Yazar "Fujita, Goro" seçeneğine göre listele

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    Comparison of ABC and Genetic Algorithms on Economic Power Dispatch
    (Ieee, 2018) Afandi, A.N.; Fadlika, Irham; Sendari, Siti; Miyauchi, Hajime; Fujita, Goro; Tutkun, Nedim
    Recently, an economic evaluation of the power system becomes one of main issues in the power system management since the power production and power selling consider a financial aspect. The system should be operated in the lowest cost and cheaper fee for consumers. In particular, an environmental protection also becomes a major issue to penetrate the pollutant production of thermal power plants. To cover this issue, one of strategies is approached using a combined economic emission dispatch (CEED) considered an economic dispatch (ED) and an emission dispatch (EmD). In these studies, the CEED is optimized using Artificial Bee Colony Algorithm which is contrasted to Genetic Algorithm for comparing both performances. By considering both algorithms, results show that generated powers lead to the total cost and pollutant emission. The total minimum cost is performed in the optimal solution with different speeds. Combinations of ED and EmD also give difference implications.
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    Designed operating approach of economic dispatch for java bali power grid areas considered wind energy and pollutant emission optimized using thunderstorm algorithm based on forward cloud charge mechanism
    (Praise Worthy Prize S.r.l, 2018) Afandi, A.N.; Wibawa, A.P.; Padmantara, Syaad; Fujita, Goro; Triyana, W.; Sulistyorini, Yunis; Gao, X.Z.
    Due to ecological and economic benefits, variable energy sources are considered as a key factor in the world-wide energy security. The main operational problems associated with these sources are their variability and intermittency. Therefore, the inclusion in the fleet of the energy mix as the standard conventional generators is difficult. The wind energy is among the most dominant renewable source. Furthermore, this paper focuses on the inclusion of the wind energy impact on the Economic Dispatch (ED) optimization problem. The ED problem also considers the minimization of pollutant emissions from fossil-based sources. The Thunderstorm Algorithm (TA) is presented in this paper as a new intelligent computation technique for optimizing the Integrated Wind Energy and Pollutant Emissions into the Economic Dispatch (IWEPEED) problem. The algorithm is tested on the modified IEEE 62-bus system with wind energy integrated into the system as an area developing model of Java Bali Power Grid development. The results show the potential and success of the TA for solving the IWEPEED optimization problem with a short computational time and a fast convergence. © 2018 Praise Worthy Prize S.r.l. - All rights reserved.
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    Renewable Energy Inclusion on Economic Power Optimization using Thunderstorm Algorithm
    (Ieee, 2017) Afandi, A.N.; Sulistyorini, Yunis; Fujita, Goro; Khai, Nguyen Phuc; Tutkun, Nedim
    This paper presents an economic operation considered renewable energy which is optimized using thunderstorm algorithm. The problem is constrained by an emission standard and various technical limits implemented on the 62-bus system model. Simulations showed that the renewable energy inclusion penetrates to the unit commitment of generating units with strongly approach for the computational solution. This inclusion also affects to the individual power production in accordance to the fuel cost and pollutant discharge.