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About the research and the project aims

Renewable energy resources (RER) and renewable energy storage (RES) are being deployed around the world at ever-increasing rates. The resource that has already been deployed can be utilized in ways that improve its resource efficiency and economic value. The idea of a Virtual Power Plant (VPP) consisting of an Energy Management System (EMS) that smartly manages a Battery Energy Storage System (BESS) for providing various value-enhancing services has been proposed in our work. The problem of BESS management has been divided into two separate problems of prognosis and control. The prognosis problem is tackled by the proposed Prognosis Module Optimization (PMO). The BESS Schedule that is the output of the Prognosis Module is the calculated expectation of how the EMS should operate the BESS while accounting for the involved uncertainties. This schedule also outlines the safety factors that help in the safe operation of the Real-time Operation Module (ROM) despite the uncertain operations involved. The ROM tackles the control problem.

Improved economic viability increases the technology adoption rate at the consumer level. Our work tries to do it for RER and RES for a sustainable future.

This project aims to create a synergetic relationship between local RER and RES owners and sustainable, resource-efficient development for the whole energy system. This enables the expedited deployment of these technologies. The VPP creates value for TSOs through frequency-related ancillary services and for the DSOs in peak shaving by offloading local bottlenecks, and in the future by reactive power management for both TSO and DSO. The local resource owners get direct economic benefit by implementing our EMS on their resource units, irrespective of their size. The EMS when deployed at any RER or RES improves its economic competitiveness. This has social, environmental, and technological benefits.

The EMS prognosis and control algorithms have been designed, simulated, and tested on historical data. Pilot studies require formal implementation of the algorithms running in real-time which would require development in part.

This research is in line with UN’s SDG 7, 8.4, 9.4, 11.6, and 12.2  as it enables affordable, reliable, sustainable, and modern energy, improves resource efficiency, and efficient use of natural resources.

The project has been performed within the RCAM ressarch group at KTH led by Professor Lina Bertling Tjernberg and in collaboration with CheckWatt. During 2021 the project work was sponsored within the SweGRIDS research program. More information from here FPS30, SweGRIDS (  

Read more from here:

[1] Real-time Operation Model for Energy Management System of Battery Energy Storage System - Case Study: The School of Sinntorp, H. Shafique, D.-E. Archer, R. Eriksson, L. B. Tjernberg, Accepted to be published in the proceedings of the International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), Manchester, June 2022.

[2] Energy Management System (EMS) of Battery Energy Storage System (BESS) – Providing Ancillary Services, H. Shafique, L. B. Tjernberg, D.-E. Archer, and S. Wingstedt, in IEEE PowerTech, Madrid, Spain, June 2021.

[3] Behind the Meter Strategies Energy management system with a Swedish case study," H. Shafique et al., " IEEE Electrification Magazine, vol. 9, no. 3, s. 112-119, 2021.

For access to a private copy send a request to .