Modeling, simulation and comparison of control techniques for energy storage systems

Ortega, Álvaro; Milano, Federico

doi:10.1109/ptc.2017.7980860

Cited by 9 publications

(10 citation statements)

References 16 publications

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“…A plethora of literature is available on the modelling and control of ESS [8][9][10]. The control techniques covered by this group are H α control, sliding mode control, virtual inertia emulation and others.…”

Section: Nomenclaturementioning

confidence: 99%

Sweeping power system stabilisation with a parametric fuzzy predictive control of a generalised energy storage device

Ahsan

Mufti

2020

IET Generation Trans & Dist

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A control oriented approach is adopted for the implementation of a parametric fuzzy‐predictive control on a compact model of a generalised energy storage device implanted in a multi‐machine system. It is realised using a combination of a heuristic fuzzy logic control (HFLC) and a predictive step ahead control (PSAC) for energy storage reactive and real power modulation, respectively. While PSAC overcomes the computational burden innate to model predictive control, the HFLC with paramount simplicity lays down the design template for fuzzy control. Local bus measurements are translated into rate of change of frequency and voltage errors, while accommodating a second‐order dynamics of a phase locked loop. To emphasise the computational simplicity and implementation speed of the proposed technique, all parameters of the problem are solved explicitly. These parameters account for the input–output mapping structure consisting of membership spreads and rule base in fuzzy domain. In predictive control, while approximating the storage‐converter dynamics by a second‐order system, relevant expressions are derived for the parameters involved in the loop. Umbrella power system stabilisation, viz., high oscillation damping with quicker settling times, frequency‐nadir curtailment, power and voltage smoothing is assured with the parametric fuzzy‐predictive controlled energy storage.

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Section: Nomenclaturementioning

confidence: 99%

Sweeping power system stabilisation with a parametric fuzzy predictive control of a generalised energy storage device

Ahsan

Mufti

2020

IET Generation Trans & Dist

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“…In 2014, a research team from the Technical University of Madrid (UPM) and another one from the Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) began collaborating on the control and sizing of a flywheel energy storage system for the frequency control of El Hierro wind‐hydropower system. A droop‐based control strategy, similar to the one implemented in the Rhode hybrid test facility (Ortega & Milano, ), as well as a nonlinear proportional control strategy which modifies the input/output power set‐point signal of the flywheels as a function of the SOC, were tested by means of simulations. The frequency regulation effort was distributed between the flywheels and the pumped‐storage power plant thanks to the use of different control dead bands.…”

Section: Previous Experiences On the Coordination Of Faes And Hydropomentioning

confidence: 99%

Integration of fast acting energy storage systems in existing pumped‐storage power plants to enhance the system's frequency control

Pérez‐Díaz

Lafoz

Burke³

2019

WIREs Energy & Environment

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This paper suggests the integration of fast acting energy storage systems in existing pumped‐storage power plants as a practical solution to enhance the system's frequency control. The term “fast acting energy storage” is used in the paper to refer to, in the authors' opinion, the most suitable energy storage technologies for the purpose of frequency control, that is, flywheels and supercapacitors. The paper describes the few research works that have so far dealt with the coordination of flywheels or supercapacitors and pumped‐storage or hydropower, and compare the proposed solution with the upgrade of existing pumped‐storage power plants to allow variable speed operation. To finish, the paper describes other side benefits of the proposed solution, discusses the most important barrier for its realization and summarizes a few regulatory changes that have been recently implemented in a few electric power systems which provide some hope for the proposed solution to become a reality. This article is categorized under: Energy Infrastructure > Systems and Infrastructure

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“…However, intermittent renewable energy causes significant issues on power system operations such as demand-generation balance, voltage/frequency stability and operational planning in electricity markets [2,[4][5][6]. Energy Storage Systems (ESSs) can play a significant role in mitigating the issues highlighted above, and improve the dynamic response of the system [7,8].…”

Section: Introductionmentioning

confidence: 99%

Battery SOC management strategy for enhanced frequency response and day-ahead energy scheduling of BESS for energy arbitrage

Gundogdu

Gladwin

Stone

2017

IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

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The electricity system has to balance demand and supply every second, a task that is becoming evermore challenging due to the increased penetration of renewable energy sources and subsequent inertial levels. In the UK, a number of grid frequency support services are available, which are developed to provide a real-time response to changes in the grid frequency. The National Grid Electricity Transmission (NGET)the primary electricity transmission network operator in the UKhas introduced a new faster frequency response service, called the Enhanced Frequency Response (EFR), which requires a response time of under one second. Battery energy storage systems (BESSs) are ideal choice for delivering such a service. In this paper a control algorithm is presented which supplies a charge/discharge power output with respect to deviations in the grid frequency and the ramp-rate limits imposed by NGET, whilst managing the state-of-charge (SOC) of the BESS to maximise the utilisation of the available energy capacity. Using the real UK market clearing prices, a forecasted battery state of charge (SOC) management strategy has been also developed to deliver EFR service whilst scheduling throughout the day for energy arbitrage. Simulation results demonstrate that the proposed algorithm delivers an EFR service within the specification whilst generating arbitrage revenue. A comparative study is also presented to compare the yearly arbitrage revenue obtained from the model of the Willenhall and an experimental Leighton Buzzard battery storage system. Simulation results on a 2MW/1MWh lithium-titanate BESS are provided to verify the proposed algorithm based on the control of an experimentally validated battery model.

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Modeling, simulation and comparison of control techniques for energy storage systems

Cited by 9 publications

References 16 publications

Sweeping power system stabilisation with a parametric fuzzy predictive control of a generalised energy storage device

Sweeping power system stabilisation with a parametric fuzzy predictive control of a generalised energy storage device

Integration of fast acting energy storage systems in existing pumped‐storage power plants to enhance the system's frequency control

Battery SOC management strategy for enhanced frequency response and day-ahead energy scheduling of BESS for energy arbitrage

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