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  • 1.
    Gopalakrishnan, Pavithra
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Alikhani, Parnian
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Shafique, Hamza
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Bertling Tjernberg, Lina
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Hallinder, Jonathan
    EON, Stockholm, Sweden..
    Engström, Adam
    EON, Stockholm, Sweden..
    He, Ying
    Vattenfall, Stockholm, Sweden..
    Peak Demand Shaving Based on Solar and Load Forecasting at Port of Gavle2022In: 2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022, Institute of Electrical and Electronics Engineers (IEEE) , 2022Conference paper (Refereed)
    Abstract [en]

    Solar energy is considered as one of the most promising solutions to prevent climate change, and optimal utilization of solar energy contributes to reducing dependence on non-renewable energy sources. Distributed generation can help support the delivery of clean and reliable power to consumers. In this paper, an Energy Management System (EMS) is developed along with load and Photovoltaic (PV) generation forecasting to perform peak shaving of electricity demand. The results from the proposed method are implemented in a real case study, in Port of Gavle in Sweden. Total revenue generated from services of peak-shaving and frequency regulation is maximum in the scenario considering high PV generation and high consumption on a selected experimental day in July. The results show that PV-battery storage systems are effective options to increase the integration of renewable energies in the grid, flatten the load, and achieve stabilized operation.

  • 2.
    Shafique, Hamza
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Archer, Dan-Eric
    CheckWatt AB, Stockholm, Sweden..
    Eriksson, Robert
    Svenska Kraftnät, Swedish Natl Grid, Stockholm, Sweden..
    Bertling Tjernberg, Lina
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Real-time Operation Model for Energy Management System of Battery Energy Storage System - Case Study: The School of Sinntorp2022In: 2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022, Institute of Electrical and Electronics Engineers (IEEE) , 2022Conference paper (Refereed)
    Abstract [en]

    This paper shows the real-time operation model of Energy Management System (EMS) for control of Battery Energy Storage System (BESS). These models are needed to manage uncertain electricity loads, delivery of peak shaving and frequency regulation services and the BESS financial feasibility. The delivery of these services result in economic return for the resource owner and increased grid flexibility. The Energy Management System implemented in this work uses the electricity load and grid frequency data as inputs to generate BESS control commands that deliver the said services. The validation simulation performed on the School of Sinntorp in Sweden returns an annual return on investment of 22% for the BESS and inverter. Implementation of storage systems was shown to expedite the adoption of renewable energy while also solving the challenges that this adoption on scale poses. This active adoption is pivotal in achieving the UN sustainable developmental goals (SDGs) for energy.

  • 3.
    Tunelid, Lucas
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Peri, Michael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Sathyamoorthy, Srinath
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Shafique, Hamza
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Rozas, Andres
    Bertling, Lina
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Simplistic Revenue Based BESS Sizing Tool Developed in Python Using Historical Grid Data2022In: IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe), Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 1-6Conference paper (Refereed)
    Abstract [en]

    The introduction of transmission operators enabling small-scale energy storage to participate in the frequency containment market through augmented bidding requires estimating the potential revenue gain of such instalments. Due to this, the overall goal of this study has been to develop and implement a simplistic model within Python for consumers looking into investing in such systems, capable of analyzing the potential of generating profit for a specific battery configuration through the use of historical electricity prices and grid frequency data. This paper proposes a model utilizing sets of linear and nonlinear constraints in order to represent the process of bidding on the Nordic frequency containment reserve market. Furthermore, the potential cost savings made by peak shaving and a method of estimating the cost of the degradation due to cycling the battery have been included within the model. The final result shows a software capable of identifying appropriate system sizes based on the instalment’s cost and the potential revenue.

  • 4.
    Shafique, Hamza
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Bertling Tjernberg, Lina
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Archer, Dan-Eric
    Wingstedt, Samuel
    Energy Management System (EMS) of Battery Energy Storage System (BESS) – Providing Ancillary Services2021In: 2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2021, article id 9494781Conference paper (Refereed)
    Abstract [en]

    In this paper, an Energy Management System (EMS) that manages a Battery Energy Storage System (BESS) is implemented. It performs peak shaving of a local load and provides frequency regulation services using Frequency Containment Reserve (FCR-N) in the Swedish reserve market. The EMS optimizes the approach of BESS resource dispatch distribution between two ancillary services, such that it maximizes profits and resource efficiency while enhancing overall system reliability of the electricity grid. The EMS consists of; a Prognosis Module running a day ahead to allow for identification of intervals for peak shaving and frequency regulation, and a Real-time Operation Module running on the day of operation creating BESS control commands. Implementing the Prognosis module on Öckerö ice-rink results in 12% cost saving on the grid tariff with 21% power peak reduction and three hours of daily frequency reserve. Multiple such systems can be aggregated to improve flexibility of the system.

  • 5. Cacovich, Stefania
    et al.
    Messou, Davina
    Bercegol, Adrien
    Béchu, Solène
    Yaiche, Armelle
    Shafique, Hamza
    École Polytechnique, IPVF, UMR 9006, CNRS, 18 Boulevard Thomas Gobert, 91120 Palaiseau, France.
    Rousset, Jean
    Schulz, Philip
    Bouttemy, Muriel
    Lombez, Laurent
    Light-Induced Passivation in Triple Cation Mixed Halide Perovskites: Interplay between Transport Properties and Surface Chemistry.2020In: ACS Applied Materials and Interfaces, ISSN 1944-8244, E-ISSN 1944-8252, Vol. 12, no 31, p. 34784-34794Article in journal (Refereed)
    Abstract [en]

    Mixed halide perovskites have attracted a strong interest in the photovoltaic community as a result of their high power conversion efficiency and the solid opportunity to realize low-cost and industry-scalable technology. Light soaking represents one of the most promising approaches to reduce non-radiative recombination processes and thus to optimize device performances. Here, we investigate the effects of 1 sun illumination on state-of-the-art triple cation halide perovskite thin films Cs0.05(MA0.14, FA0.86)0.95 Pb (I0.84, Br0.16)3 by a combined optical and chemical characterization. Competitive passivation and degradation effects on perovskite transport properties have been analyzed by spectrally and time-resolved quantitative imaging luminescence analysis and by X-ray photoemission spectroscopy (XPS). We notice a clear improvement of the optoelectronic properties of the material, with a increase of the quasi fermi level splitting and a corresponding decrease of methylammonium MA+ for short (up to 1 h) light soaking time. However, after 5 h of light soaking, phase segregation and in-depth oxygen penetration lead to a decrease of the charge mobility.

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