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Wyszukujesz frazę "bilevel optimization" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Optimized fractional low and highpass filters of (1 + α) order on FPAA
Autorzy:
Singh, N.
Mehta, U.
Kothari, K.
Cirrincione, M.
Tematy:
fractional-order filter
FPAA
realization
robustness
bilevel optimization
Pokaż więcej
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:
https://bibliotekanauki.pl/articles/200342.pdf  Link otwiera się w nowym oknie
Opis:
This work proposes an optimum design and implementation of fractional-order Butterworth filter of order (1 + α), with the help of analog reconfigurable field-programmable analog array (FPAA). The designed filter coefficients are obtained after dual constraint optimization to balance the tradeoffs between magnitude error and stability margin together. The resulting filter ensures better robustness with less sensitivity to parameter variation and minimum least square error (LSE) in magnitude responses, passband and stopband errors as well as a better –3 dB normalized frequency approximation at 1 rad/s and a stability margin. Finally, experimental results have shown both lowpass and highpass fractional step values. The FPAA-configured outputs represent the possibility to implement the real-time fractional filter behavior with close approximation to the theoretical design.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified Gray Wolf Algorithm
Autorzy:
Tian, Jingjing
Qian, Yu
Zhao, Feng
Mo, Shenglin
Xiao, Huaxuan
Zhu, Xiaotong
Liu, Guangdi
Tematy:
bilevel optimization
grey wolf optimization algorithm
multi-mode
peak shaving
valley-filling
source-network-load-storage
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Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Powiązania:
https://bibliotekanauki.pl/articles/59111824.pdf  Link otwiera się w nowym oknie
Opis:
Aiming to address power consumption issues of various equipment in metro stations and the inefficiency of peak shaving and valley filling in the power supply system, this study presents an economic optimization scheduling method for the multi-modal “source-network-load-storage” system in metro stations. The proposed method, called the Improved Gray Wolf Optimization Algorithm (IGWO), utilizes objective evaluation criteria to achieve economic optimization. First, construct a mathematical model of the “source network-load-storage” joint system with the metro station at its core. This model should consider the electricity consumption within the station. Secondly, a two-layer optimal scheduling model is established, with the upper model aiming to optimize peak elimination and valley filling, and the lower model aiming to minimize electricity consumption costs within a scheduling cycle. Finally, this paper introduces the IGWO optimization approach, which utilizes meta-models and the Improved Gray Wolf Optimization Algorithm to address the nonlinearity and computational complexity of the two-layer model. The analysis shows that the proposed model and algorithm can improve the solution speed and minimize the cost of electricity used by about 5.5% to 8.7% on the one hand, and on the other hand, it improves the solution accuracy, and at the same time effectively realizes the peak shaving and valley filling, which provides a proof of the effectiveness and feasibility of the new method.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimal configuration of energy storage system capacity in traction power supply system considering photovoltaic consumption
Autorzy:
Zhang, Wei
Chen, Xiaoqiang
Wang, Ying
Tematy:
bilevel optimization
capacity optimization configuration
energy storage system
photovoltaic
railway power conditioner
traction power supply system
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Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Powiązania:
https://bibliotekanauki.pl/articles/59111843.pdf  Link otwiera się w nowym oknie
Opis:
In order to achieve energy savings and promote on-site integration of photovoltaic energy in electrified railways, a topology structure is proposed for the integration of photovoltaic (PV) and the energy storage system (ESS) into the traction power supply system (TPSS) based on a railway power conditioner (RPC). This paper analyzes the composition and operation principles of this structure. To assess the economic benefits brought by the integration of photovoltaic and energy storage systems, a bilevel optimization model is established, with the objectives of optimizing energy storage capacity configuration and photovoltaic energy integration. The KKT (Karush–Kuhn–Tucker) method is employed to transform the model into a single-layer mixed-integer linear programming model, which is then solved using the CPLEX solver in MATLAB. The research findings indicate that, with the configuration of the ESS, the optimal PV consumption rate achieved is 96.8749%. Compared to a 100% PV consumption rate, the ESS capacity configuration is reduced by 13.14%, and the overall operational cost of the TPSS is at its lowest. The study suggests that the proposed bilevel optimization algorithm can more effectively consider PV consumption, leading to enhanced economic performance of the TPSS operation.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robust bi-level optimization for an opportunistic supply chain network design problem in an uncertain and risky environment
Autorzy:
Golpîra, H.
Tematy:
supply chain management
production-distribution planning
conditional value at risk
bilevel programming
robust optimization
KKT conditions
zarządzanie łańcuchem dostaw
planowanie produkcji
planowanie dystrybucji
optymalizacja
warunki KKT
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Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/406601.pdf  Link otwiera się w nowym oknie
Opis:
This paper introduces the problem of designing a single-product supply chain network in an agile manufacturing setting under a vendor managed inventory (VMI) strategy to seize a new market oppor-tunity. The problem addresses the level of risk aversion of the retailer when dealing with the uncertainty of market related information through a conditional value at risk (CVaR) approach. This approach leads to a bilevel programming problem. The Karush–Kuhn–Tucker (KKT) conditions are employed to trans-form the model into a single-level, mixed-integer linear programming problem by considering some relaxations. Since realizations of imprecisely known parameters are the only information available, a data-driven approach is employed as a suitable, more practical, methodology of avoiding distribu-tional assumptions. Finally, the effectiveness of the proposed model is demonstrated through a numer-ical example
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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