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Access type: UnknownSubject: search.filters.subject.Firefly algorithm

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    Optimum Operation and Cost Scenarios of a Hybrid Wind/PV/Battery in a Radial Network using Genetic Algorithm and Particle Swarm Optimization
    (2022-01-01)
    Abdelwareth, Mohamed Els S.
    ;
    Riawan, Dedet Candra
    ;
    Chompoo-Inwai, Chow
    Hybrid generation systems took the attention of many researchers searching for the best energy source that can be optimum, reliable, and scalable instead of dependency on the traditional fossil fuels sources; researchers are developing Artificial Intelligence (AI) algorithms to optimize those systems. This paper will study the optimum generating power from a Wind turbine, PV, and Battery linked to the radial network in Tomia Island, considering the optimum cost using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).
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    Warpage reduction through optimized process parameters and annealed process of injection-molded plastic parts
    (2018-10-01)
    Sudsawat, Supattarachai
    ;
    Sriseubsai, Wipoo
    The objective of this paper is to achieve the minimization of warpage for an injection molded part. The techniques that were implemented to minimize the warpage are the design of experiment (DOE), response surface methodology (RSM), firefly algorithm (FA), and annealing treatment. The packing time, cooling time, and melt temperature were shown to be significant parameters and FA was employed to seek these suitable values by experimental tests based on simulation software Moldex3D and injection machine. Analysis of variance (ANOVA) was used to validate experiments. Annealing treatment process was then applied to reduce more warpage phenomenon; the results showed that warpage phenomenon decreased dramatically compared with popular optimized parameter methodology. Moreover, the residual stress which was obtained by using photoelasticity showed that it has a direct relationship with warpage reduction. Therefore, the best solution of warpage mitigation can be solved by popular optimum process parameters and also annealing treatment.
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    Robust power oscillation damper design for DFIG-based wind turbine based on specified structure mixed H2/H∞ control
    (2014-01-01)
    Surinkaew, Tossaporn
    ;
    Ngamroo, Issarachai
    As the integration of a doubly fed induction generator (DFIG)-based wind power generation into power systems tends to increase significantly, the contribution of DFIG wind turbine is highly expected. Since the active and reactive power outputs of DFIG can be independently modulated, the stabilizing effect of DFIG on the inter-area power system oscillation is a challenging issue. This paper proposes a new robust control design of power oscillation damper (POD) for a DFIG-based wind turbine using a specified structure mixed H<inf>2</inf>/H<inf>∞</inf> control. The POD structure is a practical 2nd-order lead-lag compensator with single input. Normally, H<inf>∞</inf> control mainly enforces the closed-loop stability while noise attenuation or regulation against random disturbances is expressed in H<inf>2</inf> control. As a result, the mixed H<inf>2</inf>/H<inf>∞</inf> control gives a powerful multi-objective control design so that both closed-loop stability and performance of designed controller can be guaranteed. Here, the linear matrix inequality is applied to formulate the optimization problem of POD based on a mixed H<inf>2</inf>/H<inf>∞</inf> control. The POD parameters are optimized so that the performance and robustness of the POD against system disturbances and uncertainties are maximal. The firefly algorithm is automatically applied to solve the optimization problem. Simulation study in a two-area four-machine interconnected power system shows that the DFIG with robust POD is superior to conventional POD in terms of stabilizing effect as well as robustness against various power generating and loading conditions, unpredictable network structure, and random wind patterns. © 2013.