Optimal Frequency Support of Variable-Speed Hydropower Plants at Telemark and Vestfold, Norway: Future Scenarios of Nordic Power System

Acosta, Martha N.; Pettersen, Daniel; González-Longatt, Francisco; Argos, Jaime Peredo; Andrade, Manuel A.

doi:10.3390/en13133377

Cited by 16 publications

(15 citation statements)

References 11 publications

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“…Parameters Settings CVC Vsetpoint = 0.99 pu VQC Kdroop = 5%; 0.95 pu < Vsetpoint < 1.05 pu The proposed optimal-centralised reactive power management strategy was implemented in Python programming language and automated to be solved by creating an interface Python−DIgSILENT ® PowerFactory TM . The optimisation was solved using a meta−heuristic algorithm named improved harmony search algorithm [29], and its parameter was set up as in [30].…”

Section: Reactive Power Management Strategiesmentioning

confidence: 99%

“…Meanwhile, the fixed reactive power price is taken from the default payment rate document [22], for August 2020, which is bQ−fixed = 2.337227£/MVArh assuming a utilisation factor The proposed optimal-centralised reactive power management strategy was implemented in Python programming language and automated to be solved by creating an interface Python-DIgSILENT ® PowerFactory TM . The optimisation was solved using a meta-heuristic algorithm named improved harmony search algorithm [29], and its parameter was set up as in [30].…”

Section: Reactive Power Management Strategiesmentioning

confidence: 99%

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Optimal Microgrid–Interactive Reactive Power Management for Day–Ahead Operation

et al. 2021

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The replacement of conventional generation sources by DER creates the need to carefully manage the reactive power maintaining the power system safe operation. The principal trend is to increase the DER volume connected to the distribution network in the coming years. Therefore, the microgrid represents an alternative to offer reactive power management due to excellent controllability features embedded in the DER, which enable effective interaction between the microgrid and the distribution network. This paper proposes a microgrid−iterative reactive power management approach of power-electronic converter based renewable technologies for day-ahead operation. It is designed to be a centralised control based on local measurements, which provides the optimal reactive power dispatch and minimise the total energy losses inside the microgrid and maintain the voltage profile within operational limits. The proposed optimal-centralised control is contrasted against seven local reactive power controls using a techno-economic approach considering the steady−state voltage profile, the energy losses, and the reactive power costs as performance metrics. Three different reactive power pricing are proposed. The numerical results demonstrate the optimal microgrid−interactive reactive power management is the most suitable techno-economic reactive power control for the day−ahead operation.

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Section: Reactive Power Management Strategiesmentioning

confidence: 99%

Section: Reactive Power Management Strategiesmentioning

confidence: 99%

Optimal Microgrid–Interactive Reactive Power Management for Day–Ahead Operation

et al. 2021

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“…The distributed-BESS consists of three components (see Figure 5): (i) an energy storage package, a set of batteries with an appropriate connection to provide; (ii) a power electronic converter model (inverter/rectifier); and (iii) several control loops installed to allow for the proper operation of the energy storage system [35,36].…”

Section: Distributed Battery Energy Storage Systemsmentioning

confidence: 99%

A Coordinated Control of Offshore Wind Power and BESS to Provide Power System Flexibility

et al. 2021

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The massive integration of variable renewable energy (VRE) in modern power systems is imposing several challenges; one of them is the increased need for balancing services. Coping with the high variability of the future generation mix with incredible high shares of VER, the power system requires developing and enabling sources of flexibility. This paper proposes and demonstrates a single layer control system for coordinating the steady-state operation of battery energy storage system (BESS) and wind power plants via multi-terminal high voltage direct current (HVDC). The proposed coordinated controller is a single layer controller on the top of the power converter-based technologies. Specifically, the coordinated controller uses the capabilities of the distributed battery energy storage systems (BESS) to store electricity when a logic function is fulfilled. The proposed approach has been implemented considering a control logic based on the power flow in the DC undersea cables and coordinated to charging distributed-BESS assets. The implemented coordinated controller has been tested using numerical simulations in a modified version of the classical IEEE 14-bus test system, including tree-HVDC converter stations. A 24-h (1-min resolution) quasi-dynamic simulation was used to demonstrate the suitability of the proposed coordinated control. The controller demonstrated the capacity of fulfilling the defined control logic. Finally, the instantaneous flexibility power was calculated, demonstrating the suitability of the proposed coordinated controller to provide flexibility and decreased requirements for balancing power.

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“…The authors decided to use DIgSIELNT PowerFactory [5], [13] as a modelling and simulation tool in this paper; as a consequence, IEEEG1 model defined in the global library of the software was used. After the refurbishment of the governors and turbines in 2019, a new model-based adaptive PID controller is used in AGS813 Servo Module for steam turbine governor (see Fig.…”

Section: B Modelling Of a Steam Turbine And Governormentioning

confidence: 99%

System Parameter Identification of Thermal Generation Unit in the Mongolian Electrical Grid: Real-Life Frequency Response Test

Adiyabazar¹,

González-Longatt

Acosta

et al. 2021

2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America)

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Mongolian power grid (MPG) is becoming more eco-friendly as the power system is continuously integrating renewable energy, which reached 20% of the total installed capacity of Mongolia in 2020. With such growth of renewable energy in the system, the daily operation and the safety of the MPG has become a challenge. Therefore, the dynamic behaviour of conventional power plants (CPPs) must be demonstrated to fulfil the requirements of integrating more renewable energy in the MPG, especially for frequency stability. This paper illustrates the results of the system parameter identification of an actual steam turbine and a governor system with PID controller by using a real-life test performed on Generator 1 (G1) of the biggest thermal power plant (TPP-4) in Mongolia on 6 th March 2020. The main contribution of this paper is to clear uncertainties about the PID controller's parameters installed in the steam turbine of G1 in early 2019, as a consequence, giving the system operator an accurate dynamic model of the generation unit. The steam turbine and governor are modelled in DIgSILENT® PowerFactory, and the Particle Swarm Optimization (PSO) method is used for identifying the parameters of the PID controller of the G1 at TPP-4. Simulation results from the PowerFactory software matched firmly (error <0.3%) with the measured frequency from the Phasor Measurement Unit (PMU).

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Optimal Frequency Support of Variable-Speed Hydropower Plants at Telemark and Vestfold, Norway: Future Scenarios of Nordic Power System

Cited by 16 publications

References 11 publications

Optimal Microgrid–Interactive Reactive Power Management for Day–Ahead Operation

Optimal Microgrid–Interactive Reactive Power Management for Day–Ahead Operation

A Coordinated Control of Offshore Wind Power and BESS to Provide Power System Flexibility

System Parameter Identification of Thermal Generation Unit in the Mongolian Electrical Grid: Real-Life Frequency Response Test

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