NEURAL NETWORK FORECASTING MODEL OF ENERGY CONSUMPTION

• Main Author: MOHD. PARIS, JOHANA
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi Petronas 2011
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://utpedia.utp.edu.my/7566/1/2011%20-%20Neural%20network%20forecasting%20model%20of%20energy%20consumption.pdf; http://utpedia.utp.edu.my/7566/

Natural gas is transported to consumers via pipelines. The outgoing gas flow along the pipelines is managed and monitored by a metering system. The metering system must be ensured reliable and dependable at all cost to maintain the billing integrity between distributors and customers. An existing system in Nur Metering Station, PETRONAS Gas Berhad (PGB), Kulim is held responsible to calculate the energy consumption from the sales gas produced. The system consists of a turbine meter, measuring equipments which are pressure transmitter and temperature transmitter, gas chromatography and flow computer. However, the system is a standalone system that does not have any reference system to verify its integrity. Customers are billed according to the amount of energy consumption calculated and any error in calculation will cause loss of profit to the company and affect PETRONAS's business credibility. Therefore a neural network forecasting model of energy consumption is developed as a verification system. The model will forecast the energy consumption of outgoing gas flow and compare it with the results of the existing metering system to ensure the reliability and accuracy of the system. A few models are developed and the best model is chosen based on the performance indicator. As a result, the billing integrity between PETRONAS and the customers could be maintained and in the future if the project is expanded, it will have the potential of saving of millions of dollars to Malaysian oil and gas companies.