Power management system for RTG crane using fuzzy logic controller. (February 2020)

• Record Type: Journal Article
• Authors: Pietrosanti, Stefano; Alasali, Feras; Holderbaum, William
• Is Part Of: Sustainable energy technologies and assessments. Volume 37(2020)
• Publication Date: 2020-02
• Subjects: Energy storage system -- RTG crane -- Fuzzy logic controller -- Energy saving; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2020.100639
• Languages: English
• ISSNs: 2213-1388

Abstract

Highlights: FLC controller is developed to increase energy saving and peak reduction for e-RTGs. The parameters of FLC controllers are investigated and tested to improve power performance of ESS. A comparison analysis for the impact of using different power controller in the ESS are conducted to evaluate the proposed models. Abstract: In this research, there are two major objectives have been investigated for a Rubber Tyred Gantry (RTG) crane system: energy consumption reduction and decrease the stress on the primary source. These objectives can be met by using an advance control system that reads the status of the crane and outputs a power reference value which is fed to the storage device. This paper presents Fuzzy Logic Controller (FLC) approach to maximise the potential benefits of adding energy storage units to RTG cranes. In this work, FLC is described and simulated, with the results analysed to highlight the behaviour of the storage in association with the specific control system. An actual collected data at the Port of Felixstowe, UK has been used to develop the crane and ESS models and test the proposed control strategies in this paper. Furthermore, a comparison analysis between the FLC and the standard control system (PI) for RTG crane and ESS applications will be presented with respect to energy consumption, fuel saving and the control impact on the energy device. The simulation results of the FLC control strategy for the collected data shows that it successfully increases the energy savings by 32% and outperforms the PI controller by 26%.