Combined islanding detection scheme utilising active network management for future resilient distribution networks

Laaksonen, Hannu; Hovila, Petri; Kauhaniemi, Kimmo

doi:10.1049/joe.2018.0202

Cited by 6 publications

(6 citation statements)

References 8 publications

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“…Q flex dispatch is provided by Q WIND and Q BESS whose magnitudes are defined in Eqs. (20) and (21), respectively. The controller is designed in such a way that the Q flex allocated shall control the reactive power flow in the TSO/DSO interface within Q RPW,MIN and Q RPW,MAX and the Voltage at Sulva feeder, U SUL which is considered as the reference MV voltage.…”

Section: Qu-management Systemmentioning

confidence: 99%

“…In [19][20][21][22][23], extensive research on various ANM schemes to maintain system voltage level, as well as to manage the reactive power flow from the DERs within the reactive power window (RPW) provided by the Finnish TSO, Fingrid and ENTSO-E network code [24], have been studied and validated in a local smart grid pilot SSG. From previous results, the reactive power control of wind turbine generator (WTG) was sufficient in order to satisfy RPW requirements on an hourly average data obtained from the SSG MV distribution network.…”

Section: Introductionmentioning

confidence: 99%

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Integration and control of lithium-ion BESSs for active network management in smart grids: Sundom smart grid backup feeding case

2021

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Lithium-ion battery energy storage systems (Li-ion BESS), due to their capability in providing both active and reactive power services, act as a bridging technology for efficient implementation of active network management (ANM) schemes for land-based grid applications. Due to higher integration of intermittent renewable energy sources in the distribution system, transient instability may induce power quality issues, mainly in terms of voltage fluctuations. In such situations, ANM schemes in the power network are a possible solution to maintain operation limits defined by grid codes. However, to implement ANM schemes effectively, integration and control of highly flexible Li-ion BESS play an important role, considering their performance characteristics and economics. Hence, in this paper, an energy management system (EMS) has been developed for implementing the ANM scheme, particularly focusing on the integration design of Li-ion BESS and the controllers managing them. Developed ANM scheme has been utilized to mitigate MV network issues (i.e. voltage stability and adherence to reactive power window). The efficiency of Li-ion BESS integration methodology, performance of the EMS controllers to implement ANM scheme and the effect of such ANM schemes on integration of Li-ion BESS, i.e. control of its grid-side converter (considering operation states and characteristics of the Li-ion BESS) and their coordination with the grid side controllers have been validated by means of simulation studies in the Sundom smart grid network, Vaasa, Finland.

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Section: Qu-management Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integration and control of lithium-ion BESSs for active network management in smart grids: Sundom smart grid backup feeding case

2021

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“…where, specified by Fingrid at the HV side of the TSO/DSO interface is represented in [36] and the requirement at the MV side is presented in [37]. The maximum active power limits are based on the measured data from year 2016, when imported grid power was 8.3 MW and the exported was 1.975 MW.…”

Section: Li-ion Battery Modelmentioning

confidence: 99%

Modelling battery energy storage systems for active network management—coordinated control design and validation

Parthasarathy

Sirviö

Hafezi

et al. 2021

IET Renewable Power Gen

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Control of battery energy storage systems (BESS) for active network management (ANM) should be done in coordinated way considering management of different BESS components like battery cells and inverter interface concurrently. In this paper, a detailed and accurate lithium-ion battery model has been used to design BESS controls, thereby allowing improved overall power system control design optimisation studies by simultaneously considering both component and system-level aspects. This model is utilised to develop a multi-objective ANM scheme (a) to enhance utilisation of wind power generation locally by means of active power (P)-control of BESSs; (b) to utilise distributed energy resources (i.e. BESS and wind turbine generators) to maintain system voltage within the limits of grid code requirements by reactive power/voltage (QU)-and active power/voltage (PU)-controls. BESS control strategies to implement the ANM scheme, are designed and validated through real-time simulation in an existing smart grid pilot, Sundom Smart Grid (SSG), in Vaasa, Finland.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…The used QU-droops, PU-droops, and Pf -droop of PV and BESS units are shown in Figure 2. It can be noted that BESSs 1 and 2 (Figure 1) have also the Q unb -control responsibility in order to enable correct operation of passive islanding detection methods [40][41][42]. In many grid codes, like in ENTSO-E NC RfG [43], the required reactive power feeding/absorbing capability of the DER units is defined to be range cos(ϕ) = 0.95 ind/cap and that has been also used in this paper for defining the reactive power limits of the DER unit (PV and BESS) QU-droops (Figure 2a,b).…”

Section: Droop Control Of the Der Unitsmentioning

confidence: 99%

Solutions to Increase PV Hosting Capacity and Provision of Services from Flexible Energy Resources

et al. 2020

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Future smart grids will be more dynamic with many variabilities related to generation, inertia, and topology changes. Therefore, more flexibility in form of several active and reactive power related technical services from different distributed energy resources (DER) will be needed for local (distribution network) and whole system (transmission network) needs. However, traditional distribution network operation and control principles are limiting the Photovoltaic (PV) hosting capacity of LV networks and the DER capability to provide system-wide technical services in certain situations. New active and adaptive control principles are needed in order to overcome these limitations. This paper studies and proposes solutions for adaptive settings and management schemes to increase PV hosting capacity and improve provision of frequency support related services by flexible energy resources. The studies show that unwanted interactions between different DER units and their control functions can be avoided with the proposed adaptive control methods. Simultaneously, also better distribution network PV hosting capacity and flexibility services provision from DER units even during very low load situations can be achieved.

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Combined islanding detection scheme utilising active network management for future resilient distribution networks

Cited by 6 publications

References 8 publications

Integration and control of lithium-ion BESSs for active network management in smart grids: Sundom smart grid backup feeding case

Integration and control of lithium-ion BESSs for active network management in smart grids: Sundom smart grid backup feeding case

Modelling battery energy storage systems for active network management—coordinated control design and validation

Solutions to Increase PV Hosting Capacity and Provision of Services from Flexible Energy Resources

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