A Hybrid Technique for the Performance Optimization in the Combustion Process of a Power Plant Boiler: An Efficient ANNSSA Technique

  • P. V. Narendra Kumar EEE Department, Priyadarshini College of Engineering and Technology, Nellore, Andhra Pradesh, India
  • Ch. Chengaiah EEE Department, S. V. University College of Engineering, Tirupati, Andhra Pradesh, India
  • P. Rajesh Department of Electrical & Electronics Engineering, Anna University, India
  • Francis H. Shajin Department of Electronics & Communication Engineering, Anna University, India
Keywords: Artificial neural network, Salp swarm optimization, air to fuel ratio, Boiler combustion system.

Abstract

In this paper presents a hybrid method for optimization process of combustion in power plant boiler. ANSSA scheme will be joint implementation of Artificial Neural Network (ANN) as well as Salp Swarm Optimization Algorithm (SSA) known ANNSSA. Here, ANN training process will be enhanced by using the SSA calculating. The optimization of economic parameters reduces excess air level and performs combustion efficiency at boiler system. Due to the operation of service boiler, oxygen content of flue gases is one of the significant factors which influence the efficiency of boiler, and influence each other to other thermal parameters of economic like temperature of flue gases combustion, unburned carbon at fly ash slag and consumption of coal power supply. The combustion performance denotes a saving at operating costs of boiler. ANNSSA method evolved for process of combustion to enhance the implementation and efficiency of the power plant boiler. At that time, ANNSSA technique is implemented at MATLAB/Simulink work platform as well as implementation is evaluated using existing techniques.

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Author Biographies

P. V. Narendra Kumar, EEE Department, Priyadarshini College of Engineering and Technology, Nellore, Andhra Pradesh, India

P. V. Narendra Kumar obtained his B.Tech (2004) from Sri Venkateswara University, Tirupati, A.P, India and M.Tech (2007) from Sri Venkateswara University, Tirupati, A.P, India. He is having a total teaching experience of 13 years. He has published 6 papers in National/International journals. He is doing his Ph.D. in Sri Venkateswara University, Tirupati. Presently, he is working as Associate Professor in EEE of Priyadarshini College of Engineering and Technology, Nellore, A.P. His research interest is Power System Operation & Control, Fuzzy Logic and Artificial Neural Networks.

Ch. Chengaiah, EEE Department, S. V. University College of Engineering, Tirupati, Andhra Pradesh, India

Ch. Chengaiah, obtained his B.Tech.(1999) from Sri Venkateswara University College of Engineering, Tirupati, A.P,. India and M.E (2000) from National Institute of Technology (NIT) formerly called as Regional Engineering College, Tiruchanupalli, Tamilnadu, India and Ph.D. (2013) from Sri Venkateswara University College of Engineering, Tirupati A.P. India. He is having a total teaching experience of 18 years. He has published 20 papers in National/International journals. At present 10 students are working for Ph.D. under his guidance. Presently, he is working as Professor in EEE of S.V.University College of Engineering, Tirupati, A.P., and India. His research interest is Power System Operation & Control, Power Electronic Drives, Control Systems and Nonrenewable Energy Sources.

P. Rajesh, Department of Electrical & Electronics Engineering, Anna University, India

P. Rajesh graduated from Anna University, Chennai, India. He has more than 10 years of IT experience. His current research interests include artificial intelligence, power system, smart grid technologies and soft computing.

Francis H. Shajin, Department of Electronics & Communication Engineering, Anna University, India

Francis H. Shajin graduated from Anna University, Chennai, India. He has more than 10 years of IT experience. His current research interests include very-large-scale integration, soft computing, image processing, machine learning and networking.

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Published
2021-05-28
Section
Articles