{'fraction_non_alphanumeric': 0.020656136087484813, 'fraction_numerical': 0.010935601458080195, 'mean_word_length': 5.168539325842697, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Simulation Model of Al-Dura Electro-station Plant of 160 MW with Genetic Algorithm Method

In the present paper, a thermodynamic analysis of Al-Dura, Baghdad station type (K– 160– 13.34–0.0068), power plant has been carried out. The power plant system was simulated and a detailed parametric study undertaken. This study can be helpful to identify the plant site conditions that cause losses of useful energy taken place and also helpful to resolve some problems encountered in steam turbine, capacity unit. Developing nonlinear mathematical models based on system identification approaches during normal operation without any external excitation or disruption is always a hard effort, assuming that parametric models are available. This study included on using soft computing methods that would be helpful in order to adjust model parameters over full range of input–output operational data. In this case, the model parameters are adjusted by applying genetic algorithms as optimization methods. Comparison between the responses of the turbine – generator model with the responses of real system validates the accuracy of the proposed model in steady state and transient conditions. Simulation results shows that the efficiencies and feasibility of the developed model in term of more accurate and less deviation with the responses of read system in the steady and transient conditions, and the error of proposed function is less than 0.37%. This study presents the usage of the Cycle – tempo and Matlab/Simulink package to implement the model of the power plant. Finally, many recommendations have been suggested for improved plant performance.