Predictive energy management for a wind turbine with hybrid energy storage system

Summary Hybrid energy storage systems (HESSs) help mitigating the fluctuations and variable availability of certain renewable sources, such as wind power, as they can provide support in different time scales. Therefore, regulating their state‐of‐charge (SOC) becomes crucial to ensure that the hybrid...

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Veröffentlicht in:International journal of energy research 2020-03, Vol.44 (3), p.2316-2331
Hauptverfasser: González‐Rivera, Enrique, Sarrias‐Mena, Raúl, García‐Triviño, Pablo, Fernández‐Ramírez, Luis M.
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container_issue 3
container_start_page 2316
container_title International journal of energy research
container_volume 44
creator González‐Rivera, Enrique
Sarrias‐Mena, Raúl
García‐Triviño, Pablo
Fernández‐Ramírez, Luis M.
description Summary Hybrid energy storage systems (HESSs) help mitigating the fluctuations and variable availability of certain renewable sources, such as wind power, as they can provide support in different time scales. Therefore, regulating their state‐of‐charge (SOC) becomes crucial to ensure that the hybrid system complies with generation commitments agreed in time‐ahead markets despite subsequent unexpected wind speed variations. So far, research has been mainly targeted at avoiding extreme SOC situations in the storage devices, whereas the regulation of this parameter to specific values has often been disregarded. A novel approach is proposed in this work, where model predictive control (MPC) is used to regulate the SOC of a HESS under variable wind and grid demand scenarios. The MPC‐based supervisory controller developed for the hybrid system has been implemented and simulated under different situations. This controller monitors the future variation of the SOC with the aim of having the HESS available to develop its assigned functions successfully. The results show that a proper regulation of the SOC in the HESS increases the capacity to manage the active power supplied to the grid by the hybrid system based on wind power, as well as the level of compliance with generation commitments established time ahead. Regulating the SOC of the energy storage devices increases their availability and facilitates a smart energy management in the hybrid system. Using a predictive algorithm, the SOC of the UC is controlled to a defined value, not being introduced simply as a constraint in the supervisory control system. The amount of backup energy is actively controlled, not depending uniquely on the operating and environmental conditions. Anticipating the energy stored in the HESS allows operating the hybrid system in time‐ahead markets similarly to traditional power plants.
doi_str_mv 10.1002/er.5082
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Therefore, regulating their state‐of‐charge (SOC) becomes crucial to ensure that the hybrid system complies with generation commitments agreed in time‐ahead markets despite subsequent unexpected wind speed variations. So far, research has been mainly targeted at avoiding extreme SOC situations in the storage devices, whereas the regulation of this parameter to specific values has often been disregarded. A novel approach is proposed in this work, where model predictive control (MPC) is used to regulate the SOC of a HESS under variable wind and grid demand scenarios. The MPC‐based supervisory controller developed for the hybrid system has been implemented and simulated under different situations. This controller monitors the future variation of the SOC with the aim of having the HESS available to develop its assigned functions successfully. The results show that a proper regulation of the SOC in the HESS increases the capacity to manage the active power supplied to the grid by the hybrid system based on wind power, as well as the level of compliance with generation commitments established time ahead. Regulating the SOC of the energy storage devices increases their availability and facilitates a smart energy management in the hybrid system. Using a predictive algorithm, the SOC of the UC is controlled to a defined value, not being introduced simply as a constraint in the supervisory control system. The amount of backup energy is actively controlled, not depending uniquely on the operating and environmental conditions. 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source Wiley Online Library Journals Frontfile Complete
subjects Computer simulation
Control
Controllers
Energy
Energy management
energy management system
Energy storage
hybrid energy storage system
Hybrid systems
hydrogen storage
Predictive control
Renewable energy
Storage systems
supervisory control system
Turbine engines
Turbines
ultracapacitor
Variation
Wind power
Wind speed
Wind turbines
title Predictive energy management for a wind turbine with hybrid energy storage system
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