Air Compressor Load Forecasting using Artificial Neural Network

Da-Chun Wu; Babak Bahrami Asl; Ali Razban; Jie Chen

doi:10.24433/co.9017343.v1

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Air Compressor Load Forecasting using Artificial Neural Network

Da-Chun Wu Babak Bahrami Asl Ali Razban Jie Chen

Year: 2020 Code Ocean

DOI: 10.24433/co.9017343.v1

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Abstract

The objective of this study is to predict compressed air systems’ electrical load proﬁle, which is valuable to industry practitioners as well as software providers in developing better practice and tools for load management and look-ahead scheduling programs. Two artificial neural networks, Two-Layer Feed-Forward Neural Network and Long Short-Term Memory were used to predict an air compressor's electrical load.

Keywords:

Gas compressor Artificial neural network Air compressor Electrical load Mean squared error Computer science Engineering Artificial intelligence Statistics Mathematics Voltage Electrical engineering Mechanical engineering

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Refrigeration and Air Conditioning Technologies

Physical Sciences → Engineering → Mechanical Engineering

Turbomachinery Performance and Optimization

Physical Sciences → Engineering → Aerospace Engineering

Energy Efficiency and Management

Physical Sciences → Energy → Renewable Energy, Sustainability and the Environment

Air Compressor Load Forecasting using Artificial Neural Network

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