Novel phasianidae inspired peafowl (Pavo muticus/cristatus) optimization algorithm: Design, evaluation, and SOFC models parameter estimation

2022 ◽  
Vol 50 ◽  
pp. 101825
Author(s):  
Jingbo Wang ◽  
Bo Yang ◽  
Yijun Chen ◽  
Kaidi Zeng ◽  
Hao Zhang ◽  
...  
2017 ◽  
Vol 65 (4) ◽  
pp. 479-488 ◽  
Author(s):  
A. Boboń ◽  
A. Nocoń ◽  
S. Paszek ◽  
P. Pruski

AbstractThe paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.


This paper discusses various optimization algorithm design techniques. So, optimization techniques which are discussed in this paper are greedy method, dynamic programming and branch and bound. Problem comes under optimization are used to find either maximum or minimum. All these techniques we have multiple inputs and some constraints and we have to find feasible solution using these inputs and constraints. In greedy method we follow some predefined method. Using that predefined method, we reach to the solution. On contrary to this in dynamic programming we take decision at every step and in the end we reach to the solution. In branch and bound we create state space tree and explore all possibilities of live node. Based on some constraint we start killing some alive nodes. Here, firstly I will discuss all the design techniques. Then types of problems that can be solved under each design techniques and their time complexities.


2019 ◽  
Vol 33 (07) ◽  
pp. 1950075 ◽  
Author(s):  
Gong Ren ◽  
Renhuan Yang ◽  
Renyu Yang ◽  
Pei Zhang ◽  
Xiuzeng Yang ◽  
...  

Compared to the integer-order systems, the system characteristics of the fractional system are closer to the system characteristics of the real engineering system, the study found beyond that, strictly speaking, various physical phenomena in nature are nonlinear. The problem of parameter estimation problem of fractional-order nonlinear systems can be transformed into the problem of parameter optimization problem by constructing an appropriate fitness function. This paper proposes a hybrid improvement algorithm based on whale optimization algorithm (WOA) to solve this problem and verify it both in Lorenz system and Lu system. The simulation result shows that the hybrid improved algorithm is superior to genetic algorithm (GA), particle swarm optimization (PSO), grasshopper optimization algorithm (GOA) and WOA in convergence speed and accuracy.


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