Optimal scheduler for energy consumption reduction in multi-vector energy management systems: A case study at the Port of Borg

Abstract

The objective of microgrid operation is to supply the energy demanded by the loads at minimum cost. To achieve this goal, new tools are being proposed in the literature, such as the use of optimal schedulers in the field of multi-vector management systems. An optimal scheduler provides the hourly schedule of the flexible loads that exist in a microgrid to maximize the use of local renewable resources. This work aims to investigate the application in the context of five optimization algorithms in terms of energy and computation costs and to demonstrate how optimal schedulers can contribute significantly to reducing energy operating costs in new and real microgrid scenarios. The analysis of the algorithms is carried out through an experimental process on the existing installations at Port of Borg (Norway), which contains photovoltaic production and different types of flexible assets, such as cranes, electric vehicle charging stations, and electrical storage. Real data gathered at the port's premises is used to assess the energy cost reduction when the optimal scheduler is part of the energy management system, and the computations are performed in real time to apply the proposed schedule to the pilot. The results show how the use of optimal schedulers can reduce operation costs up to 17.2%, augmenting local energy production utilization, and that using two OS algorithms in cascade can also reduce the computation time

This project was undertaken by the eXiT research group, recipient of the established research distinction (SITES group, Ref. 2021 SGR 01125) granted by the Generalitat de Catalunya. The research received funding from the European Union Horizon 2020 under E-Land project grant agreement No 824388, from the European Union Horizon Europe under RESCHOOL project grant agreement No 101096490, and from MCIN/AEI/10.13039/501100011033 and the European Union NextGenerationEU/PRTR under OptiREC project grant agreement TED2021-131365B-C41. The work of Andreas Sumper was supported by the Catalan Institution for Research and Advanced Studies (ICREA) Academia Program

Open Access funding provided thanks to the CRUE-CSIC agreement with Elsevier

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