RoCoF-Constrained Scheduling Incorporating Non-Synchronous Residential Demand Response

Daly, Pádraig; Qazi, Hassan W.; Flynn, Damian

doi:10.1109/tpwrs.2019.2903784

Cited by 31 publications

(9 citation statements)

References 35 publications

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“…In such a case the operational constraint (3) becomes (4) which ensures that inertia constant of any N-1 generators events operating at nominal frequency (fo) and nominal power ( Pi ) does not count toward the total system inertia. These operational limits are similar to that investigated in [34]. The all Island power system import/export power from Great Britain electricity grid via two HVDC interconnectors.…”

Section: Calibrated Frequency Event On the Irish Power Systemsupporting

confidence: 73%

“…Where i is the time step of the time domain simulation, TRoCoF is the measurement window (0.5 s) over which the RoCoF is calculated. The timeframe of 0.5 s corresponds to that deployed for the current anti-islanding RoCoF relay settings in the Irish power system grid code [34] [41]. Other shorter rolling windows (e.g., 0.1 s and 0.25 s) are also proposed in literature [41].…”

Section: B Effect Of Demand Response On Rocofmentioning

confidence: 99%

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Manipulation of Static and Dynamic Data Center Power Responses to Support Grid Operations

et al. 2020

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This research investigates three frameworks for data centers to deliver fast frequency response services from their UPS storage systems, HVAC cooling units, and the ability of off-gridding the entire data center during transient frequency events. The aim of this is to provide dynamic injection during transients in real time for grid operators and for power sellers in hour ahead markets. A static and a dynamic model was developed in DIgSILENT PowerFactory. In the static model, the data centers are off-gridded in response to emergency frequency signals from system operator in a centralized manner, whereas in the dynamic model the UPS systems and shiftable cooling units power consumption was altered continuously in the data centers in response to local frequency measurements considering different real-time scenarios. The performance of the proposed operational frameworks is validated, and calibrated to actual frequency events that occurred in the Irish power system. The sensitivity analysis demonstrates that both static and dynamic load controls can significantly improve system frequency metrics, i.e., frequency nadir and rate of change of frequency during transients. The key findings show that demand response can only make a substantial frequency improvement if a large amount of energy delivered within the timeframe of inertial response. INDEX TERMS Battery and UPS, data centers, demand-side management, fast frequency response, inertia response, load modeling, power system dynamics, wind power generation. NOMENCLATURE PLo,j Pre-fault active power of a load at j th bus. QLo,j Pre-fault reactive power of a load. PL,j Active and reactive power of a load. QL,j Reactive power of a load at j th bus. vo,j Pre-fault voltage of j th bus. vj Post-fault voltage of j th bus. ui, uj Committed status. E Operational inertia floor constraint. Hi Inertia floor constraint of i th generators. Hsys Post-event system inertia constant. Si Stated nominal power limit. fo Nominal system frequency. fi Regional nominal frequency. fCOI Frequency at center of inertia.

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Section: Calibrated Frequency Event On the Irish Power Systemsupporting

confidence: 73%

Section: B Effect Of Demand Response On Rocofmentioning

confidence: 99%

Manipulation of Static and Dynamic Data Center Power Responses to Support Grid Operations

et al. 2020

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“…The power system will experience times of lower inertia levels due to higher shares of asynchronous wind and solar generation. Both increasing asynchronous generation and decommitting synchronous generation lead to decreased inertia (Daly et al, 2019). The inertia in a power system has an influence on the dynamic behavior of the frequency after any unbalance of generation and consumption.…”

Section: 22mentioning

confidence: 99%

“…To address the low-inertia problem, a commitment-and-dispatch ROCOF (future) constraint within a unit commitment algorithm has been proposed, which explicitly considers the commitment status and power output of synchronous resources as well as the (generator) contingency set (Daly et al, 2019). Comparison is made with an inertial floor (current) approach based on the worst-case conditions.…”

Section: Operational Models: Unit Commitment and Economic Dispatchmentioning

confidence: 99%

Design and Operation of Energy Systems with Large Amounts of Variable Generation: IEA Wind TCP Task 25 (Final Summary Report)

Holttinen¹,

Kiviluoma²,

Helistö³

et al. 2021

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“…The economic benefits of using supermarket refrigeration systems as source of reserves can be assessed using established approaches [27,39,40] , whereby it is assumed that the reserve offer price of supermarket refrigeration systems is near zero. The contribution of DR units towards reserve provision tends to reduce the need for (inefficient) part-loading of conventional generators, as reserve is provided from elsewhere [39].…”

Section: Unit Commitment Schedulingmentioning

confidence: 99%

Fast frequency response provision from commercial demand response, from scheduling to stability in power systems

Misaghian

O’Dwyer

Flynn

2022

IET Renewable Power Gen

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Reduced numbers of online conventional generators, due to increasing shares of renewable energy sources, are increasing the requirement for a fast frequency response capability from reserve providers when a large infeed/outfeed trips. The commercial demand‐side sector, considering its size (MW/MWh) and existing communication and control infrastructure, makes it a potential valuable source of flexibility provision. Supermarket refrigeration systems are considered here as being representative of commercial end‐uses, with individual devices stochastically simulated under different ambient conditions, supermarket occupancy, food categories, and refrigeration performance. An aggregated fleet of supermarket loads are then created to provide a system‐wide reserve response. The all‐island power system of Northern Ireland and Republic of Ireland, with a horizon of 2030, is considered as a representative case study. Three distinct demand‐side frequency control methods, including static, droop, and hybrid control are presented and developed within a stability analysis platform. Year‐long simulation results show a general improvement in the frequency nadir and (maximum) rate of change of frequency when supermarkets are providing fast frequency response services to the grid, with the likelihood of severe transients (frequency nadir <49 Hz) greatly reduced (82% improvement), depending on the FFR control design, and associated speed of response.

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RoCoF-Constrained Scheduling Incorporating Non-Synchronous Residential Demand Response

Cited by 31 publications

References 35 publications

Manipulation of Static and Dynamic Data Center Power Responses to Support Grid Operations

Manipulation of Static and Dynamic Data Center Power Responses to Support Grid Operations

Design and Operation of Energy Systems with Large Amounts of Variable Generation: IEA Wind TCP Task 25 (Final Summary Report)

Fast frequency response provision from commercial demand response, from scheduling to stability in power systems

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