard equivalent Chi-squared under the same conditions. The weights turn out to be linear combinations of the parameters of the distribution and the moments of a Gaussian density, and can be computed exactly. This is a convenient result, since then the probability intervals can be easily calculated from existing Chi-squared distribution tables. The test is applied to assess the weekly solar irradiance data stability for a twelve-year period. It shows that the density is acceptably stable overall, except for some eventual and localised dates. It is also shown that the usual probability intervals implemented in stability testing are larger than those of the equivalent Chi-squared distribution under comparable conditions. This implies that the common upper tail interval values for rejecting the null stability hypothesis are larger.

This paper proposes an energy management strategy (EMS) for a hybrid stand-alone plant destined to supply controllable loads. The plant is composed of photovoltaic panels (PV), a wind turbine, a diesel generator, and a battery bank. The set of the power sources supplies controllable electrical loads. The proposed EMS aims to ensure the power supply of the loads by providing the required electrical power. Moreover, the EMS ensures the maximum use of the power generated by the renewable sources and therefore minimizes the use of the genset, and it ensures that the batteries bank operates into the prefixed values of state of charge to ensure their safe operation. The EMS provides the switching control of the switches that link the plant components and decides on the loads’ operation. The simulation of the system using measured climatic data of Mostoles (Madrid, Spain) shows that the proposed EMS fulfills the designed objectives.

The aim of the article is to present the development of photovoltaic energy in the EU countries as one of the alternatives to fossil fuels. The article was prepared on the basis of secondary information and statistical data on the photovoltaic energy market in EU countries, and three hypotheses were formulated: H1—There is a statistically significant correlation between a country’s long-term orientation and its use of photovoltaic energy in European Union countries; H2—There is a statistically significant correlation between GDP per capita and photovoltaic energy use in European Union countries; and H3—There is a relationship between climate and photovoltaic energy use in European Union countries. Correlation coefficients and the Guilford classification were used to analyse the data. Data analysis has shown that photovoltaic energy is the second fastest-growing energy source in the EU, after wind energy. In 2020, 134 TWh of solar energy was produced in the EU countries. Based on the analysis, it can be concluded that there is a statistically significant correlation between the production of photovoltaic energy per person and the level of GDP per capita in the EU countries (Hypothesis 2). Germany and the Netherlands produce the most solar energy. The studies did not confirm Hypothesis 3; however, it can be seen that countries such as Germany, Belgium and the Netherlands have the highest PV energy efficiency compared to average temperature values. A data analysis showed statistically significant correlations between the country’s long-term orientation in the use of photovoltaic energy (Hypothesis 1). In the case of Germany and Belgium, the long-term orientation indicator is very high above 80, while Portugal, Poland and Finland have the lowest indicator, from 30 to 40.

The control of renewable energy sources is more complicated when used as hybrid energy systems. Power electronic circuits are used to convert and store the electrical energy generated from renewable energy sources. However, the high frequency switching in these power electronic circuits complicates the control of the systems. Advanced control methods are required to control such complex systems. In this study, a hybrid energy system was devised and implemented experimentally to first convert the solar and wind energy to electrical energy and, then to store and use it through a common bus voltage. The study focused on buck–boost converters' parallel connection and deviations from the common bus voltage level were taken into account. The converter system's control was tested with FLC as the best solution, and the results obtained from simulation and experiments were compared. The experimental setup was controlled with a fast and real-time digital signal processor (DSP). Current and voltage measurement circuits, MOSFET drivers, and parallel-connected buck–boost converters were realized experimentally. The simulations and experimental results were suitable for various solar and wind conditions. This hybrid system was also tested at low solar radiation and at low wind speeds to stabilize common bus voltage and energy harvesting. [ABSTRACT FROM AUTHOR]

This manuscript proposes a series of global models to estimate optimum annual tilt angle (β o p t ) as a function of local variables (latitude, diffuse fraction and albedo) based on the hourly irradiance data of 14,468 sites spread across the globe from the One Building database. As a result, these models can be used for any location in the absence of local meteorological data. First, a polynomial regression model, applicable worldwide, is proposed to estimate β o p t as a function of latitude. This model fits the global data considered with a 2% RMSE error. Average energy losses are estimated to be 1% for a 10° variation from β o p t . A variation of 40° with respect to β o p t , implies a 12–18% energy loss depending on latitude. In addition, if only latitude is considered to estimate β o p t , different expressions should be used for latitudes > 50 ° depending on the hemisphere. These variations are a result of the influence of diffuse irradiance on β o p t , due to the fact that sites with higher amounts of diffuse irradiance have a lower β o p t . Secondly, a polynomial surface regression model to estimate β o p t as a function of latitude and the annual diffuse fraction is proposed improving the results, reaching a 0.7% RMSE error. Thirdly, a simplified polynomial surface regression model to estimate β o p t as a function of latitude and albedo (without the influence of the diffuse fraction) is proposed, and finally a model gathering all three variables under study (latitude, annual diffuse fraction and albedo) to calculate the optimum tilt angle is presented. • Model to estimate the annual optimum tilt angle for any location worldwide. • Search based model based on polynomial regression, using data from 14468 sites. • Studied influence variables on optimum tilt: hemisphere, diffuse fraction and albedo. • The energy loss when the optimum tilt angle is misestimated increases with latitude. • An estimation of a 0.2 annual albedo is only accurate for absolute latitudes <60°. [ABSTRACT FROM AUTHOR]

Water treatment has been extensively studied; however, only a few studies have considered it in isolated sites that do not have electric supply, which is a major inconvenience for inhabitants of rural areas. In this paper, the aim was to develop and implement a photovoltaic generator (PVG) that powers a pumping system, and water treatment with ozone. First, the PVG panel's orientation was optimized using response surface modelling to identify the optimum operating orientation angles. Then, this configuration was applied to supply a water treatment system to bleach dye-contaminated water and disinfect well water. The experimental results are presented and discussed to show that our system can be used to treat well water in isolated sites. [ABSTRACT FROM AUTHOR]

One of the UN Sustainable Development Goals is the supply of sustainable energy even where no electrical grid is available. The photovoltaic rural electrification programs are the most common systems implemented in remote areas, especially in developing countries. These programs include the systems installation and their maintenance for a given period. Installation costs and even spare parts costs over time are usually well estimated. However, design and cost estimation of the maintenance systems is a difficult task, whose wrong management has often resulted in the failure of these electrification programs. In this work, a methodology for designing maintenance systems and estimating costs is presented. The methodology includes a mixed integer linear programming model and a rule based expert system. The mathematical programming model allows obtaining the optimal size and accurate cost estimation of a maintenance system, based on precise information about the installed systems. This model is calibrated and validated with real running programs and will be used to get an enlarged data set of simulated cases if needed. The rule based expert system is obtained from the data set applying classification and regression methods with general information about the region and program to be run. It can be used for designing programs or for companies making decisions about being involved in a program to be developed. The methodology has been applied to real Morocco programs. [ABSTRACT FROM AUTHOR]

The photovoltaic systems connected to the grid consist of a renewable technology growing in the world energy matrix. However, for the competitiveness and diffusion of this technology to be boosted, it is necessary to integrate different actors in the photovoltaic value chain in a collaborative environment to overcome technical, economic, managerial, political and market barriers. Thus, the objective of this article is to identify the actors that compose the sector's value chain and the main factors that influence competitiveness and the adoption of distributed generation of photovoltaic energy. For this, a systematic review of the literature was conducted using the review protocol Preferred Reporting Items for Systematic Reviews and Meta-Analyzes, resulting in 81 articles distributed between 1989 and 2019. The conclusions point out that the actors in the value chain and the factors that influence the sector's competitiveness are concentrated in several spheres, presenting dependency relationships established in the upstream, midstream, downstream, and auxiliary chain segments. The developed value chain presents uniquely the compilation of interactions between different actors. Also, the factors that make photovoltaic technology competitive are discussed, helping the government, investors, companies, electricity concessionaires, and consumers to expand the diffusion of this renewable energy source and contribute to economic, environmental, and social developments. [ABSTRACT FROM AUTHOR]

Copyright of DYNA - Ingeniería e Industria is the property of Publicaciones Dyna SL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Anuario do Instituto de Geociencias is the property of Universidade Federal do Rio de Janeiro, Instituto de Geociencias and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The increasing penetration of photovoltaic (PV) energy in power grids will impose system instability issues, especially in the occurrence of faults. However, very limited research has been conducted on the low‐voltage ride‐through (LVRT) control of PV systems in the low‐voltage distribution networks (LVDNs) with predominantly resistive line impedances. To fulfil this remaining gap, the effects of active current injection (ACI) on the grid voltage support in LVDN is mathematically analysed in this study. Subsequently, a novel LVRT control scheme for the PV grid‐forming inverter is proposed, where the control distinguishes itself from other existing methods due to its optimisation of ACI and PV energy harvesting with the premise of system safety and specified reactive current injection as per grid codes. Multi‐mode control modes are involved in the proposed method for dealing with different environmental conditions and voltage dips. Meanwhile, the DC‐link voltage is adaptively operated in a self‐adjustable control structure for improving grid resilience. The effectiveness of the proposed control method is verified by simulations in MATALB Simulink and hardware experiments on a PV microinverter. Compared with the traditional LVRT control, the post‐fault power recovery and voltage support capability can be significantly improved. [ABSTRACT FROM AUTHOR]

Hydrogen production systems supplied by photovoltaic solar energy have nonlinear dynamics and discontinuities which must be taken into account when a control system is applied. The main purpose of the control system is to maintain the electrolyzer current at the desired operating point and, at the same time, to optimize the grid energy consumption despite the solar energy variability. Classic controllers, like PID ones, are not able to obtain good performance over the whole operation range of these kinds of plants because of the aforementioned characteristics. To overcome these limitations, an optimal control strategy and a linear hybrid model predictive controller (HMPC) are applied to a hydrogen production system in this work. Regarding the optimal control design, a systematic framework is presented in order to obtain the optimal (in the sense of minimal grid energy consumption) trajectory of the states by converting the control problem into a boundary value problem by means of the Pontryagin's Maximum Principle. Interestingly, the resulting control law is explicit and piecewise continuous. Regarding the linear HMPC strategy, a mixed logical dynamical description of the linearized equations of the system is considered in order to obtain the control law by solving an optimization problem in the form of a mixed integer quadratic programming. For this control strategy three cost functions associating the grid energy consumption and the electrolyzer efficiency are presented. The proposed controllers are tested through numerical simulations for both the nominal and uncertain cases and different performance indexes are considered. Finally, a discussion of the main advantages and disadvantages of each controller in real-life applications is presented. • Two controllers are designed for the control problem of a hydrogen production system. • An explicit optimal control law is derived. • The HMPC algorithm approximates the optimal behavior. • Simulation tests with real data are performed for the nominal and uncertain cases. • The advantages and drawbacks of each of the proposed controllers are discussed. [ABSTRACT FROM AUTHOR]

Satellite-measured radiances are obviously of great interest for photovoltaic (PV) energy prediction. In this work we will use them together with clear sky irradiance estimates for the nowcasting of PV energy productions over peninsular Spain. We will feed them directly into two linear Machine Learning models, Lasso and linear Support Vector Regression (SVR), and two highly non-linear ones, Deep Neural Networks (in particular, Multilayer Perceptrons, MLPs) and Gaussian SVRs. We shall also use a simple clear sky-based persistence model for benchmarking purposes. We consider prediction horizons of up to 6 h, with Gaussian SVR being statistically better than the other models at each horizon, since its errors increase slowly with time (with an average of 1.92% for the first three horizons and of 2.89% for the last three). MLPs performance is close to that of the Gaussian SVR for the longer horizons (with an average of 3.1%) but less so at the initial ones (average of 2.26%), being nevertheless significantly better than the linear models. As it could be expected, linear models give weaker results (in the initial horizons, Lasso and linear SVR have already an error of 3.21% and 3.46%, respectively), but we will take advantage of the spatial sparsity provided by Lasso to try to identify the concrete areas with a larger influence on PV energy nowcasts. [ABSTRACT FROM AUTHOR]

With the increase in demand for energy, penetration of alternative sources of energy in the power grid has increased. Photovoltaic (PV) energy is the most common and popular form of energy sources which is widely integrated into the existing grid. As solar energy is intermittent in nature, to ensure uninterrupted and reliable power supply to the prosumers, it is essential to forecast the solar irradiance. Accurate solar forecasting is necessary to facilitate large-scale modelling and deployment of PV plants without disrupting the quality and reliability of the power grid as well as to manage the power demand and supply. There are various methods to predict the solar irradiance such as numerical weather prediction methods, satellite-based approaches, cloud-image based methodologies, data-driven methods, and sensor-network based approaches. This study gives an overall review of the different resources and methods used for forecasting solar irradiance in different time horizons and also gives an extensive review of the sensor networks that are used for determining solar irradiance. The various error metrics and accessible data sets available for the sensor networks are also discussed that can be used for validation purposes. [ABSTRACT FROM AUTHOR]

Electroflocculation is a technique for liquid effluent treatment that has been widely used due to simplicity in operation and to the possibility of application in different types of effluents. This study aimed to evaluate the electroflocculation treatment efficiency, monitoring and controlling an effluent automatically from the textile industry, also considering a feasibility study to photovoltaic generation application. The electrofloculation tests were performed with raw effluent, in a batch reactor containing aluminum electrodes and glass vat. Sensors and a microcontroller make up the electronic system, which monitors and controls voltage, temperature, and time variables and also processes and sends the data to the computer. The tests consist of applying 1 and 2A current in a 3 liters volume taking aliquots in 5, 10, 15 min. The parameters analyzed were: pH, conductivity, turbidity, Chemical Oxygen Demand, and absorbance sweep in 200 to 800 nm range. The samples presented in the visible region a band with the maximum absorbance at 670nm; thus, it was decided to evaluate the system at this wavelength. The results of the electroflocculation tests showed that the best removal of turbidity, COD, and absorbance at 670nm occurred in the conditions of 2A/10min, with average efficiency above 70%. A photovoltaic system was projected to meeting the demand for the energy electroflocculation system, whose analysis found that the best strategy is connecting the photovoltaic system to the electric power grid. Through financial simulation, It was identified as a significant energy-saving which offsets costs related to system installation. In conclusion, the system developed is efficient in textile effluent treatment and that the photovoltaic system meets the demand for energy from the electroflocculation system, ensuring project sustainability. [ABSTRACT FROM AUTHOR]

Copyright of Sustainability in Debate / Sustentabilidade em Debate is the property of University of Brasilia, Center for Sustainable Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Sustainability in Debate / Sustentabilidade em Debate is the property of University of Brasilia, Center for Sustainable Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The increasing presence of photovoltaic (PV) generation in the energy mix demands improved forecasting tools which can be updated in an almost continuous basis. Satellite-based information lends itself naturally to this purpose and here it is used to nowcast hourly PV energy production for horizons up to six hours over Peninsular Spain and two islands, Majorca in the Mediterranean Sea and Tenerife in the Atlantic Ocean. This paper compares a single model-based on same-day numerical weather prediction (NWP) with hourly refreshed models which either only use satellite-based measurements or which combine both NWP same-day forecasts and satellite data. As shown in the experiments, the satellite–NWP combination gives very good nowcasting results, clearly superior to those achievable separately by either approach. [ABSTRACT FROM AUTHOR]

The increasing gap between electricity prices and feed-in tariffs for photovoltaic (PV) electricity in many countries, along with the recent strong cost degression of batteries, led to a rise in installed combined PV and battery systems worldwide. The load profile of a property greatly affects the self-consumption rate and, thus, the profitability of the system. Therefore, insights from analyses of residential applications, which are well studied, cannot simply be transferred to other types of properties. In comparison to residential applications, PV is especially suitable for municipal buildings, due to their better match of demand and supply. In order to analyze the value of additional batteries, municipal PV battery systems of different sizes were simulated, taking load profiles of 101 properties as inputs. It was found that self-consumption differs significantly from households, while different types of municipal buildings are largely similar in terms of the indicators analyzed. The share of electricity consumed during summertime was found to have the most significant impact on the self-consumption rate for most considered system sizes. Due to lower electricity tariffs and lower increases in self-consumption provided through batteries in municipal buildings, the investment into a battery is not economically advantageous in most of the cases considered. • The specifics of municipal buildings are focused in this PV battery system study. • Profitability indicators are presented for a large range of system configurations. • Measured data from >100 buildings were used for the profitability analysis. • Most up-to-date economic data was used to get practically meaningful results. • Battery investments were found to be not advantageous in most, but not all settings. [ABSTRACT FROM AUTHOR]

To construct a long-term energy plan for renewable energies such as photovoltaics (PV), the influence of meteorological conditions on energy yield must be considered. It is necessary to understand how climate change impacts energy generation. For that purpose, a method to estimate PV energy generation considering climate change scenarios was developed. The developed method can estimate hourly generation amounts with spatial resolutions of 1-km mesh. It was applied to Fukushima Prefecture, located in the northeast region of Japan. To establish future scenarios three Representative Concentration Pathways (RCP) and seven Global Climate Models (GCM) were analyzed, and uncertainties caused by differences in future scenarios were investigated. The results show that annual generation of PV energy was estimated to increase on average by 1.7% in 2030, 3.9% in 2050, and 4.9% in 2070 due to climate change. Energy plans and adaptation actions are expected to be performed so the country is prepared for future impacts. • Climate change impacts on future PV energy generation in Japan were investigated. • Uncertainty of future climate change was evaluated using multiple GHG emission scenarios and GCMs. • Annual PV output increases on average by 1.7% in 2030, 3.9% in 2050, and 4.9% in 2070. [ABSTRACT FROM AUTHOR]

Copyright of TURyDES is the property of TURYDES and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Validation of the photovoltaic estimation model SoL using data from real facilities. • The results for SoL are compared to other state-of-the-art PV estimators. • SoL presents more accurate results, despite being a simple and more efficient model. • A self-shading model is proposed for SoL as a new enhancement feature. • The self-shading feature is validated against real data and proved useful. The estimation of electrical power generation in photovoltaic (PV) grid-connected systems based on meteorological data is a nontrivial, highly useful task, for instance to achieve accurate energy assessment. Widely used PV generation simulators are PV Systems (PVsyst), System Advisor Model (SAM) and PVLib. These simulators are characterized by presenting numerous features and providing complete results, however the PV estimation model SoL is an example of a new approach to PV generation estimation. SoL is characterized by its simplicity and computational efficiency. The objective of this paper is validating the recently published SoL model using real data from two PV locations for several years and facilities and comparing the results with those of three other PV simulators, namely PVsyst (in Spain), SAM (in Denver) and PVLib (both). It has been found that SoL estimates power production accurately for both locations and its estimations are more precise than those given by PVsyst, SAM and PVLib. It proves to be more computationally efficient than PVsyst, it can work with higher resolutions than SAM and PVsyst and requires fewer inputs than PVLib, SAM or PVsyst. Finally, a self-shading model is proposed as an enhancement for the SoL model. The number of inputs required is minimal, and it is an approximate yet efficient model. The estimation when using the self-shading enhancement is even more accurate than the previous estimation for SoL in locations where self-shading is evident. SoL proves to be an appropriate model for power estimation, and its results are enhanced when using the self-shading model proposed in this paper. [ABSTRACT FROM AUTHOR]

This paper focuses on the control of large-scale grid-connected photovoltaic system. The proposed system is composed of two conversion stages: the first stage contains four PV arrays, each one connected to an individual DC/DC converter (boost converter), while the second stage is a five-level neutral point clamped (NPC) inverter tied to the grid. Each DC-link capacitor input of the NPC inverter is connected to the output of the DC/DC boost converter. In order to enhance the energy harvesting capability of the proposed system, different controllers based on finite-set model predictive control (FS-MPC) are developed and presented. A fast voltage-oriented maximum power point tracking performed by FS-MP current controller (FS-MPCC) is investigated and applied for each boost converter to maximize the produced power from each PV array. Furthermore, a FS-MPC algorithm is proposed to control the centralized five-level NPC inverter. The purposes of the developed controllers are: track the MPP rapidly and accurately under sudden irradiation changes, ensure the balance of the four DC-link capacitor voltages whatever the difference between the extracted powers from each PV system unit, inject the reactive power demanded by the grid operator and also minimize the switching frequency of the five-level NPC inverter. The results obtained through MATLAB/Simulink and Simpower toolbox packages prove that the proposed control scheme provides better performance in comparison with conventional control scheme. Moreover, a high grid current quality and perfect DC-link capacitor voltages balancing are ensured under contrast of extract powers from each PV system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of International Social Research is the property of Journal of International Social Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we present our contribution in photovoltaic energy optimization subject. In this research work, the goal is to determinate fastly the optimal PV Module working point, allowing maximum power extraction. In this work we use DC-DC Boost converter to control the working point, by adjusting PV voltage trough duty cycle. In order to achieve our goal, we use the combination of incremental conductance MPPT technique and DC-DC Boost converter backstepping control. The validation of this control is made by Matlab simulation; the obtained results prove its effectiveness and its good maximum power tracking dynamics for different irradiance and temperature profiles. [ABSTRACT FROM AUTHOR]

The article describes the current situation and the share of the renewable energy sources in the electricity system of Valle del Cauca Department in Colombia. The research involves an interpretation of the institutional framework regarding renewable energies in this country, a general presentation of the worldwide energy system, and the Colombian electricity system. The next issue refers to the share of renewable sources in electricity generation developed in Valle del Cauca. It mainly refers to the production and infrastructure of hydroelectric power, bioenergy, and photovoltaic energy. Then, the article focuses on the electric potential of renewable energies held in the Department. Finally, there is a set of discussions on how Valle del Cauca has taken advantage of the institutional framework regarding the exploitation and use of renewable energies. [ABSTRACT FROM AUTHOR]

Research Objective: This research aims to identify issues and opportunities for the expansion of electric power generation with large-scale photovoltaic solar cells in Brazil. Methodology/approach: The methodology includes in-depth interviews with multiplestakeholders, including industry, public sector, academia, and Non-Governmental Organizations representatives. Originality/Relevance: Despite the progress in public policies to incorporate new measures to foster photovoltaic solar energy use, results are still quite insignificant. Therefore the main contribution of this research is to help to understand the main reasons for the low level of participation in photovoltaic solar energy use in the Brazilian energy matrix. Main results: A favorable mix of public policies, including subsidies and financing, were fundamental for solar energy growth in the countries studied. In Brazil, however, public policy is fragmented and incomplete, as financing mechanisms and long-term low interest rates for manufacturers, investors and consumers are lacking in order to significantly expand the use of this alternative. Theoretica/Metodological contributions: The absence of strategic vision from the government and the business sector hinders seizing solar energy use in Brazil preventing the country from the benefits associated to its comparative advantages in this segment. Conclusion: Among the opportunities missed by the country stand out the jobs generated in the production chain and its contribution to social inclusion and reduction of environmental impacts when compared to traditional systems of power generation. [ABSTRACT FROM AUTHOR]

Copyright of ESTOA: Revista de la Facultad de Arquitectura y Urbanismo de la Universidad de Cuenca is the property of ESTOA Revista de la Facultad de Arquitectura y Urbanismo de la Universidad de Cuenca and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ambiência is the property of Revista Ambiencia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The procurement auction scheme for long-term photovoltaic (PV) energy contracts is being implemented in various countries to ensure stable profits for potential PV generators. However, in most of these auction formats, there is a deficiency in that they consider only the contract price and capacity, neglecting to account for the uncertainty of generation efficiency. In this regard, this study proposes a procurement auction scheme for long-term photovoltaic (PV) energy contracts based on mechanism design theory. We developed a two-dimensional auction model in which PV generators bid their cost and capacity. The energy buyer then determines the winners and enters into contracts with them for a fixed period. We incorporated the capacity factor into the payoff functions of both the buyer and the sellers to reflect different generation efficiencies of generators. Following the revelation principle, we characterized the incentive-compatible, individually rational direct mechanism that maximizes the buyer's expected payoff during the contract period. We also proposed a computation algorithm to implement the auction. Numerical analysis using data from the Korean PV auction market suggested that the proposed model demonstrates results similar to the uniform price auction in terms of the levelized cost of electricity and contract price, and these results are lower than those of the Vickrey auction. Furthermore, despite the fact that the proposed auction results in a slight increase in social costs (approximately 1% more than the Vickrey auction), it maximizes the expected procured electricity and the auctioneer's payoff. • An optimal procurement auction for long-term photovoltaic energy contracts is proposed. • A two-dimensional auction mechanism in which generators bid their cost and capacity is considered. • The generation uncertainty of solar energy is reflected by the capacity factor of the generators. • An incentive compatible, individually rational, and buyer's payoff maximizing auction rule is characterized. • A computation algorithm to implement the auction is proposed with numerical analysis. [ABSTRACT FROM AUTHOR]

Home energy management systems are essential for the optimization of resources in complex demand scheduling problems that require energy efficiency in homes. This can be achieved through the use of Renewable Electricity Sources (RES), for cleaner and more sustainable energy generation, as well as participation in Demand Response (DR) programs, for lower energy prices. The problem becomes more complex when it is considered a community of households. This paper aims to address individual and community household participation in DR programs and RES sharing while considering constraints imposed on the operation schedule of appliances, through load shifting optimization. For that, a Genetic Algorithm is proposed, implemented, and validated, which focuses on minimizing energy costs. It takes into account dynamic pricing, distributed generation, and household community energy sharing. Using real household workload data, two case studies are presented, one for the cost optimization of an individual household and another for a photovoltaic energy-sharing household community containing twenty houses. Both case studies represent five days of scheduling, where each house can have up to five appliances able to shift. The business as usual costs are 16.74 EUR and 269.99 EUR for the individual and community case studies, respectively. Results show improvements of up to 24.3% (12.67 EUR in the optimized schedule, 4.07 EUR in savings) for the individual case study and 11.8% (238.21 EUR in the optimized schedule, 31.78 EUR in savings) for the household community. In a community, households can expect cost reductions of 1.5%–26.8% when compared to individual scheduling. [ABSTRACT FROM AUTHOR]

The growing need for clean energy and food production are favoring the use of underused spaces, such as rooftops. This study aims to demonstrate the compatibility of the use of rooftops both for the production of photovoltaic energy and for the production of food, despite the fact that both compete for the same resource, sunlight (rooftop agrivoltaic). In the experiment reported in this study, which was carried out in Almería (Spain) during the spring and summer of 2021, three shade treatments were tested for a lettuce crop, produced by photovoltaic modules with different arrangements: concentrated shade (CS), scattered shade (SS) and full sun (FS). This experiment was repeated in two seasons with high radiation levels and temperature. The results show that in these environmental conditions, the cultivation of plants that demand little sunlight, such as lettuce, is compatible with the shading produced by photovoltaic panels. In addition, it is shown that the same percentage of the area covered with shade (22%), but using mini-PV modules arranged in patterns, improves the productivity (fresh weight, dry matter, number of leaves, maximum length and dry matter of roots) of lettuce cultivation, both in spring and summer.

This article has been developed to assess the economic feasibility of a rooftop photovoltaic installation of industrial self-consumption. Numerical models that enable an interested person to obtain the main expected parameters will be generated, with those models being the article’s main contribution to the field. To do this, a calculation methodology will be developed through which the reader, knowing the location of the facility and dimensions of the roof, will be able to calculate the maximum installable power, the main parameters related to production, the cost of the installation, and the LCOE of the plant. The use of actual costs will be facilitated in case they are known. Still, it will remain possible to apply the major equipment costs (modules, inverter, and structure) considered throughout the article. This developed calculation methodology will also allow a quick comparison of the forecasts of production, CAPEX, and LCOE of plants designed with different inclinations and different types of modules. Consequently, it will be especially useful in decision-making before developing the plant’s basic engineering. Moreover, the calculations used for modeling the LCOE will be analyzed in depth. This analysis will allow evaluating how the different technical variables affect the profitability of a photovoltaic installation, such as the selected tilt, the location, the module’s technology, or the available area.

Photovoltaic (PV) energy is a renewable energy resource which is being widely integrated in intelligent power grids, smart grids, and microgrids. To characterize and monitor the behavior of PV modules, current-voltage (I-V) curves are essential. In this regard, Internet of Things (IoT) technologies provide versatile and powerful tools, constituting a modern trend in the design of sensing and data acquisition systems for I-V curve tracing. This paper presents a novel I-V curve tracer based on IoT open-source hardware and software. Namely, a Raspberry Pi microcomputer composes the hardware level, whilst the applied software comprises mariaDB, Python, and Grafana. All the tasks required for curve tracing are automated: load sweep, data acquisition, data storage, communications, and real-time visualization. Modern and legacy communication protocols are handled for seamless data exchange with a programmable logic controller and a programmable load. The development of the system is expounded, and experimental results are reported to prove the suitability and validity of the proposal. In particular, I-V curve tracing of a monocrystalline PV generator under real operating conditions is successfully conducted.

This paper introduces a single-switch, high step-up DC–DC converter for photovoltaic applications such as power optimizers and microinverters. The proposed converter employs two voltage multipliers cells with switched capacitor and magnetic coupling techniques to achieve high voltage gain. This feature, along with a passive clamp circuit, reduces the voltage stress across the switch, allowing for the employment of low RDSon MOSFET. This leads to low conduction loss of the switch. The diodes operate with zero-current switching at their turn-off transition, eliminating the reverse recovery losses. Additionally, the switch turns on with zero-current switching, leading to insignificant switching loss associated with its turn-on transition. The operation principle and steady-state analysis are presented and validated through experimental results obtained from a 140 W prototype of the proposed converter.

This paper presents a novel complete design procedure to convert a maximum power point tracking (MPPT) algorithm into a control system. The MPPT algorithm can be tuned by employing any control system design. In this paper, we adopted Bode diagrams using the criteria of module and phase as the power electronics specialists are habituated with such concepts. The MPPT control transfer functions were derived using the average state equations and small-signal analysis. The control loops were derived for power and voltage control loops. The design procedure was applied to the well-known perturb and observe (P&O) and incremental conductance (IC) algorithms, returning the P&O based on PI and IC based on PI algorithms. Such algorithms were evaluated through simulation and experimental results. Additionally, we showed that the proposed design methodology can optimize energy harvesting, allowing algorithms to have outstanding tracking factors (above 99%) and adaptability characteristics.

In Europe, buildings are responsible for more than one third of the total final energy demands and greenhouse gas emissions. In the last twenty years, the European Union has published a succession of energy performance of building directives to define and ensure the fulfilment of a series of objectives regarding greenhouse gas emissions, energy consumption, energy efficiency and energy generation from renewable sources in buildings. For its part, Spain is adapting its legal framework, transposing these directives with the aim of achieving greater energy efficiency and sustainability for buildings. Under this context, an energy, economic and environmental assessment is performed to analyze the impact of these regulatory changes on a single-family home including a photovoltaic installation for self-consumption with surpluses and/or a solar thermal installation for domestic hot water supply, located in each one of the eight thousand one hundred thirty-one municipalities that make up Spain. The energy behavior of the original house is compared with that obtained after it is updated with these new facilities. The transient system simulation tool is used for the energy study. The results show that the European objectives are far exceeded. The energy savings achieved range from 67% to 126%, carbon dioxide emissions decrease by 42% to 100% and energy bills are reduced in cost by 32% to 81%. The findings of this work can be used by policymakers as guidelines for the development of national strategic plans and financial incentives for the promotion of small-scale residential photovoltaic and solar thermal applications, as well as by designers, supervisors, managers and developers to include them in their projects.

This work aims to identify the most suitable location for photovoltaic power plants on the Spanish island of Gran Canaria. To that end, we propose a methodology which will assess those physical territorial resources involved in the development of photovoltaic solar energy by means of two devices: the available territorial resource map and the available territorial resource index. In order to achieve this objective, multi-criteria analysis through an analytical hierarchy process with geographical information systems was used. The empirical analysis concluded that a large percentage of the island territory enjoys excellent potential for the setting-up of photovoltaic plants. The contribution of this research is particularly important in an island context, since it is in this type of territory where such tools are especially relevant to plan the best use of limited land area and availability.

Being able to detect, to identify and to quantify the severity of defects that appear within photovoltaic modules is essential to constitute a reliable, efficient and safety system, avoiding energy losses, mismatches and safety issues. The main objective of this paper is to perform an in-depth, onsite study of 17,142 monocrystalline modules to detect every single existing defect, classifying them in different groups, studying the variance of the same kind of defect in different modules and the patterns of each group of thermal defects. Results can be useful in a subsequent development of a software to automatically detect if a module has an anomaly and its classification. Focusing on the results obtained, all faults detected have been classified in five different thermographic defects modes: hotspot in a cell, bypass circuit overheated, hotspot in the junction box, hotspot in the connection of the busbar to the junction box and whole module overheated. An analysis of patterns of the different defects is included, studiyng location within the module, size and temperature statistical results, as average temperature, standard deviation, maximum temperature, median and first and third quartile.

This paper presents a two-way optimization of the Perturb & Observe (P&O) maximum power point tracking (MPPT) technique using current correction and fuzzy logic techniques. In fact, photovoltaic (PV) energy has become more and more coveted today. In the future, it will become a necessity. To ensure its optimization, maximum operating point tracking method is considered as a technological key in PV systems. One of the most used MPPT methods is the P&O technique. In this paper, we will focus on optimizing this method based on two techniques. A first attempt has been made to estimate a current correction of the P&O algorithm in case of illumination variation. Then, fuzzy logic optimization attempt had been highlighted to improve power loss. It is shown that both proposed techniques are very effective and allow considerable improvement of accuracy and are less affected by sudden variation of climatic parameters. The proposed approaches are tested via Matlab software and compared the classical P&O algorithm. Through applications, we could conclude that the two optimized proposed methods offer a remarkable improvement concerning power losses.