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Prof. Dr. George E. Georghiou
Photovoltaic Technology Laboratory, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus

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0 Solar Energy
0 Storage
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Journal article
Published: 21 June 2021 in Energies
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Distributed generation (DG) systems are growing in number, diversifying in driving technologies and providing substantial energy quantities in covering the energy needs of the interconnected system in an optimal way. This evolution of technologies is a response to the needs of the energy transition to a low carbon economy. A nanogrid is dependent on local resources through appropriate DG, confined within the boundaries of an energy domain not exceeding 100 kW of power. It can be a single building that is equipped with a local electricity generation to fulfil the building’s load consumption requirements, it is electrically interconnected with the external power system and it can optionally be equipped with a storage system. It is, however, mandatory that a nanogrid is equipped with a controller for optimisation of the production/consumption curves. This study presents design consideretions for nanogrids and the design of a nanogrid system consisting of a 40 kWp photovoltaic (PV) system and a 50 kWh battery energy storage system (BESS) managed via a central converter able to perform demand-side management (DSM). The implementation of the nanogrid aims at reducing the CO2 footprint of the confined domain and increase its self-sufficiency.

ACS Style

Yerasimos Yerasimou; Marios Kynigos; Venizelos Efthymiou; George Georghiou. Design of a Smart Nanogrid for Increasing Energy Efficiency of Buildings. Energies 2021, 14, 3683 .

AMA Style

Yerasimos Yerasimou, Marios Kynigos, Venizelos Efthymiou, George Georghiou. Design of a Smart Nanogrid for Increasing Energy Efficiency of Buildings. Energies. 2021; 14 (12):3683.

Chicago/Turabian Style

Yerasimos Yerasimou; Marios Kynigos; Venizelos Efthymiou; George Georghiou. 2021. "Design of a Smart Nanogrid for Increasing Energy Efficiency of Buildings." Energies 14, no. 12: 3683.

Journal article
Published: 18 February 2021 in Energies
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A main challenge for integrating the intermittent photovoltaic (PV) power generation remains the accuracy of day-ahead forecasts and the establishment of robust performing methods. The purpose of this work is to address these technological challenges by evaluating the day-ahead PV production forecasting performance of different machine learning models under different supervised learning regimes and minimal input features. Specifically, the day-ahead forecasting capability of Bayesian neural network (BNN), support vector regression (SVR), and regression tree (RT) models was investigated by employing the same dataset for training and performance verification, thus enabling a valid comparison. The training regime analysis demonstrated that the performance of the investigated models was strongly dependent on the timeframe of the train set, training data sequence, and application of irradiance condition filters. Furthermore, accurate results were obtained utilizing only the measured power output and other calculated parameters for training. Consequently, useful information is provided for establishing a robust day-ahead forecasting methodology that utilizes calculated input parameters and an optimal supervised learning approach. Finally, the obtained results demonstrated that the optimally constructed BNN outperformed all other machine learning models achieving forecasting accuracies lower than 5%.

ACS Style

Spyros Theocharides; Marios Theristis; George Makrides; Marios Kynigos; Chrysovalantis Spanias; George E. Georghiou. Comparative Analysis of Machine Learning Models for Day-Ahead Photovoltaic Power Production Forecasting. Energies 2021, 14, 1081 .

AMA Style

Spyros Theocharides, Marios Theristis, George Makrides, Marios Kynigos, Chrysovalantis Spanias, George E. Georghiou. Comparative Analysis of Machine Learning Models for Day-Ahead Photovoltaic Power Production Forecasting. Energies. 2021; 14 (4):1081.

Chicago/Turabian Style

Spyros Theocharides; Marios Theristis; George Makrides; Marios Kynigos; Chrysovalantis Spanias; George E. Georghiou. 2021. "Comparative Analysis of Machine Learning Models for Day-Ahead Photovoltaic Power Production Forecasting." Energies 14, no. 4: 1081.

Journal article
Published: 07 February 2021 in Renewable Energy
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Bifacial solar panels installed on flat rooftop of industrial buildings are an effective way to boost the yield. The albedo of the flat roof determines to great extent the bifacial gain. However, because it changes due to soiling and moss growth, the power output of bifacial PV installations over time is difficult to calculate. For the purpose of evaluating and rating the effect of bifacial PV rooftop systems, a small plant with 20 modules including dummies was installed. To guarantee an optimized output, a commercial bifacial PV module supporting construction was placed on a flat roof that was painted white. By using an east-west orientation, an optimum for the use of available roof space was reached. The yield for each module was determined with power optimizers and the extracted data, provided by the monitoring portal, were analysed. The data were collected for each day over a time of one year. Three different modules, both east and west orientated, were investigated. The bifacial module with a transparent backsheet compared to a module with the same bifacial cells but with a black backsheet, showed initially a benefit of 17% for the east and 15% for the west orientated panels. After one year of operation, a measured benefit of 7% for the east and 5% for the west orientated panels remained due to albedo loss because of moss growth and pollution. The use of panels with 92% bifaciality resulted in a higher yield of up to 3% compared to panels with 70% bifaciality.

ACS Style

W. Muehleisen; J. Loeschnig; M. Feichtner; A.R. Burgers; E.E. Bende; S. Zamini; Y. Yerasimou; J. Kosel; C. Hirschl; G.E. Georghiou. Energy yield measurement of an elevated PV system on a white flat roof and a performance comparison of monofacial and bifacial modules. Renewable Energy 2021, 170, 613 -619.

AMA Style

W. Muehleisen, J. Loeschnig, M. Feichtner, A.R. Burgers, E.E. Bende, S. Zamini, Y. Yerasimou, J. Kosel, C. Hirschl, G.E. Georghiou. Energy yield measurement of an elevated PV system on a white flat roof and a performance comparison of monofacial and bifacial modules. Renewable Energy. 2021; 170 ():613-619.

Chicago/Turabian Style

W. Muehleisen; J. Loeschnig; M. Feichtner; A.R. Burgers; E.E. Bende; S. Zamini; Y. Yerasimou; J. Kosel; C. Hirschl; G.E. Georghiou. 2021. "Energy yield measurement of an elevated PV system on a white flat roof and a performance comparison of monofacial and bifacial modules." Renewable Energy 170, no. : 613-619.

Review
Published: 21 January 2021 in Renewable Energy
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Due to the potential for deploying distributed generation, improving energy efficiency and adopting sustainable energy-related practices, consumers provide significant value in the energy sector transformation. If their interests and goals are similar, they can group together and form energy communities. Energy communities enable consumers to jointly pursue their individual and collective economic, environmental and social goals, while simultaneously contributing to the decarbonisation of the energy system. Considering the growing interest in this field, this paper aims to enhance the understanding of the social arrangements, the technical designs and the impacts of energy communities. The social arrangements of energy communities are discussed in relation to the different actors, their roles and interactions. Then, the paper reviews the technical aspects of designing various local energy systems, while taking into account the goals of energy community members and outside actors. The reviewed literature is benchmarked with respect to the methods, modelling objectives and the constraints used in the design process. Finally, the paper quantifies the economic, environmental, technical and social impacts of energy communities, reviews the numerical indicators used to quantify these impacts and provides a critical discussion of the findings. Based on the findings, future research directions are highlighted.

ACS Style

Vladimir Z. Gjorgievski; Snezana Cundeva; George E. Georghiou. Social arrangements, technical designs and impacts of energy communities: A review. Renewable Energy 2021, 169, 1138 -1156.

AMA Style

Vladimir Z. Gjorgievski, Snezana Cundeva, George E. Georghiou. Social arrangements, technical designs and impacts of energy communities: A review. Renewable Energy. 2021; 169 ():1138-1156.

Chicago/Turabian Style

Vladimir Z. Gjorgievski; Snezana Cundeva; George E. Georghiou. 2021. "Social arrangements, technical designs and impacts of energy communities: A review." Renewable Energy 169, no. : 1138-1156.

Journal article
Published: 05 January 2021 in IEEE Journal of Photovoltaics
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Photovoltaic (PV) soiling profiles exhibit a sawtooth shape, where cleaning events and soiling deposition periods alternate. Generally, the rate at which soiling accumulates is assumed to be constant within each deposition period. In reality, changes in rates can occur because of sudden variations in climatic conditions, e.g., dust storms or prolonged periods of rain. The existing models used to extract the soiling profile from the PV performance data might fail to capture the change points and occasionally estimate incorrect soiling profiles. This work analyzes how the introduction of change points can be beneficial for soiling extraction. Data from nine soiling stations and a 1-MW site were analyzed by using piecewise regression and three change point detection algorithms. The results showed that accounting for change points can provide significant benefits to the modeling of soiling even if not all the change point algorithms return the same improvements. Considering change points in historical trends is found to be particularly important for studies aiming to optimize cleaning schedules.

ACS Style

Leonardo Micheli; Marios Theristis; Andreas Livera; Joshua S. Stein; George E. Georghiou; Matthew Muller; Florencia Almonacid; Eduardo F. Fernandez. Improved PV Soiling Extraction Through the Detection of Cleanings and Change Points. IEEE Journal of Photovoltaics 2021, 11, 519 -526.

AMA Style

Leonardo Micheli, Marios Theristis, Andreas Livera, Joshua S. Stein, George E. Georghiou, Matthew Muller, Florencia Almonacid, Eduardo F. Fernandez. Improved PV Soiling Extraction Through the Detection of Cleanings and Change Points. IEEE Journal of Photovoltaics. 2021; 11 (2):519-526.

Chicago/Turabian Style

Leonardo Micheli; Marios Theristis; Andreas Livera; Joshua S. Stein; George E. Georghiou; Matthew Muller; Florencia Almonacid; Eduardo F. Fernandez. 2021. "Improved PV Soiling Extraction Through the Detection of Cleanings and Change Points." IEEE Journal of Photovoltaics 11, no. 2: 519-526.

Journal article
Published: 21 December 2020 in Energies
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A main challenge towards ensuring improved lifetime performance and reduction of financial risks of photovoltaic (PV) technologies remains the accurate degradation quantification of field systems and the dependency of this performance loss rate to climatic conditions. The purpose of this study is to address these technological issues by presenting a unified methodology for accurately calculating the degradation rate () of PV systems and provide evidence that degradation mechanisms are location dependent. The method followed included the application of data inference and time series analytics, in the scope of comparing the long-term of different crystalline Silicon (c-Si) PV systems, installed at different climatic locations. The application of data quality and filtering steps ensured data fidelity for the analysis. The yearly results demonstrated that the adopted time series analytical techniques converged after 7 years and were in close agreement to the degradation results obtained from indoor standardized procedures. Finally, the initial hypothesis that the is location dependent was verified, since the multicrystalline silicon (multi-c-Si) systems at the warm climatic region exhibited higher degradation compared to the respective systems at the moderate climate. For the investigated monocrystalline silicon (mono-c-Si) systems the location-dependency is also affected by the manufacturing technology.

ACS Style

Alexander Frick; George Makrides; Markus Schubert; Matthias Schlecht; George E. Georghiou. Degradation Rate Location Dependency of Photovoltaic Systems. Energies 2020, 13, 6751 .

AMA Style

Alexander Frick, George Makrides, Markus Schubert, Matthias Schlecht, George E. Georghiou. Degradation Rate Location Dependency of Photovoltaic Systems. Energies. 2020; 13 (24):6751.

Chicago/Turabian Style

Alexander Frick; George Makrides; Markus Schubert; Matthias Schlecht; George E. Georghiou. 2020. "Degradation Rate Location Dependency of Photovoltaic Systems." Energies 13, no. 24: 6751.

Journal article
Published: 10 December 2020 in Physics of Plasmas
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In the present report, an atmospheric pressure plasma jet is sustained in a helium channel by high square wave unipolar voltage. The gas flow rate and the square wave features (amplitude, frequency, and duty cycle) are varied over a wide range, while the plasma ultraviolet to near infrared emission is recorded. The plasma emission pattern, the propagation dynamics of the involved ionization fronts, the relative density of critical excited species, and the rotational and vibrational temperatures of neutral and ionic species are measured. An optimum operational window is found corresponding to a helium flow rate of 2 slm, a pulse amplitude of 7.5 kV, a pulse repetition rate of 10 kHz, and a pulse duty cycle of 5%–7%. Under these conditions, a plasma jet length close to 45 mm and a gas temperature close to 325 K are obtained, while a high yield of OH, N2(SPS), N 2 +(FNS), N2(FPS), He*, O*, and NOγ is achieved. The results are found to be in good agreement with the bibliography and motivate a consideration on the involved physical mechanisms. The plasma jet propagation with respect to the reactive species production is discussed based on the local electric field variation over the high voltage pulse width.

ACS Style

K. Gazeli; P. Svarnas; C. Lazarou; C. Anastassiou; G. E. Georghiou; P. K. Papadopoulos; F. Clément. Physical interpretation of a pulsed atmospheric pressure plasma jet following parametric study of the UV–to–NIR emission. Physics of Plasmas 2020, 27, 123503 .

AMA Style

K. Gazeli, P. Svarnas, C. Lazarou, C. Anastassiou, G. E. Georghiou, P. K. Papadopoulos, F. Clément. Physical interpretation of a pulsed atmospheric pressure plasma jet following parametric study of the UV–to–NIR emission. Physics of Plasmas. 2020; 27 (12):123503.

Chicago/Turabian Style

K. Gazeli; P. Svarnas; C. Lazarou; C. Anastassiou; G. E. Georghiou; P. K. Papadopoulos; F. Clément. 2020. "Physical interpretation of a pulsed atmospheric pressure plasma jet following parametric study of the UV–to–NIR emission." Physics of Plasmas 27, no. 12: 123503.

Journal article
Published: 23 October 2020 in IEEE Journal of Photovoltaics
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Potential-induced degradation (PID) is an unsolved and major power degradation mechanism that affects photovoltaic (PV) cells, and the tendency to increase the operating voltage of PV systems will render it worse, affecting their reliability. A method, which can detect PID at an early stage, can alleviate reliability issues, safeguarding high energy output. The measurement of the forward dc resistance (FDCR) provides promising results for the early PID detection (<2% power loss). The FDCR method is tested on single-cell and multi-cell PV modules and it is the pathway for the development of a detection method at the system level. This work examines the effect of PID degradation rate and temperature on the detection sensitivity (electrical behavior) of the FDCR method. Additionally, the effect of temperature (temperature behavior) on the FDCR as PID progresses is studied. The electrical behavior demonstrates that the detection sensitivity is robust to PID degradation rate and temperature and that the degradation rate is not related to the initial shunt resistance of the PV cell. The temperature behavior indicates that the temperature coefficient of the FDCR is initially negative and increases toward more positive values as PID progresses. Furthermore, the electrical variation of the FDCR with PID progression is much higher (74%) than the variation of the FDCR due to temperature (19%) and this favors PID detection.

ACS Style

Michalis Florides; George Makrides; George E. Georghiou. Electrical and Temperature Behavior of the Forward DC Resistance With Potential Induced Degradation of the Shunting Type in Crystalline Silicon Photovoltaic Cells and Modules. IEEE Journal of Photovoltaics 2020, 11, 16 -25.

AMA Style

Michalis Florides, George Makrides, George E. Georghiou. Electrical and Temperature Behavior of the Forward DC Resistance With Potential Induced Degradation of the Shunting Type in Crystalline Silicon Photovoltaic Cells and Modules. IEEE Journal of Photovoltaics. 2020; 11 (1):16-25.

Chicago/Turabian Style

Michalis Florides; George Makrides; George E. Georghiou. 2020. "Electrical and Temperature Behavior of the Forward DC Resistance With Potential Induced Degradation of the Shunting Type in Crystalline Silicon Photovoltaic Cells and Modules." IEEE Journal of Photovoltaics 11, no. 1: 16-25.

Research article
Published: 07 October 2020 in Progress in Photovoltaics: Research and Applications
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Data integrity is crucial for the performance and reliability analysis of photovoltaic (PV) systems, since actual in‐field measurements commonly exhibit invalid data caused by outages and component failures. The scope of this paper is to present a complete methodology for PV data processing and quality verification in order to ensure improved PV performance and reliability analyses. Data quality routines (DQRs) were developed to ensure data fidelity by detecting and reconstructing invalid data through a sequence of filtering stages and inference techniques. The obtained results verified that PV performance and reliability analyses are sensitive to the fidelity of data and, therefore, time series reconstruction should be handled appropriately. To mitigate the bias effects of 10% or less invalid data, the listwise deletion technique provided accurate results for performance analytics (exhibited a maximum absolute percentage error of 0.92%). When missing data rates exceed 10%, data inference techniques yield more accurate results. The evaluation of missing power measurements demonstrated that time series reconstruction by applying the Sandia PV Array Performance Model yielded the lowest error among the investigated data inference techniques for PV performance analysis, with an absolute percentage error less than 0.71%, even at 40% missing data rate levels. The verification of the routines was performed on historical datasets from two different locations (desert and steppe climates). The proposed methodology provides a set of standardized analytical procedures to ensure the validity of performance and reliability evaluations that are performed over the lifetime of PV systems.

ACS Style

Andreas Livera; Marios Theristis; Elena Koumpli; Spyros Theocharides; George Makrides; Juergen Sutterlueti; Joshua S. Stein; George E. Georghiou. Data processing and quality verification for improved photovoltaic performance and reliability analytics. Progress in Photovoltaics: Research and Applications 2020, 29, 143 -158.

AMA Style

Andreas Livera, Marios Theristis, Elena Koumpli, Spyros Theocharides, George Makrides, Juergen Sutterlueti, Joshua S. Stein, George E. Georghiou. Data processing and quality verification for improved photovoltaic performance and reliability analytics. Progress in Photovoltaics: Research and Applications. 2020; 29 (2):143-158.

Chicago/Turabian Style

Andreas Livera; Marios Theristis; Elena Koumpli; Spyros Theocharides; George Makrides; Juergen Sutterlueti; Joshua S. Stein; George E. Georghiou. 2020. "Data processing and quality verification for improved photovoltaic performance and reliability analytics." Progress in Photovoltaics: Research and Applications 29, no. 2: 143-158.

Journal article
Published: 18 May 2020 in IEEE Journal of Photovoltaics
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Although common practice for estimating photovoltaic (PV) degradation rate (R $_D$ ) assumes a linear behavior, field data have shown that degradation rates are frequently nonlinear. This article presents a new methodology to detect and calculate nonlinear R $_D$ based on PV performance time-series from nine different systems over an eight-year period. Prior to performing the analysis and in order to adjust model parameters to reflect actual PV operation, synthetic datasets were utilized for calibration purposes. A change-point analysis is then applied to detect changes in the slopes of PV trends, which are extracted from constructed performance ratio ( $PR$ ) time-series. Once the number and location of change points is found, the ordinary least squares method is applied to the different segments to compute the corresponding rates. The obtained results verified that the extracted trends from the PR time-series may not always be linear and therefore, “nonconventional” models need to be applied. All thin-film technologies demonstrated nonlinear behavior whereas nonlinearity detected in the crystalline silicon systems is thought to be due to a maintenance event. A comparative analysis between the new methodology and other conventional methods demonstrated levelized cost of energy differences of up to 6.14%, highlighting the importance of considering nonlinear degradation behavior.

ACS Style

Marios Theristis; Andreas Livera; C. Birk Jones; George Makrides; George E. Georghiou; Joshua S. Stein. Nonlinear Photovoltaic Degradation Rates: Modeling and Comparison Against Conventional Methods. IEEE Journal of Photovoltaics 2020, 10, 1112 -1118.

AMA Style

Marios Theristis, Andreas Livera, C. Birk Jones, George Makrides, George E. Georghiou, Joshua S. Stein. Nonlinear Photovoltaic Degradation Rates: Modeling and Comparison Against Conventional Methods. IEEE Journal of Photovoltaics. 2020; 10 (4):1112-1118.

Chicago/Turabian Style

Marios Theristis; Andreas Livera; C. Birk Jones; George Makrides; George E. Georghiou; Joshua S. Stein. 2020. "Nonlinear Photovoltaic Degradation Rates: Modeling and Comparison Against Conventional Methods." IEEE Journal of Photovoltaics 10, no. 4: 1112-1118.

Journal article
Published: 15 April 2020 in Energies
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Three load matching indicators (self-consumption rate, self-sufficiency rate, loss of load probability) and the CO2 emissions were evaluated for 55 Cypriot households with 3 kWp rooftop photovoltaic (PV) generators. The calculations were performed using 30-minute generation and consumption data from a large scale smart meter project in Cyprus. To investigate the effects of recent advances in local legislation, an analysis for higher PV capacities (5 kWp and 10 kWp) was also performed. The PV generation profiles for 5 kWp and 10 kWp PVs were obtained by scaling the 3 kWp PV generation profiles. The results showed that the self-consumption of the analyzed households varied seasonally, as it was related to their heating and cooling demand. More interestingly, the ratio between the households’ annual electricity generation and demand, formally defined here as generation-to-demand ratio (GTDR), was found to be related to the value ranges of the studied load matching indicators. Hence, on average, households with 3 kWp PV generators annually self-consumed 48.17% and exported 2,415.10 kWh of their PV generation. On the other hand, households with larger PV generators were characterized by a higher GTDR, but lower load matching capabilities. For the cases of 5 kWp and 10 kWp PV generators, the average self-consumption fell to 34.05% and 19.31%, while the exported PV generation was equal to 5,122.47 kWh, and 12,534.90 kWh, respectively. Along with lower load matching capabilities, households that generated more than they consumed were also found to have a lower potential for CO2 emissions reduction per installed kWp within the boundaries of the building. In this context, the GTDR could be used by stakeholders to characterize buildings, infer possible value ranges of more complex indicators and make evidence based decisions on policy and legislation.

ACS Style

Vladimir Z. Gjorgievski; Nikolas G. Chatzigeorgiou; Venizelos Venizelou; Georgios C. Christoforidis; George E. Georghiou; Grigoris K. Papagiannis. Evaluation of Load Matching Indicators in Residential PV Systems-the Case of Cyprus. Energies 2020, 13, 1934 .

AMA Style

Vladimir Z. Gjorgievski, Nikolas G. Chatzigeorgiou, Venizelos Venizelou, Georgios C. Christoforidis, George E. Georghiou, Grigoris K. Papagiannis. Evaluation of Load Matching Indicators in Residential PV Systems-the Case of Cyprus. Energies. 2020; 13 (8):1934.

Chicago/Turabian Style

Vladimir Z. Gjorgievski; Nikolas G. Chatzigeorgiou; Venizelos Venizelou; Georgios C. Christoforidis; George E. Georghiou; Grigoris K. Papagiannis. 2020. "Evaluation of Load Matching Indicators in Residential PV Systems-the Case of Cyprus." Energies 13, no. 8: 1934.

Journal article
Published: 08 February 2020 in Renewable Energy
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Electricity networks are experiencing increasing congestion and reliability issues as current generation and transmission infrastructures endeavour to match the supply with demand. The integration of intermittent renewable energy resources such as photovoltaic (PV) systems has led to a large variation in energy production and increased supply uncertainty in power systems. In this context, demand-side management (DSM) schemes can be used to motivate prosumers to refine their energy behaviours by offering them various incentives. This study presents a universally-applied methodology that will promote the deployment of effective price-based DSM for residential prosumers. The proposed methodology can be applied on both prosumers and consumers since the utilization of the net-load profile was found to reduce the percentage of unintended revenues by 15%. Additionally, the effectiveness of the methodology was validated through a pilot-network of 300 residential prosumers with installed rooftop PV systems, and resulted in seasonally dependent peak consumption reduction in the range of 1.03% and 3.19% and a reduction of the overall consumption by approximately 2%. Finally, the conducted cost-benefit analysis demonstrated an overall net-benefit of €4.62mln, over a 15-year period, when considering assumptions that are linked to the costs and benefits of a nationwide deployment of the proposed DSM scheme.

ACS Style

Venizelos Venizelou; George Makrides; Venizelos Efthymiou; George E. Georghiou. Methodology for deploying cost-optimum price-based demand side management for residential prosumers. Renewable Energy 2020, 153, 228 -240.

AMA Style

Venizelos Venizelou, George Makrides, Venizelos Efthymiou, George E. Georghiou. Methodology for deploying cost-optimum price-based demand side management for residential prosumers. Renewable Energy. 2020; 153 ():228-240.

Chicago/Turabian Style

Venizelos Venizelou; George Makrides; Venizelos Efthymiou; George E. Georghiou. 2020. "Methodology for deploying cost-optimum price-based demand side management for residential prosumers." Renewable Energy 153, no. : 228-240.

Journal article
Published: 12 December 2019 in Applied Sciences
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A small-scale, decentralized hybrid system is proposed for autonomous operation in a commercial building (small hotel). The study attempts to provide a potential solution, which will be attractive both in terms of efficiency and economics. The proposed configuration consists of the photovoltaic (PV) and solid oxide fuel cell (SOFC) subsystems. The fuel cell subsystem is fueled with natural gas. The SOFC stack model is validated using literature data. A thermoeconomic optimization strategy, based on a genetic algorithm approach, is applied to the developed model to minimize the system lifecycle cost (LCC). Four decision variables are identified and chosen for the thermoeconomic optimization: temperature at anode inlet, temperature at cathode inlet, temperature at combustor exit, and steam-to-carbon ratio. The total capacity at design conditions is 70 and 137.5 kWe, for the PV and SOFC subsystems, respectively. After the application of the optimization process, the LCC is reduced from 1,203,266 to 1,049,984 USD. This improvement is due to the reduction of fuel consumed by the system, which also results in an increase of the average net electrical efficiency from 29.2 to 35.4%. The thermoeconomic optimization of the system increases its future viability and energy market penetration potential.

ACS Style

Alexandros Arsalis; George E. Georghiou. Thermoeconomic Optimization of a Hybrid Photovoltaic-Solid Oxide Fuel Cell System for Decentralized Application. Applied Sciences 2019, 9, 5450 .

AMA Style

Alexandros Arsalis, George E. Georghiou. Thermoeconomic Optimization of a Hybrid Photovoltaic-Solid Oxide Fuel Cell System for Decentralized Application. Applied Sciences. 2019; 9 (24):5450.

Chicago/Turabian Style

Alexandros Arsalis; George E. Georghiou. 2019. "Thermoeconomic Optimization of a Hybrid Photovoltaic-Solid Oxide Fuel Cell System for Decentralized Application." Applied Sciences 9, no. 24: 5450.

Review
Published: 30 July 2019 in Renewable Energy
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In recent years, the scientific research into photovoltaic (PV) technology has focused on the failure modes in order to increase the PV reliability, durability and service lifetime. One of the predominant failure modes that appears in the crystalline silicon (c-Si) PV technology is the cell cracking that may damage the mechanical integrity of the PV module and hence, result in power loss due to the disconnected areas of the cell. Other forms of degradation may also be triggered such as potential induced degradation (PID) and hot spots. Therefore, the understanding of the cracking mechanism is of great importance. This paper presents the origins and factors that affect the cell cracks. Classification of cracks has been conducted as their characteristics determine the mechanical and electrical degradation of the PV module. Furthermore, experimental and numerical studies related to PV cracks on the scale of wafer, cell and PV module are analysed in detail. The results from the above investigations show that cracks do not always lead to a strong performance degradation and therefore the impact of cracks on the electrical characteristics of PV modules is still debatable.

ACS Style

Lamprini Papargyri; Marios Theristis; Bernhard Kubicek; Thomas Krametz; Christoph Mayr; Panos Papanastasiou; George E. Georghiou. Modelling and experimental investigations of microcracks in crystalline silicon photovoltaics: A review. Renewable Energy 2019, 145, 2387 -2408.

AMA Style

Lamprini Papargyri, Marios Theristis, Bernhard Kubicek, Thomas Krametz, Christoph Mayr, Panos Papanastasiou, George E. Georghiou. Modelling and experimental investigations of microcracks in crystalline silicon photovoltaics: A review. Renewable Energy. 2019; 145 ():2387-2408.

Chicago/Turabian Style

Lamprini Papargyri; Marios Theristis; Bernhard Kubicek; Thomas Krametz; Christoph Mayr; Panos Papanastasiou; George E. Georghiou. 2019. "Modelling and experimental investigations of microcracks in crystalline silicon photovoltaics: A review." Renewable Energy 145, no. : 2387-2408.

Journal article
Published: 22 May 2019 in IEEE Journal of Photovoltaics
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In this paper, the annual performance loss rates (PLRs) of five different grid-connected photovoltaic (PV) technologies based on outdoor field measurements were computed. The data used were collected in five different geographical locations covering five climatic zones. The PLR values were determined as absolute and relative measures for all sites and module types using seasonal time series decomposition using local regression. The results are very consistent and show a clustering of the PLR for each technology, provided some explainable outliers are removed. This allows the conclusion that in presence of properly sized and quality-driven systems, the influence of different climates on the degradation of PV modules is not very strong. In the first approximation, individual degradations rate values computed in a single climatic zone can be seen as representative for the technology in general. The reason for this is that for defects there is an associated activation energy, which has not been reached yet in the systems analyzed in this study.

ACS Style

Philip Ingenhoven; Giorgio Belluardo; George Makrides; George E. Georghiou; Paul Rodden; Lyndon Frearson; Bert Herteleer; Dario Bertani; David Moser. Analysis of Photovoltaic Performance Loss Rates of Six Module Types in Five Geographical Locations. IEEE Journal of Photovoltaics 2019, 9, 1091 -1096.

AMA Style

Philip Ingenhoven, Giorgio Belluardo, George Makrides, George E. Georghiou, Paul Rodden, Lyndon Frearson, Bert Herteleer, Dario Bertani, David Moser. Analysis of Photovoltaic Performance Loss Rates of Six Module Types in Five Geographical Locations. IEEE Journal of Photovoltaics. 2019; 9 (4):1091-1096.

Chicago/Turabian Style

Philip Ingenhoven; Giorgio Belluardo; George Makrides; George E. Georghiou; Paul Rodden; Lyndon Frearson; Bert Herteleer; Dario Bertani; David Moser. 2019. "Analysis of Photovoltaic Performance Loss Rates of Six Module Types in Five Geographical Locations." IEEE Journal of Photovoltaics 9, no. 4: 1091-1096.

Journal article
Published: 30 April 2019 in IEEE Journal of Photovoltaics
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Potential induced degradation (PID) is still a serious threat for the photovoltaic (PV) industry and it is expected to aggravate due to the tendency to increase the operating voltage of PV systems. Therefore, a method which can detect PID at an infant stage is necessary in order to increase the reliability of PV systems and preserve their lifetime. This paper provides a pathway (proof of concept) for the early and reliable detection of PID, by using the forward dc resistance (FDCR) of a PV cell since it is a parameter, which is affected by the cell's shunt resistance (Rsh), which in turn is heavily affected by PID before any significant power loss occurs, and could act as a PID detection mechanism. The paper presents simulation results, which examine at which forward bias conditions the FDCR has to be measured for the purpose of using it as a PID detection means at an early stage (<1% power loss). The simulation examined the FDCR variation with shunt resistance, reverse dark saturation current (I0), and ideality factor (n). Furthermore, an experiment was performed to verify the simulation results, demonstrating detection before 2% power loss occurs.

ACS Style

Michalis Florides; George Makrides; George E. Georghiou. Early Detection of Potential Induced Degradation by Measurement of the Forward DC Resistance in Crystalline PV Cells. IEEE Journal of Photovoltaics 2019, 9, 942 -950.

AMA Style

Michalis Florides, George Makrides, George E. Georghiou. Early Detection of Potential Induced Degradation by Measurement of the Forward DC Resistance in Crystalline PV Cells. IEEE Journal of Photovoltaics. 2019; 9 (4):942-950.

Chicago/Turabian Style

Michalis Florides; George Makrides; George E. Georghiou. 2019. "Early Detection of Potential Induced Degradation by Measurement of the Forward DC Resistance in Crystalline PV Cells." IEEE Journal of Photovoltaics 9, no. 4: 942-950.

Journal article
Published: 16 December 2018 in Energies
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New energy solutions are needed to decrease the currently high electricity costs from conventional electricity-only central power plants in Cyprus. A promising solution is a decentralized, hybrid photovoltaic-solid oxide fuel cell (PV-SOFC) system. In this study a decentralized, hybrid PV-SOFC system is investigated as a solution for useful energy supply to a commercial building (small hotel). An actual load profile and solar/weather data are fed to the system model to determine the thermoeconomic characteristics of the proposed system. The maximum power outputs for the PV and SOFC subsystems are 70 and 152 kWe, respectively. The average net electrical and total efficiencies for the SOFC subsystem are 0.303 and 0.700, respectively. Maximum net electrical and total efficiencies reach up to 0.375 and 0.756, respectively. The lifecycle cost for the system is 1.24 million USD, with a unit cost of electricity at 0.1057 USD/kWh. In comparison to the conventional case, the unit cost of electricity is about 50% lower, while the reduction in CO2 emissions is about 36%. The proposed system is capable of power and heat generation at a lower cost, owing to the recent progress in both PV and fuel cell technologies, namely longer lifetime and lower specific cost.

ACS Style

Alexandros Arsalis; George Georghiou. A Decentralized, Hybrid Photovoltaic-Solid Oxide Fuel Cell System for Application to a Commercial Building. Energies 2018, 11, 3512 .

AMA Style

Alexandros Arsalis, George Georghiou. A Decentralized, Hybrid Photovoltaic-Solid Oxide Fuel Cell System for Application to a Commercial Building. Energies. 2018; 11 (12):3512.

Chicago/Turabian Style

Alexandros Arsalis; George Georghiou. 2018. "A Decentralized, Hybrid Photovoltaic-Solid Oxide Fuel Cell System for Application to a Commercial Building." Energies 11, no. 12: 3512.

Journal article
Published: 01 October 2018 in Renewable Energy
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In this study a completely-autonomous, zero-emission photovoltaic (PV)-based system is modeled for residential application. Apart from the PV subsystem, an electrolyzer-hydrogen storage-fuel cell subsystem is integrated to the system to fully fulfill a varying load profile throughout the year. The fuel cell and electrolyzer components are based on proton exchange membrane technology. The model allows quantification of energy and power flows, such as power input from the PV subsystem, conversion of electricity to hydrogen, and re-production of electricity. The system components are sized to satisfy demand, which is varied through a case study conducted to investigate system performance at different capacities. The economic performance of the proposed system is assessed with a detailed cost model. The proposed system results in a unit cost of electricity at 0.216 EUR/kWh for a system capacity of 100 households, which is moderately higher than the conventional cost of electricity in Cyprus. A parametric study including those economic parameters with a high degree of uncertainty is conducted to investigate the sensitivity and future potential of the system. The results show that the unit cost of electricity for the proposed system can be reduced below the current cost of electricity in Cyprus, making the system competitive, if electrolyzer/fuel cell lifetime is increased, while the specific costs of the electrolyzer and the PV are reduced.

ACS Style

Alexandros Arsalis; Andreas N. Alexandrou; George E. Georghiou. Thermoeconomic modeling of a completely autonomous, zero-emission photovoltaic system with hydrogen storage for residential applications. Renewable Energy 2018, 126, 354 -369.

AMA Style

Alexandros Arsalis, Andreas N. Alexandrou, George E. Georghiou. Thermoeconomic modeling of a completely autonomous, zero-emission photovoltaic system with hydrogen storage for residential applications. Renewable Energy. 2018; 126 ():354-369.

Chicago/Turabian Style

Alexandros Arsalis; Andreas N. Alexandrou; George E. Georghiou. 2018. "Thermoeconomic modeling of a completely autonomous, zero-emission photovoltaic system with hydrogen storage for residential applications." Renewable Energy 126, no. : 354-369.

Accepted manuscript
Published: 04 September 2018 in Plasma Sources Science and Technology
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Atmospheric pressure plasma jet (APPJ) can be generated in capillary tubes flowing with pure helium and with admixtures of oxygen into the pure helium. The jet exiting the tube can be used for a variety of applications through surface interaction. In this study, a two-dimensional axi-symmetric model has been developed to provide insight into the evolution of capillary helium plasma jet with and without the presence of oxygen admixtures and its interaction with a dielectric surface placed normal to the jet axis. The model considers the gas mixing of helium and ambient air and the analytical chemistry between helium, nitrogen and oxygen species. Experiments were performed in similar conditions as the simulations in order to get qualitative agreement between them. The numerical and experimental results show that the evolution of the helium plasma jet is highly affected by the introduction of oxygen admixtures. In particular, it was observed that the addition of oxygen admixtures in the helium gas promotes plasma bullet propagation on the axis of symmetry of the tube (instead off axis propagation for the pure helium plasma jet). On the other hand, the presence of the dielectric surface (the slab placed in front of the tube exit) forces the plasma bullet to spread radially. Furthermore, the plasma bullet speed decreases when the helium plasma jet is operated in the presence of oxygen admixtures. The numerical results also showed that He/O2 plasma jets induced much higher electric fields on the dielectric surface in comparison to the pure helium plasma jet.

ACS Style

Constantinos Lazarou; Charalambos Anastassiou; Ionut Topala; Alina Silvia Chiper; Ilarion Mihaila; Valentin Pohoata; George Elia Georghiou. Numerical simulation of capillary helium and helium−oxygen atmospheric pressure plasma jets: propagation dynamics and interaction with dielectric. Plasma Sources Science and Technology 2018, 27, 105007 .

AMA Style

Constantinos Lazarou, Charalambos Anastassiou, Ionut Topala, Alina Silvia Chiper, Ilarion Mihaila, Valentin Pohoata, George Elia Georghiou. Numerical simulation of capillary helium and helium−oxygen atmospheric pressure plasma jets: propagation dynamics and interaction with dielectric. Plasma Sources Science and Technology. 2018; 27 (10):105007.

Chicago/Turabian Style

Constantinos Lazarou; Charalambos Anastassiou; Ionut Topala; Alina Silvia Chiper; Ilarion Mihaila; Valentin Pohoata; George Elia Georghiou. 2018. "Numerical simulation of capillary helium and helium−oxygen atmospheric pressure plasma jets: propagation dynamics and interaction with dielectric." Plasma Sources Science and Technology 27, no. 10: 105007.

Conference paper
Published: 01 June 2018 in 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC)
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Accurate day-ahead photovoltaic (PV) power output forecasting techniques are important both for grid and plant operators. In this work, a machine learning model was implemented based on gradient boosting machine (GBM), for accurate PV production forecasting. The accuracy of the developed model was experimentally verified on a test system installed in Cyprus. The basic methodology followed was to train and optimize different developed GBM PV production day-ahead forecasting models with acquired data-sets and construct relationships between the input and output features. The final optimal developed GBM model included 7 inputs, 1000 trees with 10 minimum observations on each node and a shrinkage level set to 0.001. The prediction results obtained when the test set was applied to the model, demonstrated that the nRMSE was 0.80 %, while some days were exhibiting accuracies close to 0.50 %. Finally, the forecasting performance assessment results obtained when the test set and numerical weather prediction (NWP) data were applied to the optimal designed model, showed a nRMSE of 7.9 % with 55 % of the test set days exhibiting nRMSE below 5 %. The error relative to the capacity of the system for all points during clear sky conditions was in most cases less than 0.1 W/W p .

ACS Style

Spyros Theocharides; Venizelos Venizelou; George Makrides; George E. Georghiou. Day-ahead Forecasting of Solar Power Output from Photovoltaic Systems Utilising Gradient Boosting Machines. 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC) 2018, 2371 -2375.

AMA Style

Spyros Theocharides, Venizelos Venizelou, George Makrides, George E. Georghiou. Day-ahead Forecasting of Solar Power Output from Photovoltaic Systems Utilising Gradient Boosting Machines. 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC). 2018; ():2371-2375.

Chicago/Turabian Style

Spyros Theocharides; Venizelos Venizelou; George Makrides; George E. Georghiou. 2018. "Day-ahead Forecasting of Solar Power Output from Photovoltaic Systems Utilising Gradient Boosting Machines." 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC) , no. : 2371-2375.