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This work proposes high step-up DC-DC converter to acquire power from low voltage ambient sources like TEG, solar PV panels etc... The proposed converter provides high DC voltage gain, with reduced component count with high efficiency. Additionally, this topology significantly improves the voltage conversion ratio in comparison with other similar DC-DC converters presented recently. Besides, the design part includes less number of passive components to ensure compactness and low cost. The validation of the converter in continuous conduction mode (CCM) is carried out with detailed design method and performance of the same is verified using simulated using the MATLAB/Simulink.&nbsp

With the accelerating penetration of photovoltaics (PVs) and electric vehicles (EVs), distribution networks face the risks of voltage violations and fluctuations. On the one hand, conventional voltage regulation resources like OLTC transformers and capacitor banks feature slow response and limited lifetime duration, making them incapable of quickly responding to the temporary voltage issues created by PVs and EVs. On the other hand, EVs and PVs interact with the power grid via fully controllable power electronic converters capable of real-time adjusting their operating settings, making them ideal voltage support resources. To exploit the voltage support capability of PVs and EVs, this paper proposes a two-stage control scheme for the voltage regulation of distribution networks, consisting of the day-ahead and intraday control stages. The day-ahead control mitigates potential voltage violations via day-ahead scheduling of the operation settings for OLTC transformers and capacitor banks. The intraday control further alleviates voltage deviations and voltage fluctuations based on the reactive power support of PV systems and the rational EV charging/discharging scheduling. A rolling optimization-based control technique is proposed in the intraday control stage to achieve real-time control of EVs and PVs with the stochastic nature of EV charging behaviors inherently considered. The proposed two-stage voltage regulation scheme is validated via case studies performed on the IEEE 123-node test feeder integrated with PVs and EVs.

Energy demand forecasted for the next several years has been bench marked due to the massive need for electrical energy. Solar power plants have earned a great marketplace position in recent years, but also face challenges in terms of power dissipation due to the frequent occurrence of shade. As a result, the per unit solar electricity price increases drastically. There is an immense need to ensure the maximum dependable power conversion efficiency of Photovoltaic (PV) systems by mitigating power output losses during partial shading conditions. The reconfiguration of PV arrays is a useful, effective, and promising approach in this context. Though several reconfiguration techniques have been developed in recent years, their applicability to real-time power plants is debatable due to the requirement of many physical relocations, long interconnecting ties, and complexity. This research work proposes a novel row index mathematical procedure followed by a technique in which the reconfiguration matrix indexes are filled with a unique number so that no row number repeats in the same row and column. Additionally, the proposed approach uses small number of switches that reduce the cost as well as the computational complexity. To strengthen the analysis, very recent techniques such as Sudoku, Total Cross Tied (TCT), Chess-Knight, and Particle Swarm Optimization (PSO) based reconfiguration are compared against five different shading patterns. It has been observed that approximately 68% power loss is mitigated in TCT configuration. It is worth noting that it results in higher PV output power than the existing latest reconfiguration techniques such as PSO, Chess-Knight, Sudoku, and others.

The operating performance of a PV module/array is extremely reliant on the weather (temperature/irradiation) and non-linear. Thus, to ensure that the PV array produces the maximum possible power at any time and regardless of the external conditions, maximum power point tracking (MPPT) techniques are required. The solution suggested in this paper involves taking into account two cascaded controllers as follows; the incremental conductance (INC) controller, which is intended to provide a reference proportional to the PV array's optimal power PMPP, and the sliding mode control (SMC), which is in charge of controlling the GPV voltage. The strategy of the SMC is to design a sliding surface that defines the operating point. The SMC combined with the INC aims to achieve fast MPPT action on PV systems using cascade control. The proposed controller is robust to changing weather conditions. In order to evaluate what is done, the results are compared with the INC+PI controller. When an abrupt change occurs, the SMC has a low transient and arrives to equilibrium sooner than the INC+PI controller. the results are presented by the PSIM software, and demonstrate the SMC controller's performance while confirming that the new approach has increased both production and energy efficiency.

This paper shows the technical–economic assessment of two power systems based on renewable electricity to cover the energy consumption requirements of a drinking water treatment plant in the town of Pile, Ecuador, with a planning horizon of 15 years. A stand-alone and a grid-connected solar PV system were proposed to power this plant, which was designed considering the maximum daily potable water supply condition. This plant operated under two scenarios: (1) 12 h during daylight hours and (2) 24 h. Both schedules were proposed to assess the impact of PV power systems on plant operation. We modeled and optimized a total of four scenarios, where each scenario consisted of one of the proposed PV power systems and the plant with one of its operating schedules. Homer Pro software was used to size and find an optimal solution in each scenario, considering the net present cost (NPC) as the main criterion for optimization. The results showed that the change in the plant operation schedule significantly influenced the parameters of each scenario, such as component sizing, electricity production, initial capital, NPC, and electricity purchase/sale capacity from the plant as a grid power service user to the electric utility company.

The classic Photovoltaic system maximum power point tracking technique cannot concurrently take into account the dynamic response speed and steady-state accuracy when the light intensity changes. To address this issue, a new composite variable step MPPT control algorithm is developed in this study. Based on the three-stage variable step incremental conductance method, the algorithm adds the Kalman filtering algorithm to pre-process the photovoltaic cells output signal, and uses a new calculation approach to adjust the variable step coefficient. As a result, the perturbation step can be automatically modified according to changes in the external environment, which resolves the issues with poor dynamic reaction speed when the classic variable step algorithm started and the light changed. Compared to conventional MPPT control algorithms, the improved MPPT strategy can be easily realized using a hardware control system since it has a simplified control logic and requires less data to be calculated. In this study, the hardware circuit of the enhanced MPPT control algorithm is built using the ESP32 as the primary control chip. This chip can be utilized in conjunction with the Internet of Things to enable remote monitoring of the solar power system’s operational state. According to test results, the algorithm can instantly detect the maximum power point in all lighting circumstances with tracking accuracy of up to 99.6% and a reduction in dynamic response time of the system to 0.12 s.

Die Dekarbonisierung der elektrischen Energieerzeugung ist ein wesentlicher Bestandteil zur Eindämmung des Klimawandels. Energiegemeinschaften bieten Privatpersonen und Unternehmen die Möglichkeit, sich aktiv daran zu beteiligen. Innerhalb einer Energiegemeinschaft kann die lokal erzeugte erneuerbare Energie verteilt, gehandelt, gespeichert und verbraucht werden. Für eine erfolgreiche Planung und den langfristigen Betrieb von Energiegemeinschaften ist ein fundiertes Verständnis über die Abläufe und Einflussfaktoren unumgänglich.Diese Diplomarbeit beschäftigt sich daher mit einer tiefgehenden Analyse des Einflusses von heterogenen Parametern auf die Kennzahlen von Energiegemeinschaften. Dazu wurde ein, auf der Plattform BIFROST basierendes, Simulationsframework entwickelt, mithilfe dessen es möglich ist unterschiedliche Szenarien zu definieren, zu simulieren und auszuwerten. Es wurden relevante technische, ökologische und soziale Parameter sowie Umwelteinflüsse identifiziert und deren Auswirkung auf technische, ökonomische und ökologische Kennzahlen simulativ ermittelt.Die im Rahmen dieser Diplomarbeit definierten Szenarien zeigen einen überwiegend technischen, ökologischen und sozialen Vorteil, während finanzielle Profite stark von der aktuellen Marktsituation abhängen. Die Topologie einer Energiegemeinschaft trägt dabei wesentlich zum Erfolg dieser bei. Ein Fokus auf den Ausbau individueller Autarkie zeigt Nachteile in Hinblick auf die Wirksamkeit von Energiegemeinschaften. Bei der Gestaltung moderner Niederspannungsnetze gilt es daher abzuwägen, ob gemeinschaftliche Maßnahmen im Vergleich zu individuellen Maßnahmen zu bevorzugen sind., Decarbonizing electrical power generation is an essential part of mitigating climate change. Energy communities offer private individuals and companies the opportunity to actively participate in this. Within an energy community, locally generated renewable energy can be distributed, traded, stored and consumed. For successful planning and long-term operation of energy communities, a sound understanding of the processes and influencing factors is indispensable.This thesis therefore deals with an in-depth analysis of the influence of heterogeneous parameters on the key performance indicators of energy communities. For this purpose, a simulation framework based on the BIFROST platform was developed, with the help of which it is possible to define, simulate and evaluate different scenarios. Relevant technical, ecological and social parameters as well as environmental influences were identified and their impact on technical, economic and ecological key performance indicators was simulated.The scenarios defined in this thesis show a predominantly technical, ecological and social advantage, while financial profits depend strongly on the current market situation. The topology of an energy community contributes significantly to its success. A focus on the expansion of individual self-sufficiency shows disadvantages with regard to the effectiveness of energy communities. When designing modern low-voltage grids, it is therefore important to weigh up whether community measures are preferable to individual measures.

A combined PSO-ANN control is proposed in this work to achieve the best voltage regulation in a distribution network, based on quick response and minimum average voltage deviation. The Jordanian Sabha Distribution Network (JSDN) with PV Farms is used as a real case study to examine a voltage variation issue. Two STATCOMs are used to solve the voltage fluctuation problem on the network’s three buses. The required reactive powers of STATCOMs for voltage regulation during load variation are calculated in offline mode using a particle swarm optimization (PSO) algorithm. Despite its high performance in solving voltage issue in the JSDN network, the PSO controller is unable to react promptly to dynamic changes in the network. An artificial neural network (ANN) is therefore suggested as an online mode controller for quick and efficient voltage regulation. The offline dataset is used to train the ANN for online voltage regulation utilizing the MATLAB-Tool Box. At an average voltage deviation (AVD) of 1.168%; (whereas an acceptable one is 6%), the results revealed the proposed ANN controller’s competence for voltage regulation in the distribution network. Moreover, to find the best position based on an efficient voltage regulation, many sites for STATCOMs are taken into consideration.

Οι υπηρεσίες για την ικανοποίηση των ανθρώπινων αναγκών, της οικονομικής ανάπτυξης, της ευημερίας και της υγείας των πολιτών απαιτούν υψηλά ποσά ενέργειας και οι ανάγκες αυξάνονται με ταχύτατους ρυθμούς. Είναι συντριπτικό να γνωρίζουμε ότι στις μέρες μας 1,4 δισεκατομμύρια άνθρωποι δεν έχουν πρόσβαση σε ηλεκτρική ενέργεια. Επιπλέον, η αύξηση των εκπομπών του διοξειδίου του άνθρακα καθώς και η σημαντική αλλαγή του κλίματος είναι μια από τις μεγαλύτερες προκλήσεις του εικοστού πρώτου αιώνα. Οι σοβαρές αυτές επιπτώσεις μπορεί ακόμη να αποφευχθούν, εάν καταβληθούν προσπάθειες για τον μετασχηματισμό των σημερινών ενεργειακών συστημάτων. Οι ανανεώσιμες πηγές ενέργειας αποτελούν το καθοριστικό μέσο για την μείωση των εκπομπών αερίων που συμβάλουν στο φαινόμενο του θερμοκηπίου, καθώς και μια λύση για την απεξάρτηση τόσο από το ρωσικό φυσικό αέριο και τους εξαντλήσιμους συμβατικούς πόρους. Σκοπός της παρούσας διπλωματικής είναι να γίνει εκτενής αναφορά στην εξέλιξη των Ανανεώσιμων Πηγών Ενέργειας καθώς και να αναφερθούν τα πιο πρόσφατα στοιχεία που αφορούν τη παραγωγή και ζήτησή τους στο διασυνδεδεμένο δίκτυο ηλεκτρισμού της Ελλάδας (ΔΕΔΔΗΕ) με σκοπό την πρόβλεψη μετρήσεων για την ενσωμάτωση τους σε αυτό και την επίτευξη των στόχων που έχουν τεθεί από την ΕΕ για να διασφαλιστεί η αγορά ενέργειας της Ευρώπης και να αυξηθεί η ανθεκτικότητα του ενεργειακού της συστήματος . Για την μελέτη περίπτωσης, των Φωτοβολταϊκών Συστημάτων, τα οποία αποτελούν από τις πλέον σύγχρονες, πράσινες μορφές ενέργειας, με περιορισμένο περιβαλλοντικό αντίκτυπο, γίνεται μία διερεύνηση της δυνητικής δυναμικότητάς τους και μία προσπάθεια πρόβλεψης της εξέλιξής τους. Τέλος, θα πρέπει να σημειωθεί ότι η παρούσα εργασία, με την χρήση χρονοσειρών, προέβλεψε ότι η μέση μηνιαία αύξηση για την παραγόμενη ενέργεια από διασυνδεδεμένα φωτοβολταϊκά συστήματα είναι της τάξεως του 58,2% για το χρονικό διάστημα Ιούνιος 2022 μέχρι Μάιος του 2023., The demand for energy and the relative services required for humankind’s social and Economic growth, prosperity, and health are increasing at a very rapid pace. Moreover, the increase in carbon dioxide emissions as well as the significant climate Change is one of the greatest challenges of the 21st century. These severe consequences can still be avoided provided those necessary efforts are put into the transformation of today’s energy systems Renewable energy sources are the decisive means for the reduction of gas emissions that contribute to the greenhouse effect, as well as a solution to the reduction of reserves of traditional energy raw materials including the Russian gas. The purpose of this thesis is to make an extensive reference to the evolution of Renewable Energy Sources as well as to report the most recent data regarding their production and demand in the interconnected electrical grid of Greece with the aim of predicting measurements for their input into it and achieving of the guidelines—goals that have been set. Finally, it should be noted that this work, using time series, predicted that the average monthly increase for the energy produced by interconnected photovoltaic systems is of the order of 58.2% for the period of June 2022 to May 2023.

This paper presents a classical estimation problem for calculating the energy generated by photovoltaic solar energy systems, on a daily, annual, regional and national basis. Our methodology relies on two data sources: PVOutput , an online portal with solar energy production measurements, and modelled irradiance data available for large parts of Africa and Europe, from the Royal Netherlands Meteorological Institute. Combining these, we obtain probability functions of observing energy production, given the irradiation. These are applied to a PV systems database, using Monte Carlo sampling, allowing daily and annual solar energy production to be calculated. These are, in turn, used to calculate solar energy production per municipality. As a case study, we apply this methodology to one country in particular, namely the Netherlands. By examining the variation in our estimates as a result of taking different subsets of PVOutput systems with certain specifications such as azimuth, tilt and inverter loading ratio, we obtain specific annual energy yields in the range of 877 - 946 kWh / kW p and 838 - 899 kWh / kW p for 2016 and 2017 respectively. The current method used at Statistics Netherlands assumes this to be 875 kWh / kW p , irrespective of irradiation, meaning the yields were underestimated in 2016 and overestimated in 2017. In the case of the Netherlands, this research demonstrates that an irradiation based measure of solar energy generation is necessary. More generally, this research shows that different types of open data sources may be combined to develop models that calculate the energy production of PV system populations.

Existing international standards address harmonic orders up to the 40th or 50th (at 2 or 2.5 kHz for a 50 Hz network). Modern converters effectively suppress components within that range, but they also tend to shift emission to higher frequencies. Recently reported cases of disturbances in modern distribution grids specifically attributed to supraharmonics (harmonic components within the 2–150​ kHz range) have drawn interest in associated research. Grid-connected PV systems utilizing PWM-controlled inverters inject supraharmonic currents into the distribution network at their point of connection. Comprehension of their electrical behavior, including their impact on grid supraharmonic levels, can be achieved through extensive simulation studies. In this paper, a three-phase PV system is simulated using models successfully already developed for single phase PV inverters that increase simulation speed by avoiding time-consuming procedures. Current and voltage waveforms as well as supraharmonic levels are presented. The simulation results are compared with real measurements obtained from an operating small rooftop PV system and evaluated. Additional simulations are carried out using different values for system parameters and their respective impact on supraharmonic levels is assessed. Moreover, this paper presents real supraharmonics’ measurements from a grid-connected 8kWp PV system.

Cyberattacks can be strategically counterfeited to replicate grid faults, thereby manipulating the protection system and leading to accidental disconnection of grid-tied converters. To prevent such setbacks, we propose a physics-informed spline learning approach-based anomaly diagnosis mechanism to distinguish between both events using minimal data for the first time in the realm of power electronics. This methodology not only provides compelling accuracy with limited data, but also reduces the training and computational resources significantly. We validate its effectiveness and accuracy under experimental conditions to conclude how data availability problem can be handled.

Nowadays, photovoltaic (PV) systems are responsible for over 994 TWH of the worldwide energy supply, which highlights their relevance and also explains why so much research has arisen to enhance their implementation; among this research, different optimization techniques have been widely studied to maximize the energy harvested under different environmental conditions (maximum power point tracking) and to optimize the efficiency of the required power electronics for the implementation of MPPT algorithms. On the one hand, an earthquake optimization algorithm (EA) was introduced as a multi-objective optimization tool for DC–DC converter design, mostly to overcome component shortages by optimal replacement, but it had never been tested (until now) for PV applications. On the other hand, the original EA was also taken as inspiration for a promising EA-based MPPT, which presumably enabled a solution with simple parametric calibration and improved dynamic behavior; yet prior to this research, the EA-MPPT had never been experimentally validated. Hence, this work fills the gap and provides the first implementation of the EA-based MPPT, validating its performance and suitability under real physical conditions, where the experimental testbed was optimized through the EA design methodology for DC–DC converters and implemented for the first time for PV applications. The results present energy waste reduction between 12 and 36% compared to MPPTs based on perturb and observe and particle swarm optimization; meanwhile, the designed converter achieved 7.3% current ripple, which is between 2.7 and 12.7% less than some industrial converters, and it had almost 90% efficiency at nominal operation. Finally, the EA-MPPT proved simple enough to be implemented even through an 8-bit MCU (ATmega328P from Arduino UNO).

Maximum power point tracking (MPPT) is a pivotal objective for photovoltaic (PV) systems. To test various MPPT techniques, a reliable and effective PV emulator is required. Therefore, this article proposes a low-cost PV emulator for partial shading conditions, in which a cascaded structure of a DC power source with a resistor is constructed to generate the multiple peaks of the power-voltage (P-V) curve. The proposed structure is simple and modular. Consequently, it can be extended to obtain several peaks in the P-V characteristics to emulate more complex partial shading conditions. The partial shading occurrence over the PV source (PV array) causes a significant power loss production from the PV system. To increase the PV system’s efficiency, optimization techniques are employed to harness the global power. Accordingly, the particle swarm optimization (PSO) technique is used to track the global peak. Furthermore, the conventional perturb and observe (P&O) method is applied for comparison and investigation. The proposed PV emulation system is validated under different operating conditions using simulation and experimental hardware-in-the-loop (HIL) results.

Bu tez çalışması Batman Üniversitesi Bilimsel Araştırmalar Projeleri (BAP) tarafından BTÜBAP-2021-YL-06 nolu proje ile desteklenmiştir., Bu tez çalışması; Batman ili iklim şartlarında birbirinden farklı faz değiştiren malzemeler kullanılarak 110 W Monokristal güneş paneli üzerindeki ısı ve verim hesaplamalarının deneysel karşılaştırılması yapılmıştır. Batman üniversitesi Batı Raman Kampüsünde kurulan deney düzeneği farklı gün ve saat aralıklarıyla sıcaklık miktarlarının ve FDM’lerin (faz değiştiren malzemelerin) güneş panelinden elde edilen enerji miktarına etki eden parametreler deneysel olarak incelenmiştir. Güneş radyasyonu, panel sıcaklıkları ve ortam sıcaklığı ölçülmüştür. Elde edilen verilerin analizi sonucunda panel üzerindeki verim hareketliliği incelenmiştir. 3 panelin arka yüzeyine montajlanan cam muhafaza içerisine eklenmiş üç farklı FDM malzemesi ile FV sistem soğutulmuştur. Her üç fotovoltaik panelin, arka yüzeyine ayrı ayrı FDM çeşitleri eklenmiştir. Parafin, Yağ Asidi ve Tuz Hidrat FDM’leri eklenerek soğutma yapılmıştır. Bir adet fotovoltaik paneli de ortam koşullarında bulunan bir panelin durumunu gözlemlemek ve referans olarak almak için olarak boş bırakılmıştır. Panel yüzeyine yerleştirilen üç farklı yüzey sıcaklıkları, ortam sıcaklığı ve giriş çıkış sıcaklıkları alınmış ve zamana bağlı olarak oluşan güç, akım ve volt değerleri kaydedilmiştir. Deney düzeneğinde kullanılan tüm panellerin maksimum güç oranları hesaplanmıştır. Deney analizleri sonucunda; Parafin kullanılan panelde %11,34, Tuz Hidrat kullanılan panelde %17,22, Yağ Asidi kullanılan panelde ise %30 güç üretimi fazlalığı bulunmuştur. Her üç panel de aynı özelliklere sahip olmasına rağmen oluşan farklılıklar deney sonucunda etkisini göstermiştir. Hesaplamalar sonucunda elektriksel verimin her panelde farklılık gösterdiği ölçülmüştür. FDM’ler eklenmeden önce elde edilen verilere göre; Parafin kullanılan panelin elektriksel verimi %9,2 iken parafin eklendikten sonra %9,7 olarak hesaplanmıştır. Tuz Hidrat kullanılan panelin elektriksel verimi %8,4 iken Tuz Hidrat eklendikten sonra elektriksel verimi %9,4 ve Yağ Asidi kullanılan panelin elektriksel verimi %6,6 iken Yağ Asidi eklendikten sonra elektriksel verimi %8,1 olarak bulunmuştur. Yapılan deneyde soğutma yapılan Parafin kaplı güneş panelinde 16℃, Tuz Hidrat kaplı panelde 11℃, Yağ Asidi ile kaplanmış panelde ise 13℃ sıcaklık farkı ölçülmüştür. Deneylerin sonucunda güneş panellerinde meydana gelen ortalama sıcaklık farkı en yüksek Yağ Asidi FDM’si ile 4. güneş panelinde 13℃ miktarda olmuştur. Farklı FDM’ler ile kaplı olan üç güneş panelinin de anlık ve günlük ortalama verim değerlerini arttırdığı gözlemlenmiştir. Ortalama en yüksek verim değerlerine bakıldığında; %30 güç artışı ile Yağ Asidi FDM olduğu görülmüştür., This thesis work; An experimental comparison of the heat and efficiency calculations on the 110 W Monocrystalline solar panel was made by using different phase-changing materials in the climatic conditions of Batman province. The experimental setup established in Batman University West Raman Campus, the temperature amounts and the parameters affecting the energy amount obtained from the solar panel of FDMs (phase-change materials) were investigated experimentally at different day and hour intervals. Solar radiation, panel temperatures and ambient temperature were measured. The results of the analysis of the obtained findings were examined in terms of yield mobility on the panel. The PV system is cooled with three different PCM materials added to the glass enclosure mounted on the back surface of the 3 panels. Separate PCM variants have been added to the back surface of each of the three photovoltaic panels. Paraffin, Fatty Acid and Salt Hydrate PCMs were added and cooling was done. For a photovoltaic panel, it is left blank to observe the status of a panel in ambient conditions and to take a reference. Three different surface temperatures, ambient temperature and input and output temperatures placed on the panel surface were taken and the power, current and volt values that occurred depending on time were recorded. The maximum power ratios of all panels used in the experimental setup were calculated. As a result of the experimental analysis; A power production excess of 11.34% was found in the panel using paraffin, 17.22% in the panel using Salt Hydrate, and 30% in the panel using Fatty Acid. Although all three panels have the same characteristics, the differences have shown their effect as a result of the experiment. As a result of the calculations, it was measured that the electrical efficiency differs in each panel. According to the data obtained before adding FDMs; While the electrical efficiency of the panel using paraffin was 9.2%, it was calculated as 9.7% after adding paraffin. While the electrical efficiency of the panel using Salt Hydrate was 8.4%, the electrical efficiency of the panel using Salt Hydrate was 9.4% and the electrical efficiency of the panel using Fatty Acid was 6.6%, while the electrical efficiency was 8.1% after adding Fatty Acid. In the experiment, the temperature difference was measured at 16°C on the Paraffin coated solar panel, 11°C on the Salt Hydrate coated panel, and 13°C on the Fatty Acid coated panel. As a result of the experiments, the average temperature difference in the solar panels was 13℃ in the 4th solar panel with the highest Fatty Acid PCM. It has been observed that the three solar panels covered with different PCMs increase the instantaneous and daily average efficiency values. Considering the average highest yield values; Fatty Acid PCM was observed with 30% power increase.

The present study aims at analyzing and assessing the performance of grid-connected photovoltaic (PV) systems, where the considered arrangement is the two-stage PV system. Normally, the maximum power point tracking (MPPT) process is utilized in the first stage of this topology (DC-DC). Furthermore, the active and reactive power control procedure is accomplished in the second stage (DC-AC). Different control strategies have been discussed in the literature for grid integration of the PV systems. However, we present the main techniques, which are considered the commonly utilized and effective methods to control such system. In this regard, and for MPPT, popularly the perturb and observe (P&O) and incremental conductance (INC) are employed to extract the maximum power from the PV source. Moreover, and to improve the performance of the aforementioned methods, an adaptive step can be utilized to enhance the steady-state response. For the inversion stage, the well-known and benchmarking technique voltage-oriented control, the dead-beat method, and the model predictive control algorithms will be discussed and evaluated using experimental tests. The robustness against parameters variation is considered and an extended Kalman filter (EKF) is used to estimate the system’s parameters. Future scope and directions for the research in this area are also addressed.

Designing with photovoltaics (PV) is the core focus of this paper which presents the results of a design study on conceptual PV applications for electric mobility systems. This is a relevant direction for new product development because PV technology can contribute to improved features of electric mobility systems not just in terms of CO2 emissions reduction but also regarding product aesthetics and user experiences. Design studies are multidisciplinary by nature; therefore, in this case technical, user, regulatory and aesthetic aspects are covered. Eleven conceptual designs were developed in 2019 by means of a design project executed at the University of Twente, encompassing solutions for PV-powered charging of electric vehicles, vehicle-integrated PV products and other applications. The concepts focus on various modes of transport beyond passenger cars such as public transportation, electric bicycles and utility vehicles, in some cases applying alternative charging technologies such as battery swapping and induction charging in their design. In this paper four of these conceptual designs are presented as case studies, showing their multidisciplinary focus as well as parts of the design process behind their development. An evaluation of these conceptual designs revealed several design challenges that need to be addressed in their development, including the limited space available for integrating PV cells, the technical limitations posed by some of the proposed charging methods and the effective visual communication of the concept's intended function.

This paper briefly outlines part of the research work being carried out on the application of the photovoltaic systems to cover universities’ electrical energy needs, with due consideration to the technical, architectural, economic, social. and legal aspects and impacts of this application. The paper considers optimizing the PV system selection objectives and methodology with a case study application. at a university campus in Ankara, Turkey. The main objective here is to develop a practical simple method of selecting an optimum PV system that gives the maximum energy yield possible in a certain period of one year, with the minimum specific energy cost per kWh, where a multiple-variable multi-criteria decision-making making method is applied, to help designers and system engineers in selecting the optimum system. The developed method is demonstrated in the example of the typical case, where the recommended PV system was turned out to be at an Azmuth angle of 0 degrees, the PV technology was monocrystelline Silicon, the annual electrical energy yield per 100 m2 of PV modules surface area 22.4 MWH/Year, the specific electrical energy cost was 0.15 Euos/Kwh, as a first merit option, making a difference of around 13% of saving compared with the 10th last option. The work concludes that a viable PV application is feasible, encouraging its application in various campuses provided that comprehensive planning and careful considerations are given to the related aspects.

Renewable energy sources are can play an important role both in fulfilling the increasing demands for energy and in reduction of the emissions of the greenhouse gases and other air pollutants. For these reasons their energy yield increases dynamically. Renewable energy sources are available in different ratios in different regions of the continents. Every regions has its own features what result in different utilisation methods. This paper presents a solar energy potential estimating model what can be used at any locations over the Earth. Examinations were carried out on a remote controlled system composed of 64 solar panels in the Renewable Energy Park Research Center in Debrecen, Hungary. Results revealed that the agreement between the model and the values in our database is over 90% thus using the model the production of the solar panel systems could be predicted taking into account specific local conditions as well.

The community all over the World has to tackle the problem of depletion of fossil fuels, overusing the natural resources, and growing emission of greenhouse gases into the atmosphere. It is related to the growing demand for electricity due to global development in every field. The solution to this problem can be production clean, solar energy with the use of photovoltaic modules. However, the installation of PV system in urban areas is very often impossible because of high-density citie’s architecture. The objective of this study was to analyze building applied photovoltaic system configurations for the flat rooftop of the detached house in Warsaw, Poland. Four configurations were analyzed taking into consideration the area of the rooftop, different tilt angles of PV modules, and shading areas. The system configuration as well as monthly energy output were carried out by the use of DDS-Cad software. The ecological aspect of the photovoltaic installation was also analyzed. A significant reduction of greenhouse gases was observed based on conducted calculations.

Photovoltaic (PV) systems are the most promising technology for residential installation as an alternative source of energy. To interface the primary source of PV to the electrical grid, an LCL-filtered inverter is being broadly adopted due to its low volume compared to the L-filtered one and the superior ability to filter high-frequency harmonics. In this context, this paper proposes highly accurate digital current controllers for single-phase LCL-filtered grid-connected inverters. The proposed controllers are: Integral-single-lead, integral double-lead, integral double-lead taking into account the effect of pulse width modulation (PWM) delay and the proportional-resonant (PR). These controllers are different from the traditional Proportional-Integral (PI), Proportional-Derivative (PD), and Proportional-Integral-Derivative (PID). One of the novelties of this paper is the detailed, step-by-step procedure for tuning each parameter of the proposed digital controllers considering the dynamic behavior of the LCL filter. The proposed PR has a different and more straightforward tuning methodology than those procedures commonly found in the literature. Therefore, this paper is an attractive tool for a fast, accurate, and reliable way to tune digital current controllers for a single-phase LCL-filtered grid-connected inverter. The controllers were verified in the digital signal controller (DSC) TMS320F28335 while the power structure runs in a hardware-in-loop (HIL device). Results show the efficacy of the proposed controllers.

Electric vehicles (EVs) are becoming an increasingly attractive option to effectively and economically efficiently reduce global fossil fuel consumption as well as CO2 emissions associated with road transportation. In general, the grid provides the electricity required to charge an EV's battery. However, it could be worthwhile to consider EV charging by specific solar photovoltaic (PV) systems to further facilitate the use of renewable energy and to minimize CO2 emissions. Additional benefits could, for instance, be less overloaded local grids and additional grid flexibility. Because little information and experiences exist with so-called solar PV-powered EVs, this paper explores how well PV systems—with the possible combination of battery energy storage systems (BESSs)—might contribute to charging of EVs in four different countries, namely, The Netherlands, Norway, Brazil, and Australia. To this end, a model has been developed that calculates the interactions between PV-BESS systems, EVs, and the grid in each country to determine the electricity balance, financial consequences, and avoided CO2 emissions of PV-powered EVs, compared with EVs that are solely charged by the grid, as well as conventional passenger cars with an internal combustion engine (ICE-V). It is logically found that in countries with a high irradiation, the whole year through, such as Brazil and Australia, solar PV-powered EVs can be operated more effectively than in countries with a high variability of irradiation over the year such as The Netherlands and Norway. If the charging system's PV share is increased from 0% to 50%, the number of required grid charging events per year can be reduced from 104 to 34 in The Netherlands and from 123 to 55 in Norway. PV charging can also reduce CO2 emissions of EVs by 18% to 93% as compared with ICE-Vs depending on the location. From a financial perspective, PV-powered EVs are not yet financially feasible in all countries; however, in some nations, 100% PV charging is already a viable option. In general, it can be concluded that in contrast to driving an ICE-V, the further PV-powered EVs are driven, the more affordable they become—they might even generate financial revenues—and hence, the higher their positive environmental impact will be. On the basis of this study, it can therefore be concluded that solar PV-powered EVs are a technically feasible and increasingly financially attractive option for transport sector emission reductions in most countries when compared with regular grid charging of EVs and certainly as compared with ICE-Vs.

The Solar photovoltaic (PV) energy has many advantages which makes it one of the great sources for power generation. Photovoltaic systems are linked to the electrical grid with the help of a DC-AC converter and a DC-AC inverter. The project's major goal is to improve the grid's interoperability with PV installations. To get the desired performance, the converter as well as inverter characteristics are adjusted. The inverter is controlled by an ARPI (adaptive reference PI) controller, which improves the performance of the system by allowing for low voltage ride through (LVRT). It also smooths out the oscillations in PV-generated electricity that occur because of the due to environmental changes. The converter is utilized to provide MPPT while the PV system is under varied environmental conditions (MPPT). To assess the efficiency of the suggested method, a simulation of system performance employing the suggested ARPI is provided.

Operators of photovoltaic (PV) systems, especially the small ones, monitor only the produced energy output, since they are not equipped with a meteorological station, or there is none in the neighbourhood. When evaluating a large number of PV systems across a region or country, access to the data due to privacy restrictions is usually very limited. To resolve both aspects, we report on a methodology to evaluate the performance of photovoltaic systems where only produced energy data and rated power of the PV system are available and all other data, including orientation and inclination angles, and the exact location are missing. We developed a novel algorithm for automatic detection of orientation/inclination angles and used the recently developed Typical Daily Profiles (TDP) methodology for a fast and accurate evaluation of PV systems. TDPs are representative hourly profiles of the observed parameter (e.g., power, irradiance and temperature) on a monthly basis. For the PV system degradation rate extraction, year-to-year TDPs are used. The case study of 957 PV systems in Slovenia in the period 2015–2019 reveals an average PV system performance ratio exceeding 85% and an average PV system rated power degradation rate of −0.7% per year.

Clean energy is extremely important not only because of economic purposes but also for health considerations. The use of photovoltaic (PV) systems is growing, with the increased needs for electricity. This requires more attention to research of PV systems. In this study, a method to predict the expected lifetime based on the reliability of system performance is proposed. Geographical data were collected near two different locations: Cairo, Egypt and Riyadh, Saudi Arabia. The PV system was simulated with inputs from collected data to obtain the device factors and system responses. To study the significance of inputs and device parameters on the system responses, the Taguchi OA method was used. The probability density function (pdf) of the time of acceptable performance was estimated from the simulation data. A reliability analysis method was applied to the obtained pdf to estimate the reliability function, lifetime or mean life, reliable life, and rate of failure of the used PV system as assessment factors. The results showed that the system efficiency is highly dependent on the ambient temperature, while the performance ratio depends on many variables. The reliability analysis revealed that the field orientation of 30° tilt and 20° azimuth and of 30° tilt and 30° azimuth are best for near Cairo and near Riyadh, respectively. These orientations lead to the longest mean life of 772.25 and 688.36 months for Cairo and Riyadh, respectively. It also resulted in the lowest failure rates of 0.001295 and 0.001228 per month for both regions.

Measurement and modeling of broadband and spectral terrestrial solar radiation is important for the evaluation and deployment of solar renewable energy systems. This paper focuses on optimizing the performance of 200W solar module taking into consideration the local climatic conditions of Bauchi locality. The uncertainty in life cycle savings for solar thermal and photovoltaic (PV) systems as linearly correlated with uncertainty in solar resource data. These uncertainties paved way for the need to conduct a critical assessment of the resource. Assessment of the solar resource for these technologies rely upon measured data, where available. In this paper, we present the development of mathematical model of photovoltaic solar cells based on their detailed single diode equivalent circuit representation. Pertinent simulation models for PV solar module both for an ideal weather situation and for taking into consideration the effects of microclimatic conditions that prevail in Bauchi as evaluated and compared with benchmarks available. The complete model of the PV system was implemented using MATLAB/Simulink platform. The standard characteristic curves for the 200W solar panel are as presented. The simulation of the ideal PV system made use of standard test conditions (STC) to facilitate comparison with the existing benchmark results in the literature. The analysis of the characteristics performance curves returned an average VOC = 42.9v and ISC = 4.21A. The simulation results further revealed that the power delivered by the 200W monocrystalline solar module of 144.3W @620W/m2, 35ºC as recorded for Bauchi under all climatic conditions as evaluated. The benchmark values obtained in the laboratory are VOC = 45.5V, ISC = 5.92A and 200-W under the Standard test condition (STC) conditions of cell temperature 25ºC, solar irradiance of 1000W/m2 and air mass (AM) of 1.5. The average conversion efficiency and fill factor as evaluated are 0.77 and 16% respectively. This result agrees with the benchmark of module efficiency of >15.66% recorded at STC. The results conclusively reveal that the microclimate of a locality essentially affects the performances of solar PV systems deployed to each location on the globe. Therefore, utilization of these parameters is essential for consideration in the design of solar systems in all localities.

In this paper, a Reinforcement Learning (RL)-based approach to optimally dispatch PV inverters in unbalanced distribution systems is presented. The proposed approach exploits a decentralized architecture in which PV inverters are operated by agents that perform all computational processes locally; while communicating with a central agent to guarantee voltage magnitude regulation within the distribution system. The dispatch problem of PV inverters is modeled as a Markov Decision Process (MDP), enabling the use of RL algorithms. A rolling horizon strategy is used to avoid the computational burden usually associated with continuous state and action spaces, coupled with a computationally efficient learning algorithm to model the action-value function for each PV inverter. The effectiveness of the proposed decentralized RL approach is compared with the optimal solution provided by a centralized nonlinear programming (NLP) formulation. Results showed that within several executions, the proposed approach converges either to the optimal solution or to solutions with a PV curtailment excess of less than 2.5% while still enforcing voltage magnitude regulation.

This data article refers to the paper ''Optimizing photovoltaic electric generation and roof insulation in existing residential buildings” [1].The reported data deal with roof retrofit in different types of existing residential buildings (single-family, multi-family and apartment complex) located in Milan (Northern Italy). The study focus on the optimization of envelope insulation and photovoltaic (PV) energy production associated with different building geometries, initial insulation level, roof constructions, and materials.The data linked within this article relate to the modelled building energy consumption, renewable production, potential energy savings, and costs. Data refer to two main scenarios: refurbishment (roof in need of replacement and insulation) and re-roofing (energy intervention for roof improvement). Data allow to visualize energy consumption before and after the optimization, selected insulation level and material, costs and PV renewable production (with and without energy storage). The reduction of energy consumption can be visualized for each building type and scenario. Further data is available on CO2 emissions, envelope, materials, and systems.

It is known that, the available power from a photovoltaic system is unpredicted and differs with climatic changes, so it has an intermittent nature, in other words it is unable to supply the load continuously and steadily. Because of that, storage methods of its energy must be studied to use it again in a way that could be predicted. Hydrogen production is one of these methods by connecting the PV system to water electrolysers, and this stored hydrogen could be used either in fuel cells or burning it to get thermal energy. This study focuses on PV system and the available energy taken from it, and the electrolysers and its requirements and products. Making a mathematical model would be done and plotting the curves that represent the system by programming it using MATLAB. A simple numeral example that clears the system would be calculated. By this way, the energy efficiency would be between 23 to 67 % according to the way the produced hydrogen is used, {"references":["http://journal.tishreen.edu.sy/index.php/engscnc/article/view/2886/2728"]}

The promotion of the distributed generation and the photovoltaic (PV) energy great potential put this technology in the spotlight of investors. Thus, the optimization of its efficiency is made a priority. In this paper, a complete and versatile remote controller (C&VRC) for PV systems is presented, scalable to any kind and size of installations (with or without partial shading, with or without connection to the grid, housing, small plants or even large-scale solar plants) and valid for any weather conditions. The C&VRC involves the controller itself, which is constituted by a set of sensors and actuators connected to the converters Direct Current (DC)/DC and DC/Alternating Current (AC), if necessary, and a control unit communicated with them through the third-generation mobile telecommunications technology (3G) network. The control strategies can be changed according to the different weather conditions and installations characteristics, which guaranties the optimum performance of the system. The use of the 3G network as communication platform makes the C&VRC useful in remote and low accessibility places, because it is the most extended worldwide. The C&VRC is also based on free software, open hardware and low-cost electronic devices. Experimental results are presented in this paper to show the C&VRC optimum usability., This paper is framed in the project “Integral control system to optimize the microgrids energy demand” funded by the Spanish Ministry of Science and Innovation, call for Scientific and Technical Research and Innovation 2020-2023. Funding for open access charge: Universidad de Huelva / CBUA.This paper is framed in the project “Integral control system to optimize the microgrids energy demand” funded by the Spanish Ministry of Science and Innovation, call for Scientific and Technical Research and Innovation 2020-2023. Funding for open access charge: Universidad de Huelva / CBUA.

The aim of this work is to carry out a sustainability study in five campuses of the Universitat Politècnica de Catalunya BarcelonaTech (UPC) around Catalunya, i.e. Campus North and South Campuses in Barcelona city, Campus Baix Llobregat, Campus Manresa and Campus Vilanova i la Geltrú. The amount of consumed energy included in the study for each campus corresponds to monitoring data of previous periods. The study analyses the expected energy production, as well as the self-consumption that can be achieved by using photovoltaic (PV) systems of 25, 50 and 100 kWp and c-Si, Poly or CdTe Technology in order to reduce the environmental impact in each campus. An economic analysis of all the proposed facilities was conducted to examine their financial feasibility. Peer Reviewed Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant Objectius de Desenvolupament Sostenible::4 - Educació de Qualitat

Photovoltaic (PV) systems operating in real conditions of work are very often subject to several faults that may lower significantly the produced energy and shorten their availability. Therefore, powerful and trusted fault detection procedures are necessary to enable early maintenance and avoid excessive energy losses. The large increase in PV power installed worldwide in recent years, especially in systems connected to electricity distribution networks: Grid-connected PV systems, has led to the development of strategies and tools for automatic supervision of these systems to detect faults and diagnose the source of these failures. This chapter presents a review of most relevant existing methodologies applied in fault detection and diagnosis of PV systems. Peer Reviewed Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant Objectius de Desenvolupament Sostenible::13 - Acció per al Clima

This paper details a voltage control strategy based on Generalized Predictive Control (GPC) applied to a single-phase T-type neutral point clamped voltage source inverter in stand-alone operation mode. A performance comparison between the GPC and a Proportional-Integral (PI) controller is presented to highlight the improved performance of GPC under different load scenarios. The main results show that the GPC can achieve longer prediction horizons than other controllers based on model predictive control. Furthermore, in contrast to the PI controller, the GPC responds to load changes as disturbances. Finally, GPC can operate efficiently without an online optimization method nor recursive system identification method. ispartof: pages:1-7 ispartof: 2021 IEEE 22nd Workshop on Control and Modelling of Power Electronics (COMPEL) pages:1-7 ispartof: 2021 IEEE 22nd Workshop on Control and Modelling of Power Electronics (COMPEL) location:Cartagena, Colombia date:2 Nov - 5 Nov 2021 status: published

In the context of the current energy crisis and climate change, the importance of discussions on how to incorporate monument protection into sustainable strategies that mitigate the human impact on the environment and implement renewable sources while preserving cultural values is raised. Through the case study of the Monument Reserve in Bratislava, Slovakia, this article presents the potentials and limits of the integration of photovoltaic systems in historic urban structures that directly affect their feasible participation in smart city and positive energy district concepts by means of energy cooperativeness. This study highlights the most current recommendations and basic principles on how to assess their visual impact and select the most appropriate solutions. Using the datafication process, it analyzes the irradiance of pitched and flat roof polygons of the set area based on their characteristics such as the normal vector azimuth and slope of the rooftops. For this purpose, a 3D morphological model in LOD3 detail and the open-source solar irradiation model r.sun implemented in GRASS GIS / QGIS were used. The data obtained provided an estimate of the output potential to endow the city’s power grid and were compared to the electricity consumption of the particular city district. Furthermore, these data are suitable for designing a customized technical and aesthetic solution for the integration of photovoltaics with respect to cultural sustainability, as well as for decision- and policy makers.

Solar PV systems have so far been the source of choice for the sustainable supply of urban electric transport networks—like trams and trolleybus grids. However, no consensus exists yet on the placement or sizing of PV systems at the traction substations, and no method is available for easy estimation of the PV system utilization performance. The latter is crucial for understanding the need for storage, grid exchange, or even power curtailment, and has therefore a direct impact on the technical and financial feasibility of the project. This paper looks at 11 Key Performance Indicators (KPI) that are available to trolleybus operators, in two PV case studies on Arnhem (NL) and Gdynia (PL), using verified and validated bus, grid, and PV models. Through one KPI, namely the here-defined Energy Traffic KPI, a strong trend (R2=0.93) is described that can now allow stakeholders a quick estimation of the PV potential using a simple third-degree polynomial instead of resorting to the complex grid, bus, and PV modelling. A simple placement and sizing method is also presented derived from this KPI, in a way as to increase the technical and economical feasibility of an installed PV system. Despite all efforts, stakeholders are still warned of an intrinsic, upper-performance plateau that exists in transport grids, at around 38% direct PV utilization, caused by the unavoidable mismatch between PV generation and vehicle timetables and schedules. Stakeholders are urged to implement more smart grid loads as a base load to increase the feasibility of their investments in renewables, and to transform the transportation systems thereby to multi-functional grids that can assist the main city grid.

Maximum power point tracker (MPPT) methods work to maximize the output power of a PV system under changes in meteorological conditions. The performance of these methods depends on the complexity of the algorithm and the number of used variable inputs for obtaining the MPP value. Moreover, they oscillate around the MPP in steady-state operations, causing a waste of power and power loss. Moreover, they do not work perfectly for a PV system running under partial shading conditions. Therefore, this paper proposes modifications to the global maximum power point bald eagle search-based (GMPP BES) method so that it runs as an MPPT as well. The modifications enable the GMPP BES method to detect minor changes in insolation and temperature by observing the changes in the PV array output voltage and, accordingly, trigger the search for the suitable MPP voltage. An experimental setup using a real-time digital simulator (RTDS) was utilized to evaluate the modified GMPP BES-based method under real changes in insolation and ambient temperature. The RTDS simulations confirm the capability of the modified method to accurately and efficiently locate the MPP values. Furthermore, the results demonstrate that the proposed method performs better than the perturb and observe (PO) method concerning its ability to respond to changes in insolation and ambient temperature and its ability to arrive at correct MPP values with nearly zero oscillation around the maximum power point. Thus, with these advantages, the proposed method can be considered a practical solution for solar farms that have to harvest large amounts of energy.

The catch of fish is so large and often not completely sold, causing the fish to be wasted for free. This situation even indirectly causes environmental pollution around the area where fishermen live. To overcome this problem, a fish drying machine was made using a PV system. This tool is also a form of solving the problem of the traditional fish drying process which is sometimes not clean, safe, and depends on direct sunlight. This PV system can meet 169.95% of the need for 240 Wh/day of electrical energy from fish dryers. PV system can produce electrical energy for 407.81 Wh/day, where the largest energy can reach 520 Wh and the smallest is 160.8 Wh. The results of the analysis of the impact of using fish dryers socially and economically also gave significant results (p 4.19-5.26.

This paper presents a classical estimation problem for calculating the energy generated by photovoltaic solar energy systems, on a daily, annual, regional and national basis. Our methodology relies on two data sources: PVOutput, an online portal with solar energy production measurements, and modelled irradiance data available for large parts of Africa and Europe, from the Royal Netherlands Meteorological Institute. Combining these, we obtain probability functions of observing energy production, given the irradiation. These are applied to a PV systems database, using Monte Carlo sampling, allowing daily and annual solar energy production to be calculated. These are, in turn, used to calculate solar energy production per municipality. As a case study, we apply this methodology to one country in particular, namely the Netherlands. By examining the variation in our estimates as a result of taking different subsets of PVOutput systems with certain specifications such as azimuth, tilt and inverter loading ratio, we obtain specific annual energy yields in the range of 877-946kWh/kWp and 838-899kWh/kWp for 2016 and 2017 respectively. The current method used at Statistics Netherlands assumes this to be 875kWh/kWp, irrespective of irradiation, meaning the yields were underestimated in 2016 and overestimated in 2017. In the case of the Netherlands, this research demonstrates that an irradiation based measure of solar energy generation is necessary. More generally, this research shows that different types of open data sources may be combined to develop models that calculate the energy production of PV system populations.

Photovoltaic (PV) systems are used to generate electricity and they are considered less aggressive in their environmental impact. These systems require no further maintenance once they are installed, they do not pollute the environment and their average lifespan is high. These are the reasons why they are considered a good alternative for electricity generation. However, PV systems have different challenges to solve when they are connected to low voltage distribution grids and one of them is related to the power quality when there is a high penetration of PV systems, when voltage variations usually appear. In this paper, a central energy storage system (ESS) is considered to alleviate grid voltage variations under a high penetration scenario of PV systems instead of using multiples ESS. The proposal controls the energy injected into the grid to maintain the voltage variation within the standard, no limitations are imposed on the PV systems, and then as an advantage of the proposal, the PVs’ available energy is fully delivered to the grid. In addition, in the absence of sunlight the ESS may provide power to the grid. An analysis and experimental setup were built to validate the proposed scheme.

Doktorska disertacija obravnava delovanje in staranje fotonapetostnih (PV) modulov in fotonapetostnih sistemov, ki delujejo v različnih podnebnih razmerah po vsem svetu. Glavni poudarek je na razvoju novih pristopov za ocenjevanje zmogljivosti in izgub modulov in sistemov. Predstavljenih in pojasnjenih je več novih pristopov, ki temeljijo na zajetih podatkih, kot so metoda tipičnih dnevnih profilov (TDP), Köppen-Geiger-Photovoltaic (KGPV) klimatska klasifikacijska shema in ocena donosa zaradi podnebnih sprememb (CCYA). Disertacija obdela metode vrednotenja zmogljivosti in izgub pri proizvodnji električne energije iz fotonapetostnih modulov in sistemov. Pri tem se pridobivajo, združujejo, čistijo in obdelujejo raznolike in velike količine podatkov iz raziskovalnih ustanov, fotovoltaičnih elektrarn, podnebnih modelov in satelitskih podatkov, ki omogočajo dragocen vpogled v dejansko stanje in trende. Podatkovni viri so razvrščeni v geografske informacijske sisteme (GIS) in časovne vrste, pri čemer izkoriščamo oba načina ločeno in skupaj. V okviru disertacije je razvoj pristopov z ustreznim izborom podatkovnih virov, povezanih s fotovoltaiko, omogočil predstavitev globalnih zemljevidov za določitev najboljših področij za proizvodnjo električne energije in opredelitev tveganih lokacij v luči povečane stopnje degradacije, tudi na račun umazanije in zasneževanja. V zadnjem sklopu so ključni kazalniki učinkovitosti, kot sta razmerje učinkovitosti in stopnja degradacije, analizirani, modelirani in ovrednoteni na časovni projekciji do leta 2100 in na globalni prostorski ravni, kar omogoča oceno podnebnih vplivov na podlagi preteklih podatkov in različnih scenarijev podnebnih sprememb. This doctoral dissertation discusses the performance and ageing of PV modules and PV systems operating in different climates worldwide. The primary focus is developing new techniques for assessing the gain and loss factors of PV technologies. Several novel data-driven techniques, such as the Typical Daily Profiles (TDP) method, the Köppen-Geiger-Photovoltaic (KGPV) climate classification scheme, and the Climate Change Yield Assessment (CCYA), are introduced and explained with interesting case studies. The basis of the gain and loss factors of energy production based on typical PV technologies are discussed. Here, diverse and large amounts of data from research facilities, PV power plants, climate models, and satellite-based information are retrieved, combined, cleaned, and processed, bringing valuable insights to the PV industry. The research categorizes data resources into geographical information systems (GIS) and single-time-series, taking advantage of both ways separately and combined. In the frame of this thesis, the selection of relevant PV related data sources and methodologies has allowed the presentation of eye-catching global maps to identify the best places for energy production and the identification of risky locations in terms of degradation, soiling and snow shading. Finally, key performance indicators, such as performance ratio and degradation rates, are analyzed, modelled, and evaluated on a temporal and spatial scale, being able to assess climatic impacts on historical data and under different climate change scenarios.

This article presents an initial performance analysis of a database of photovoltaic (PV) system performance time series collected within the European funded COST Action PEARL PV. The database contains monitoring data of over 8400 PV systems with accompanying metadata. The PV plants are small residential systems, primarily installed in Europe, with a high density in Belgium. In this initial study, the annual average performance ratio, the annual energy yield, and the performance loss rate of the systems are determined and evaluated. The systems have an average lifetime of 30.5 months. The annual mean performance ratio across all systems is 76.7% and the average yield is 954.9 kWh/kWp per year. The performance loss rate is calculated using three different statistical approaches and one irradiance data source. Average performance losses between $-$ 0.74%/year and $-$ 0.86%/year are calculated depending on the used approach. Furthermore, certain weather-dependent correlations are detected, such as decreasing performance ratio and increasing yield values with increasing irradiation. This study is a stepping-stone for further populating the present database, lessons learnt for handling large amounts of PV performance data, and carrying out performance studies of PV system fleets installed across Europe.

This paper proposes a flexible method for power-sharing control of single-phase AC Microgrid or sub-system that operate inverters in parallel to supply the demand. The Photovoltaic (PV) system, coupled with batteries, energized each inverter. Solar power data from the equator city area were included in the PV system for simulation with its dynamics due to weather fluctuation. The proposed power-sharing control approach combined with integral action to improve the power quality and power-sharing accuracy. It conveys three considerations for flexible power-sharing: using virtual load voltage and the frequency at grid connection terminal (i.e., point of common coupling) in the controller without direct measurement to avoid using external communication, applying those virtual values to calculate the required parameters for an accurate power-sharing and proposing a concept of extended traditional droop control coefficient to be able to apply for various line impedances. The presented case study had two inverters supported by dynamics coupled sources from a PV system installed in an equatorial city used in the MATLAB experiment and batteries function block connected in parallel. Those inverters, located in different sub-systems, supplied two sub-systems (i.e., Microgrids) with different line impedance. The presented approach can also work for more than two or multiple sub-system scenarios by replicating the same control mechanism for the new sub-system.

Haze has a significant impact on photovoltaic (PV) power generation. When the fine particulate matter reaches a certain concentration, it becomes the main factor affecting solar irradiance and seriously reduces PV power generation, but few quantitative studies on the effect caused by haze to PV power generation. This study proposes the use of the improved method of the degree of grey slope incidence to analyze the weight factors of the effects of haze on irradiance. The exponential-linear model is used to describe the impact of haze on the amount of irradiance. Furthermore, the PV system model is used to focus on the quantitative loss of PV power under the influence of haze. By modeling and analyzing the data samples of PV power generation in Hangzhou, China, it can be concluded that the losses caused by haze on PV power generation in 2017 and 2018 were 5.25 ± 1.19% and 6 ± 1.16% of the original PV power generation, respectively. We extended this analysis to other cities to analyze the PV data in Tianjin, China. From December 2018 to December 2019, the loss of PV power generation caused by haze in Tianjin was 8.77 ± 0.9%. The quantitative analysis of haze on PV power can provide an effective basis for the economic evaluation of new PV systems and also plays an important role in the prediction and scheduling of PV power generation.

Medium-voltage (MV) multilevel converters are considered a promising solution for large scale photovoltaic (PV) systems to meet the rapid energy demand. This article focuses on reviewing the different structures and the technical challenges of modular multilevel topologies and their submodule circuit design for PV applications. The unique structure of the converter’s submodule provides modularity, independent control of maximum power point tracking (MPPT), galvanic isolation, etc. Different submodule circuits and MPPT methods to efficiently extract the PV power are reviewed. The integration of the multilevel converters to PV systems suffers unbalanced power generation during partial PV shading conditions. Several balancing strategies to solve this problem are presented and compared to give a better understanding of the balancing ranges and capabilities of each strategy. In addition, the paper discusses recent research advancements, and possible future directions of MV converters-based large-scale PV systems for grid integration.

This contribution proposes an efficient methodology in time domain (TD) based on companion-circuit analysis (CCA) and a Newton method of extrapolation to the Limit Cycle (periodic steady state solution) based on a Numerical Differentiation (ND) process. Its formulation is amenable to the solution approach followed by standardized digital simulators widely accepted by the power industry, such as EMTP and/or EMTDC. The particular application reported in this research is oriented to the dynamic and fast periodic steady state solution of nonlinear single-phase electrical networks incorporating photovoltaic (PV) systems under harmonic distortion conditions. Fundamentally, the proposed methodology is based on the representation of linear and nonlinear elements (e.g., switching elements), using Norton equivalents. This solution method is based on the determination of discrete differential equations sets, obtained by nodal analysis. The solution process is iteratively obtained by using LU decomposition. In general terms, the application is based on the combination of the CCA and ND methods (CCA-ND), for the applying in different case studies associated with the assessment of harmonics distortion, in terms of individual and total harmonic distortion at the point of common coupling (PCC) between the PV system and the electrical system are reported. It is shown that the methodology is precise, reliable and efficient. The documented results have been successfully validated against those obtained PSCAD/EMTDC® simulator, widely accepted by the power industry.

Despite being a tropical country with great potential for solar power, knowledge about the actual performance of photovoltaic (PV) systems in Indonesia remains limited. In this paper, using 5-minute resolution data from 2016 to 2018 obtained from a 1 MW Copper Indium Selenide (CIS) and a 5 kW crystalline silicon (c-Si) PV plant in West Java, we aim to answer the question of how a CIS PV plant performs and degrades in Indonesia's tropical climate and how it compares to a PV system that contains c-Si technology. The methodological approach used includes performance analyses of these PV systems according to IEC standard 61724 and an investigation of the degradation rate using NREL/RdTools. The following results were derived from the analyses: the total annual Hi was 1500 kWh/m2 or around 4.2 kWh/m2/day. The daily-averaged performance ratio, PR, was 91.7 % ± 4 % and 87.4 % ± 7 % for the CIS system with string inverters and a central inverter, respectively. The mean PR of the CIS systems was 12 % higher than that of the c-Si system, which was 79.8 %. Concerning the final yield, Yf, the CIS system with a mean Yf of 3.85 kWh/kWp outperformed the c-Si system by 14 %. The CIS system degraded by 1.53 % per year, which is less than the c-Si system with a degradation rate (Rd) of 3.72 % per year. From these results, it can be concluded that, in this case, CIS technology performs better than c-Si in Indonesia's tropical climate. Uncertainties in the calculation and high values of Rd could be areas for further investigation.

Battery energy storage systems (BESS) have started to be part of the photovoltaic (PV) system design to allow the further penetration of PV into the grid. This study deals with the sizing (power and energy capacity) of a BESS for residential households which are represented by a typical load consumption profile, they have electrical air conditioning and electrical water heating (water boiler) resembling a common residential house in Cyprus. The BESS sizing is done considering the local energy consumption profile and the energy efficiency class of the house and the water boiler. The BESS is sized in order to achieve zero PV grid export and to increase self-consumption. 2019 18 4770 4774

Internet of things (IoT) devices are often located in difficult-to-access places without connection to the electrical grid. For this reason, some IoT devices usually incorporate a small stand-alone photovoltaic (PV) system to power only the IoT device. However, several IoT applications involve using other components, such as instrumentation, electrical motors, lighting bulbs, etc., which require additional electrical power. The objective of this study was to design and implement a battery controller integrated into a constrained resource device that allows powering not only other components of the IoT application but also the IoT device. In this way, the IoT device controls and monitors the PV system and executes other IoT applications such as lighting. Results show that the designed controller exhibits efficient behavior when compared with other regulators and can be integrated into resource-constrained devices, improving the life of batteries and reducing cost.

The problem of electrical power delivery is a common problem, especially in remote areas where electrical networks are difficult to reach. One of the ways that is used to overcome this problem is the use of networks separated from the electrical system through which it is possible to supply electrical energy to remote areas. These networks are called standalone microgrid systems. In this paper, a standalone micro-grid system consisting of a Photovoltaic (PV) and Wind Energy Conversion System (WECS) based Permanent Magnet Synchronous Generator (PMSG) is being designed and controlled. Fuzzy logic-based Maximum Power Point Tracking (MPPT) is being applied to a boost converter to control and extract the maximum power available for the PV system. The control system is designed to deliver the required energy to a specific load, in all scenarios. The excess energy generated by the PV panel is used to charge the batteries when the energy generated by the PV panel exceeds the energy required by the load. When the electricity generated by the PV panels is insufficient to meet the load’s demands, the extra power is extracted from the charged batteries. In addition, the controller protects the battery banks in all conditions, including normal, overcharging, and overdischarging conditions. The controller should handle each case correctly. Under normal operation conditions (20% < State of Charge (SOC) < 80%), the controller functions as expected, regardless of the battery’s state of charge. When the SOC reaches 80%, a specific command is delivered, which shuts off the PV panel and the wind turbine. The PV panel and wind turbine cannot be connected until the SOC falls below a safe margin value of 75% in this controller. When the SOC goes below 20%, other commands are sent out to turn off the inverter and disconnect the loads. The electricity to the inverter is turned off until the batteries are charged again to a suitable value.