Journal Articles - Engineering Technology - 2021

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Browsing Journal Articles - Engineering Technology - 2021 by Subject ""Cuckoo search algorithm"
  • Publication
    Optimal generation for wind-thermal power plant systems with multiple fuel sources
    ( 2021)
    Phan Nguyen Vinh
    ;
    Bach Hoang Dinh
    ;
    Van-Duc Phan
    ;
    Hung Duc Nguyen
    ;
    Thang Trung Nguyen
    In this paper, the combined wind and thermal power plant systems are operated optimally to reduce the total fossil fuel cost (TFFC) of all thermal power plants and supply enough power energy to loads. The objective of reducing TFFC is implemented by using antlion algorithm (ALA), particle swarm optimization (PSO) and Cuckoo search algorithm (CSA). The best method is then determined based on the obtained TFFC from the three methods as dealing with two study cases. Two systems with eleven units including one wind power plant (WPP) and ten thermal power plants are optimally operated. The two systems have the same characteristic of MFSs but the valve loading effects (VLEs) on thermal power plants are only considered in the second system. The comparisons of TFFC from the two systems indicate that CSA is more powerful than ALA and PSO. Furthermore, CSA is also superior to the two methods in terms of faster search process. Consequently, CSA is a powerful method for the problem of optimal generation for wind-thermal power plant systems with consideration of MFSs from thermal power plants.
  • Publication
    Optimal operation of wind-hydrothermal systems considering certainty and uncertainty of wind
    ( 2021)
    Ly Huu Pham
    ;
    Bach Hoang Dinh
    ;
    Thang Trung Nguyen
    ;
    Van-Duc Phan
    This paper proposes a High Performance Cuckoo Search Algorithm (HPCSA) for determining suitable operation parameters of the optimal wind-hydro-thermal system scheduling (OWHTSS) problem. The objective of the problem is to reach the lowest electricity generation cost of thermal power plants (TPPs) and wind power plants (WPPs) while exactly meeting all constraints of TPPs, WPPs and hydroelectric plants (HEPs). HPCSA is formed by applying improvements on the two main techniques of original Cuckoo Search Algorithm (CSA) to cover CSA’ drawbacks such as searching random solution spaces, always using two random solutions for getting a jumping step and suffering from slow convergence. HPCSA accompany with CSA, Adaptive CSA (ACSA), Snap-Drift CSA (SDCSA) and Water Cycle Algorithm (WCA) are run for solving four test systems in which the largest and complicated system is comprised of four TPPs, four HEPs and two WPPs with the uncertain wind feature. The result comparisons indicate that HPCSA is superior to applied and previous methods, and other modified versions of CSA in the literature in terms of better cost, higher stability, faster search ability and higher success rate. As a result, it leads to a conclusion that HPCSA is a strong metaheuristic algorithm for solving OWHTSS problem.