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A lot of autonomous power systems have been designed and operated with different power levels and with special requirements for climatic conditions, availability, operation/maintenance cost, fuel consumption, environmental impacts, etc. In this paper a novel design of an autonomous power system with photovoltaic panels and electrochemical batteries for a shoreline electrode station is analyzed. This station will be constructed on the small island of Stachtoroi for the new high voltage direct current (HVDC) link of Attica–Crete in Greece. The general guidelines of the International Council on Large Electric Systems (CIGRE) and of the International Electrotechnical Committee (IEC) for the power system of lighting and auxiliary loads for these HVDC stations are supplied from the medium voltage or the low voltage distribution network, whereas they do not take into account the criticality of this interconnection, which will practically be the unique power facility of Crete island. The significance of Crete power system interconnection demands an increased reliability level for the power sources, similar to military installations and hospital surgeries. In this research a basic electrical installation design methodology is presented. First, the autonomous photovoltaic power system with the energy storage system (ESS) consisting of electrochemical batteries is preliminary designed according to the relative bibliography. The station power and energy consumption are analytically determined taking into consideration the daily temperature variation annually. Afterwards, a techno-economic optimization process based on a sensitivity analysis is formed modifying the size/power of photovoltaic panels (PVs), the type and the energy capacity of the batteries taking into consideration the operation cycle of PVs—batteries charge and discharge and the battery ageing based on the relationship between battery cycles—the depth of discharge, the daily solar variation per month, the installation cost of PVs and batteries, the respective maintenance cost, etc., while the reliability criteria of expected loss of load power and of load energy are satisfied. Using the proposed methodology the respective results are significantly improved in comparison with the preliminary autonomous power system design or the connection with the distribution power system.
Panagiota M. Deligianni; George J. Tsekouras; Costas D. Tsirekis; Vassiliki T. Kontargyri; Fotis D. Kanellos; Panagiotis A. Kontaxis. Techno-Economic Optimization Analysis of an Autonomous Photovoltaic Power System for a Shoreline Electrode Station of HVDC Link: Case Study of an Electrode Station on the Small Island of Stachtoroi for the Attica–Crete Interconnection. Energies 2020, 13, 5550 .
AMA StylePanagiota M. Deligianni, George J. Tsekouras, Costas D. Tsirekis, Vassiliki T. Kontargyri, Fotis D. Kanellos, Panagiotis A. Kontaxis. Techno-Economic Optimization Analysis of an Autonomous Photovoltaic Power System for a Shoreline Electrode Station of HVDC Link: Case Study of an Electrode Station on the Small Island of Stachtoroi for the Attica–Crete Interconnection. Energies. 2020; 13 (21):5550.
Chicago/Turabian StylePanagiota M. Deligianni; George J. Tsekouras; Costas D. Tsirekis; Vassiliki T. Kontargyri; Fotis D. Kanellos; Panagiotis A. Kontaxis. 2020. "Techno-Economic Optimization Analysis of an Autonomous Photovoltaic Power System for a Shoreline Electrode Station of HVDC Link: Case Study of an Electrode Station on the Small Island of Stachtoroi for the Attica–Crete Interconnection." Energies 13, no. 21: 5550.
Daylight utilization significantly contributes to energy savings in office buildings. However, daylight integration requires careful design so as to include variations in daylight availability and maintain a balance between factors such as lighting quality and heat gain or loss. Designers with proper planning can not only improve the visual environment and create higher-quality spaces, but simultaneously minimize energy costs for buildings. The utilization of photosensors can exploit the benefits of daylighting by dimming the lighting system, so that no excessive luminous flux is produced, thus leading to energy savings as well as visual contentment. However, the human factor is crucial for the proper function of a lighting control system. Without its acceptance from the users, energy savings can be minimized or even negligible. The objective of this paper is to present a post-occupancy evaluation regarding occupant satisfaction and acceptance in relation to daylighting in offices equipped with automated daylight controls. In addition, the response of the users was compared with lighting measurements that were performed during the post-occupancy evaluation. Three case studies of office buildings with installed daylight-harvesting systems were examined. The age of the occupants was a crucial factor concerning their satisfaction in relation to the lighting levels. Aged users were more comfortable with lighting levels over 500lx, while young users were satisfied with 300lx. The impact of different control algorithms was outlined, with the integral reset algorithm performing poorly. The acceptance of the users for the closed loop systems maintained the expected energy savings of the daylight harvesting technique. Most of the occupants preferred to use daylight as a light source combined with artificial light but having the control to either override or switch it on and off at will. The results shown that a post-occupancy survey along with lighting measurements are significant for making an office environment a humancentric one.
Lambros T. Doulos; Aris Tsangrassoulis; Evangelos-Nikolaos Madias; Spyros Niavis; Antonios Kontadakis; Panagiotis A. Kontaxis; Vassiliki T. Kontargyri; Katerina Skalkou; Frangiskos Topalis; Evangelos Manolis; Maro Sinou; Stelios Zerefos. Examining the Impact of Daylighting and the Corresponding Lighting Controls to the Users of Office Buildings. Energies 2020, 13, 4024 .
AMA StyleLambros T. Doulos, Aris Tsangrassoulis, Evangelos-Nikolaos Madias, Spyros Niavis, Antonios Kontadakis, Panagiotis A. Kontaxis, Vassiliki T. Kontargyri, Katerina Skalkou, Frangiskos Topalis, Evangelos Manolis, Maro Sinou, Stelios Zerefos. Examining the Impact of Daylighting and the Corresponding Lighting Controls to the Users of Office Buildings. Energies. 2020; 13 (15):4024.
Chicago/Turabian StyleLambros T. Doulos; Aris Tsangrassoulis; Evangelos-Nikolaos Madias; Spyros Niavis; Antonios Kontadakis; Panagiotis A. Kontaxis; Vassiliki T. Kontargyri; Katerina Skalkou; Frangiskos Topalis; Evangelos Manolis; Maro Sinou; Stelios Zerefos. 2020. "Examining the Impact of Daylighting and the Corresponding Lighting Controls to the Users of Office Buildings." Energies 13, no. 15: 4024.
This paper discusses the classification of composite insulators in hydrophobicity classes, according to the spray method of IEC Standard 62073, using convolutional neural networks. By applying the spray method, about 4500 photos were collected and are available online, from all hydrophobicity classes using distilled water–ethyl alcohol as spraying solution. Convolutional neural networks were trained, validated and tested, in order to determine the hydrophobicity class of composite insulators and to eliminate the operator’s subjectivity, which is the main problem in this measurement. Various configuration setups of convolutional neural networks are applied and compared for their appropriateness in accurately classifying the composite insulators. The proposed methodology is a useful tool for the classification of composite insulators in hydrophobicity classes restricting the subjectivity of human judgment. The experiments showed this method gives almost 98% accuracy in this classification task. Therefore, the proposed methodology is helpful in maintaining of composite insulators.
Christos-Christodoulos A. Kokalis; Thanos Tasakos; Vassiliki T. Kontargyri; Giorgos Siolas; Ioannis F. Gonos. Hydrophobicity classification of composite insulators based on convolutional neural networks. Engineering Applications of Artificial Intelligence 2020, 91, 103613 .
AMA StyleChristos-Christodoulos A. Kokalis, Thanos Tasakos, Vassiliki T. Kontargyri, Giorgos Siolas, Ioannis F. Gonos. Hydrophobicity classification of composite insulators based on convolutional neural networks. Engineering Applications of Artificial Intelligence. 2020; 91 ():103613.
Chicago/Turabian StyleChristos-Christodoulos A. Kokalis; Thanos Tasakos; Vassiliki T. Kontargyri; Giorgos Siolas; Ioannis F. Gonos. 2020. "Hydrophobicity classification of composite insulators based on convolutional neural networks." Engineering Applications of Artificial Intelligence 91, no. : 103613.
The objective of this paper is to present a new methodology for predicting the critical flashover voltage of polluted insulators based on fuzzy logic. The prediction contains not only the estimated value, but also the respective confidence interval based on the re-sampling method. Various parameters, such as the number and the base width of the triangular membership functions used for the fuzzification process, etc., are assigned different values in order to optimize the estimation of the critical flashover voltage. Additionally, different methods for training the fuzzy system are applied and compared for their appropriateness in accurately predicting the critical flashover voltage.
G.E. Asimakopoulou; V.T. Kontargyri; G.J. Tsekouras; Ch. N. Elias; Ioannis Stathopulos. A fuzzy logic optimization methodology for the estimation of the critical flashover voltage on insulators. Electric Power Systems Research 2010, 81, 580 -588.
AMA StyleG.E. Asimakopoulou, V.T. Kontargyri, G.J. Tsekouras, Ch. N. Elias, Ioannis Stathopulos. A fuzzy logic optimization methodology for the estimation of the critical flashover voltage on insulators. Electric Power Systems Research. 2010; 81 (2):580-588.
Chicago/Turabian StyleG.E. Asimakopoulou; V.T. Kontargyri; G.J. Tsekouras; Ch. N. Elias; Ioannis Stathopulos. 2010. "A fuzzy logic optimization methodology for the estimation of the critical flashover voltage on insulators." Electric Power Systems Research 81, no. 2: 580-588.
The electric field and voltage distribution in glass insulators used to support high-voltage lines are very important for their performance. In this paper, a 150 kV glass insulator was simulated. A three-dimensional electric field analysis program has been used for the calculations. The electric field and potential distributions in the vicinity of the insulator was examined. Finally, in order to validate the accuracy of the method, the simulation results were compared to corresponding experimental results with satisfactory agreement. The small deviation between the simulation and the experimental results shows that the simulation methodology is a useful tool for the calculation of the potential in this problem.
V.T. Kontargyri; L.N. Plati; I.F. Gonos; I.A. Stathopulos. Measurement and simulation of the voltage distribution and the electric field on a glass insulator string. Measurement 2008, 41, 471 -480.
AMA StyleV.T. Kontargyri, L.N. Plati, I.F. Gonos, I.A. Stathopulos. Measurement and simulation of the voltage distribution and the electric field on a glass insulator string. Measurement. 2008; 41 (5):471-480.
Chicago/Turabian StyleV.T. Kontargyri; L.N. Plati; I.F. Gonos; I.A. Stathopulos. 2008. "Measurement and simulation of the voltage distribution and the electric field on a glass insulator string." Measurement 41, no. 5: 471-480.
This work attempts to apply an artificial neural network in order to estimate the critical flashover voltage on polluted insulators. The artificial neural network uses as input variables the following characteristics of the insulator: diameter, height, creepage distance, form factor and equivalent salt deposit density, and estimates the critical flashover voltage. The data used to train the network and test its performance is derived from experimental measurements and a mathematical model. Various cases have been studied and their results presented separately. Training and testing sets have been modified for each case.
V.T. Kontargyri; A.A. Gialketsi; G.J. Tsekouras; I.F. Gonos; I.A. Stathopulos. Design of an artificial neural network for the estimation of the flashover voltage on insulators. Electric Power Systems Research 2006, 77, 1532 -1540.
AMA StyleV.T. Kontargyri, A.A. Gialketsi, G.J. Tsekouras, I.F. Gonos, I.A. Stathopulos. Design of an artificial neural network for the estimation of the flashover voltage on insulators. Electric Power Systems Research. 2006; 77 (12):1532-1540.
Chicago/Turabian StyleV.T. Kontargyri; A.A. Gialketsi; G.J. Tsekouras; I.F. Gonos; I.A. Stathopulos. 2006. "Design of an artificial neural network for the estimation of the flashover voltage on insulators." Electric Power Systems Research 77, no. 12: 1532-1540.