Evaluation and Improvement Performance of a Boiler in a Thermal Power Plant Using Artificial Neural Network

This research aims to avoid damage in power plant boiler steam generation by using Artificial Neural Network techniques (ANN) to improve the boiler performance. The training and testing using ANN by Back Propagation (BP) algorithm. The inputs to the neural network such factors which include air fuel ratio, water level, flame, gas, pressure and temperature. Control of the optimum input variables represent the output of the neural network. Experimental data is obtained by using an industrial boiler operating at AL-Dura power plant.the method of control by ANN is off – line ,the information of boiler taken from real plant and applied in matlab program for training ANN to taken right decision for control of boiler. ANN results were used in the control of thermal parameters based on the software program Matlab\simulink and showed that the maximum deviation between experimental data is less than 0.01 from the predicted results of the neural network in comparison to the results with modeling of the match at High Rate with actual power plant. It is recommend that Artificial Neural Network techniques (ANN) can be used to predicate and optimization the performance of a power plant and many problem can be solve in engineering applications. KeywordsANN (Artificial Neural Network, boiler model, power plant, training, prediction model. How to cite this article: H. S. Anead, Kh. F. Sultan and R. J.Abd-Kadhum ," Evaluation and Improvement Performance of a Boiler in a Thermal Power Plant Using Artificial Neural Network " Engineering and Technology Journal, Vol. 36, Part A, No. 6, pp. 656-663, 2018 Engineering and Technology Journal Vol. 36, Part A, No. 5, 2018 657 boilerper formance related to its various running parameters. Hence, it is necessary to discover the current level of efficiency for evaluation performance of boiler, which is mandatory for power conservation action in industry. In Sugar industry, out of so many components. In any sugar industry, heart component is Boiler and tomaximize beneficiary output from sugar mill, it is necessary to maintain performance of Boiler with the design efficiency. So, in present work, an Energy analysis using direct heat loss is performed for a Bagasse Boiler of shree Mahuva Sahkari Khand Udyog Mandali. The evaluation of this power and steam producing plant is important for the proper functioning of the plant. And utilized heat loss method to find efficiency and losses in boiler house. All the necessary records for the calculation is taken from boiler house studying reading and plant data of shree Mahuva Sahkari Khand Udyog Mandali. Theimportant variable of boiler performance is sugarcane bagasse in sugar mill cogeneration systems and help calculation in its system. Many researcherhave proposed artificial neural network technique (ANN) modelingwithexperimental ortheoretical workfor more industrial and engineeringapplication. [5]proposed artificial neural network technique to control of the water level in the drum boilers in AL-Dura power plants.the input of neural network is pressure, feed water flow and steam flow,While the output of neural network is drum level.In this present used least number of hidden neurons and the leastvalue of mean square error. The neural network is simulated andits plottedthe output of the real data. And using feed forward neuralnetworks andrecurrent neural networks for testing . The results showed that the mean square error of feed forward neural networksis more than 1.0 E-04 but of recurrent neural networks is less than 1.0 E-06.this technique applied by Computer programs in MATLAB. [6]Presented using Artificial Neural Networks ato predict the water level in the drum of a boiler.In the present work applied ANN model of the boiler feed systemto increases the efficiency and reduce the tripping of the steam power plant,The variables of this model can beobtained from the characteristicsof the boiler and physical dimensions. The results showedthe frequency of deviations were reducedof the water level in the drum of the steam boiler and the degree of deviation also reduced. The model-based control algorithms is developed of boiler . The aim of this article to study the impact different parameter such as flame,air\fuel ratio, gas ,pressure , air fuel ratio, temperature on thermal power plant by using ANN. Evaluation the performance for this plants by using ANN.