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Wyszukujesz frazę "Bykuć, Sebastian" wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
Testing of a price-based system for power balancing on real-life HVAC installation in real life
Autorzy:
Radziszewska, Weronika
Bugaj, Marcin A.
Łuniewski, Mirosław
Hoogsteen, Gerwin
Chaja, Patryk
Bykuć, Sebastian
Powiązania:
https://bibliotekanauki.pl/articles/2173657.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
distributed management
heat pump
HVAC
power management
water loop
zarządzanie rozproszone
pompa ciepła
zarządzanie energią
pętla wodna
Opis:
HVAC systems use a substantial part of the whole energy usage of buildings. The optimizing of their operation can greatly affect the power use of a building, making them an interesting subject when trying to save energy. However, this should not affect the comfort of the people inside. Many approaches aim to optimize the operation of the heating and cooling system; in this paper, we present an approach to steer the heat pumps to reduce energy usage while aiming to maintain a certain level of comfort. For this purpose, we employ a market-based distributed method for power-balancing. To maintain the comfort level, the market-based distributed system assigns each device a cost-curve, parametrized with the current temperature of the room. This allows the cost to reflect the urgency of the HVAC operation. This approach was tested in a real-world environment: we use 10 heat pumps responsible for temperature control in 10 comparable-sized rooms. The test was performed for 3 months in summer. We limited the total peak power, and the algorithm balanced the consumption of the heat pumps with the available supply. The experiments showed that the system successfully managed to operate within the limit (lowering peak usage), and - to a certain point – reduce the cost without significantly deteriorating the working conditions of the occupants of the rooms. This test allowed us to estimate the minimal peak power requirement for the tested set-up that will still keep the room temperatures in or close to comfortable levels. The experiments show that a fully distributed market-based approach with parametrized cost functions can be used to limit peak usage while maintaining temperatures.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 2; art. no. e140690
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
Autorzy:
Krzywanski, Jarosław
Sztekler, Karol
Bugaj, Marcin
Kalawa, Wojciech
Grabowska, Karolina
Chaja, Patryk Robert
Sosnowski, Marcin
Nowak, Wojciech
Mika, Łukasz
Bykuć, Sebastian
Powiązania:
https://bibliotekanauki.pl/articles/2173577.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
adsorption heat pump
polygeneration
cooling capacity
low grade thermal energy
artificial neural networks
soft computing
absorpcyjna pompa ciepła
poligeneracja
wydajność chłodnicza
energia cieplna niskiej jakości
sztuczne sieci neuronowe
przetwarzanie miękkie
Opis:
Adsorption cooling and desalination technologies have recently received more attention. Adsorption chillers, using eco-friendly refrigerants, provide promising abilities for low-grade waste heat recovery and utilization, especially renewable and waste heat of the near ambient temperature. However, due to the low coefficient of performance (COP) and cooling capacity (CC) of the chillers, they have not been widely commercialized. Although operating in combined heating and cooling (HC) systems, adsorption chillers allow more efficient conversion and management of low-grade sources of thermal energy, their operation is still not sufficiently recognized, and the improvement of their performance is still a challenging task. The paper introduces an artificial intelligence (AI) approach for the optimization study of a two-bed adsorption chiller operating in an existing combined HC system, driven by low-temperature heat from cogeneration. Artificial neural networks are employed to develop a model that allows estimating the behavior of the chiller. Two crucial energy efficiency and performance indicators of the adsorption chiller, i.e., CC and the COP, are examined during the study for different operating sceneries and a wide range of operating conditions. Thus this work provides useful guidance for the operating conditions of the adsorption chiller integrated into the HC system. For the considered range of input parameters, the highest CC and COP are equal to 12.7 and 0.65 kW, respectively. The developed model, based on the neurocomputing approach, constitutes an easy-to-use and powerful optimization tool for the adsorption chiller operating in the complex HC system.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e137054
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
Autorzy:
Krzywanski, Jarosław
Sztekler, Karol
Bugaj, Marcin
Kalawa, Wojciech
Grabowska, Karolina
Chaja, Patryk Robert
Sosnowski, Marcin
Nowak, Wojciech
Mika, Łukasz
Bykuć, Sebastian
Powiązania:
https://bibliotekanauki.pl/articles/2128167.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
adsorption heat pump
polygeneration
cooling capacity
low grade thermal energy
artificial neural networks
soft computing
absorpcyjna pompa ciepła
poligeneracja
wydajność chłodnicza
energia cieplna niskiej jakości
sztuczne sieci neuronowe
przetwarzanie miękkie
Opis:
Adsorption cooling and desalination technologies have recently received more attention. Adsorption chillers, using eco-friendly refrigerants, provide promising abilities for low-grade waste heat recovery and utilization, especially renewable and waste heat of the near ambient temperature. However, due to the low coefficient of performance (COP) and cooling capacity (CC) of the chillers, they have not been widely commercialized. Although operating in combined heating and cooling (HC) systems, adsorption chillers allow more efficient conversion and management of low-grade sources of thermal energy, their operation is still not sufficiently recognized, and the improvement of their performance is still a challenging task. The paper introduces an artificial intelligence (AI) approach for the optimization study of a two-bed adsorption chiller operating in an existing combined HC system, driven by low-temperature heat from cogeneration. Artificial neural networks are employed to develop a model that allows estimating the behavior of the chiller. Two crucial energy efficiency and performance indicators of the adsorption chiller, i.e., CC and the COP, are examined during the study for different operating sceneries and a wide range of operating conditions. Thus this work provides useful guidance for the operating conditions of the adsorption chiller integrated into the HC system. For the considered range of input parameters, the highest CC and COP are equal to 12.7 and 0.65 kW, respectively. The developed model, based on the neurocomputing approach, constitutes an easy-to-use and powerful optimization tool for the adsorption chiller operating in the complex HC system.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e137054, 1--11
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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