Now showing items 21-40 of 2897

    • Article  Open Access

      A comprehensive review of unmanned aerial vehicle-based approaches to support photovoltaic plant diagnosis 

      Michail, Anna; Livera, Andreas; Tziolis, Georgios; Carús Candás, Juan Luis; Fernandez, Alberto; Antuña Yudego, Elena; Fernández Martínez, Diego; Antonopoulos, Angelos; Tripolitsiotis, Achilleas; Partsinevelos, Panagiotis; Koutroulis, Eftichis; Georghiou, George E. (Elsevier, 2024-01-03)
      Accurate photovoltaic (PV) diagnosis is of paramount importance for reducing investment risk and increasing the bankability of the PV technology. The application of fault diagnostic solutions and troubleshooting on operating ...
    • Article  

      Electricity Day-Ahead Market Conditions and Their Effect on the Different Supervised Algorithms for Market Price Forecasting 

      Loizidis, Stylianos; Konstantinidis, Georgios; Theocharides, Spyros; Kyprianou, Andreas; Georghiou, George E. (MDPI, 2023)
      Participants in deregulated electricity markets face risks from price volatility due to various factors, including fuel prices, renewable energy production, electricity demand, and crises such as COVID-19 and energy-related ...
    • Conference Object  

      Charakterisierung und Degradation von Perowskit Mini-modulen 

      Ebner, Rita; Ujvari, Gusztav; Mittal, Ankit; Hadjipanayi, Maria; Paraskeva, Vasiliki S.; Georghiou, George E.; Hadipour, Afshin; Aguirre, Aranzazu; Aernouts, Tom; Fontanot, Tommaso; Pechmann, Stefan; Christiansen, Silke; Zardetto, Valerio (2023)
      Organic-inorganic hybrid metal halide perovskites are poised to revolutionize the next generation of photovoltaics with their exceptional optoelectronic properties compatibility with low-cost and large-scale fabrication ...
    • Conference Object  

      Learning curves from long-term outdoor testing and indoor optoelectronic characterization of perovskite mini-modules 

      Paraskeva, Vasiliki S.; Hadjipanayi, Maria; Norton, Matthew; Aguirre, Aranzazu; Krishna, Anurag; Aernouts, Tom; Penchmann, Sabrina; Christiansen, Silke; Sergides, Marios; Othonos, Andreas S.; Ebner, Rita; Georghiou, George E. (2023)
      Improving the performance of perovskite devices is key to increasing their competitiveness against conventional sources of energy. Several perovskite and perovskite on Silicon tandems were extensively investigated both ...
    • Conference Object  

      Technology design and operation optimisation of integrated electricity- heat-cold-hydrogen systems in buildings 

      Olympios, Andreas V.; Arsalis, Alexandros; Kourougianni, Fanourios; Pantaleo, Antonio M.; Papanastasiou, Panos; Makrides, Christos N.; Georghiou, George E. (2023)
      In this work, a comprehensive design and operation optimisation framework is adopted to support short- and long-term technology investment and operation decisions for integrated energy generation, conversion and storage ...
    • Conference Object  

      Integration of Green Hydrogen and Heating/Cooling Subsystems to a 40 kWp Photovoltaic-60 kWh Battery Energy Storage System Living Lab Nanogrid 

      Arsalis, Alexandros; Kourougianni, Fanourios; Olympios, Andreas V.; Yiasoumas, Georgios; Papanastasiou, Panos; Georghiou, George E. (2023)
      Decentralized energy systems can contribute to the maximization of the energy share of renewable energy, especially when such systems are integrated with effective and practical energy storage and other energy efficient ...
    • Conference Object  

      Correlative microscopy and spectroscopy of perovskite mini-modules: degradation analysis 

      Paraskeva, Vasiliki; Pechmann, Sabrina; Fontanot, Tommaso; Aguirre, Aranzazu; Aernouts, Tom; Peraticos, Elias; Hadjipanayi, Maria; Sergides, Marios; Othonos, Andreas; Christiansen, Silke; Georghiou, George E. (2023)
      Perovskite materials have excellent prospects for semiconducting applications due to their desirable photoelectric properties. The morphology and the structure of the light absorption layer are crucially important for the ...
    • Article  

      Characterizing soiling losses for photovoltaic systems in dry climates: a case study in Cyprus 

      Lopez-Lorente, Javier; Polo, Jesús; Martín-Chivelet, Nuria; Norton, Matthew; Livera, Andreas; Makrides, George; Georghiou, George E. (Elsevier, 2023)
      Ensuring optimal performance of solar photovoltaic (PV) systems requires the extensive assessment and understanding of losses of different origin that affect these installations. Soiling is a key loss factor influencing ...
    • Conference Object  

      Reducing the photovoltaic operation and maintenance costs through an autonomous control operation center 

      Livera, Andreas; Fernández-Solas, Álvaro; Bessa, Joao G.; Montes-Romero, Jesús; Fernández, Eduardo F.; Papaeconomou, Vassilis; Georghiou, George E. (IEEE, 2023)
      An advanced control operation center to enable corrective, preventive and predictive maintenance, while also ensuring optimal photovoltaic (PV) plant performance was developed in this work. The developed software solution ...
    • Conference Object  

      Extreme supervised algorithm for day ahead market price forecasting 

      Loizidis, Stylianos; Theocharides, Spyros; Venizelou, Venizelos; Evagorou, Demetres; Makrides, George; Kyprianou, Andreas; Georghiou, George E. (IEEE, 2023)
      Deregulation of electricity markets has ushered in a new era of heightened competition, allowing for the inclusion of fresh market entrants. However, market participation bears challenges related the extremely high volatility ...
    • Conference Object  

      Outdoor study of Photovoltaic Mini-Modules with different perovskite compositions 

      Paraskeva, Vasiliki; Hadjipanayi, Maria; Norton, Matthew; Aguirre, Aranzazu; Krishna, Anurag; Ebner, Rita; Fontanot, Tommaso; Pechmann, Sabrina; Christiansen, Silke; Georghiou, George E. (IEEE, 2023)
      A long-term outdoor study of photovoltaic mini-modules with different perovskite compositions was undertaken to detect differences in their long-term performance that could be attributed to their composition. Diurnal ...
    • Conference Object  

      Advanced health-state data analytic workflow for utility-scale photovoltaic power plants 

      Montes-Romero, Jesus; Pikolos, Loucas; Makrides, Andreas; Heinzle, Nino; Makrides, George; Sutterlueti, Juergen; Ransome, Steve; Georghiou, George E. (IEEE, 2023)
      This work aims to present data analytic advances and next-generation workflows for utility-scale photovoltaic (PV) power plant monitoring. The proposed health-state architecture comprises of an integrated and scalable ...
    • Article  

      Evaluating the techno-economic effect of pricing and consumption parameters on the power-to-energy ratio for sizing photovoltaic-battery systems: an assessment of prosumers in the Mediterranean Area 

      Chatzigeorgiou, Nikolas G.; Theocharides, Spyros; Makrides, George; Georghiou, George E. (MDPI, 2023)
      The momentous deployment of photovoltaic (PV) installations in modern times converted schemes utilised to support behind-the-meter systems to compensation mechanisms promoting self-consumption for all prosumer types. ...
    • Article  

      Estimating the performance loss rate of photovoltaic systems using time series change point analysis 

      Livera, Andreas; Tziolis, Georgios; Theristis, Marios; Stein, Joshua S.; Georghiou, George E. (MDPI, 2023)
      The accurate quantification of the performance loss rate of photovoltaic systems is critical for project economics. Following the current research activities in the photovoltaic performance and reliability field, this work ...
    • Article  Open Access

      Estimating the Performance Loss Rate of Photovoltaic Systems Using Time Series Change Point Analysis 

      Livera, Andreas; Georghiou, George E.; Tziolis, Georgios; Stein, Joshua S.; Theristis, Marios (MDPI, 2023-04-26)
      The accurate quantification of the performance loss rate of photovoltaic systems is critical for project economics. Following the current research activities in the photovoltaic performance and reliability field, this ...
    • Article  

      ArrayFlex: A Systolic Array Architecture with Configurable Transparent Pipelining 

      Peltekis, Christodoulos; Filippas, Dionysios; Dimitrakopoulos, Giorgos; Nicopoulos, Chrysostomos; Pnevmatikatos, Dionisios (IEEE, 2023-06-02)
      Convolutional Neural Networks (CNNs) are the state-of-the-art solution for many deep learning applications. For maximum scalability, their computation should combine high performance and energy efficiency. In practice, the ...
    • Article  

      Low-Power Data Streaming in Systolic Arrays with Bus-Invert Coding and Zero-Value Clock Gating 

      Peltekis, Christodoulos; Filippas, Dionysios; Dimitrakopoulos, Giorgos; Nicopoulos, Chrysostomos (IEEE, 2023-07-17)
      Systolic Array (SA) architectures are well suited for accelerating matrix multiplications through the use of a pipelined array of Processing Elements (PEs) communicating with local connections and pre-orchestrated data ...
    • Article  

      Multi-Armed Bandits for Autonomous Test Application in RISC-V Processor Verification 

      Dimitrakopoulos, Giorgos; Kallitsounakis, E.; Takakis, Zacharias; Stefanidis, Apostolos; Nicopoulos, Chrysostomos (IEEE, 2023-07-17)
      Multi-armed bandit problems have recently received a great deal of attention, because they adequately formalize so called exploration-exploitation trade-offs arising in several relevant applications of recommendation ...
    • Article  

      Exploiting data encoding and reordering for low-power streaming in systolic arrays 

      Peltekis, Christodoulos; Filippas, Dionysios; Dimitrakopoulos, Giorgos; Nicopoulos, Chrysostomos (Elsevier, 2023-10-03)
      Systolic Array (SA) architectures are well-suited for accelerating matrix multiplications through the use of a pipelined array of Processing Elements (PEs) communicating with local connections and pre-orchestrated data ...
    • Article  

      IndexMAC: A Custom RISC-V Vector Instruction to Accelerate Structured-Sparse Matrix Multiplications 

      Titopoulos, Vasileios; Alexandridis, Kosmas; Peltekis, Christodoulos; Nicopoulos, Chrysostomos; Dimitrakopoulos, Giorgos (IEEE, 2024-03)
      Structured sparsity has been proposed as an efficient way to prune the complexity of modern Machine Learning (ML) applications and to simplify the handling of sparse data in hardware. The acceleration of ML models - for ...