Research Project

INCITE: Innovative controls for renewable sources integration into smart energy systems

Type

European Project

Start Date

01/12/2015

End Date

30/11/2019

Project Code

H2020-MSCA-ITN-675318

Project illustration

Staff

Project Description

The advances in communication and information networks and the wide availability of powerful and cheap computers have transformed many aspects of our lives. The electrical networks are not an exception. New smart meters, distributed generation, renewable energy sources and the concern about the environment are redefining electrical networks. Now, both consumers and generators are active agents that are capable of coordinating the extraction and injection of power into the electrical grid depending on the energy cost, energy availability and even the behavior of electrical variables. This new reality is a great opportunity to improve energy efficiency and reduce CO2 footprints by using clean energy sources. But it is also a big challenge. The electrical network is one of the most complex systems ever made, with this new reality the additional controllability and the great number of actors may lead to undesirable results and even to network outages.

In order to take full advantage of these new electrical networks, it is necessary a coordinated and harmonic interaction among all actors in the network. This is the role of the control algorithms, thought to act at several levels to conduct the extraction and injection of the electrical power and improve efficiency, reliability and resilience of the network. INCITE aims to this target, to propose new control algorithms with an integral view of the future electrical networks, covering aspects like energy management, stability of electrical variables, monitoring and communication implementation, energy storage, among others. The objective is to create an interdisciplinary (control, electrical and management fields), cross-sectorial (academic and industry) and international research environment in which 14 young researchers propose innovative control solution for the future energy networks.

Project Publications

Journal Publications

  • W. Ananduta, T.M. Pippia, C. Ocampo-Martínez, J. Sijs and B. De Schutter. Online partitioning method for decentralized control of linear switching large-scale systems. Journal of Franklin Institute, 2019, to appear.

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  • T. Péan, J. Salom and R. Costa Castelló. Review of control strategies for improving the energy flexibility provided by heat pump systems in buildings. Journal of Process Control, 2019, to appear.

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  • S. Siniscalchi, F. Bianchi, M. De Prada and C. Ocampo-Martínez. A wind farm control strategy for power reserve maximization. Renewable Energy, 131: 37-44, 2019.

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  • W. Ananduta, J. Barreiro, C. Ocampo-Martínez and N. Quijano. Mitigation of communication failures in distributed model predictive control strategies. IET Control Theory and Applications, 12(18): 2507-2515, 2018.

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Conference Publications

  • U. Raveendran Nair, R. Costa Castelló and German A. Ramos. An adaptive disturbance rejection control scheme for voltage regulation in DC micro-grids, 20th IEEE International Conference on Industrial Technology, 2019, Melbourne, Australia, IEEE, to appear.

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  • T. Péan, J. Salom and R. Costa Castelló. Configurations of model predictive control to exploit energy flexibility in building thermal loads, 57th IEEE Conference on Decision and Control, 2018, Miami, pp. 3177-3182.

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  • S. Siniscalchi, M. De Prada, F. Bianchi, C. Ocampo-Martínez and B. De Schutter. A multi-objective predictive control strategy for enhancing primary frequency support with wind farms, 2018 The Science of Making Torque from Wind, 2018, Milano, Italy, Vol 1037 of Journal of Physics: Conference Series, pp. 032034, 2018.

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  • S. Siniscalchi, C. Ocampo-Martínez, F. Bianchi, M. De Prada and B. De Schutter. Partitioning approach for large wind farms: Active power control for optimizing power reserve, 57th IEEE Conference on Decision and Control, 2018, Miami, pp. 3183-3188.

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  • S. Siniscalchi, F. Bianchi and C. Ocampo-Martínez. Predictive control of wind farms based on lexicographic minimizers for power reserve maximization, 2018 American Control Conference, 2018, Milwaukee, USA, pp. 701-706.

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  • W. Ananduta, J. Barreiro, C. Ocampo-Martínez and N. Quijano. Resilient information-exchange protocol for distributed model predictive control schemes, 2018 American Control Conference, 2018, Milwaukee, USA, pp. 1286-1291.

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  • W. Ananduta, J.M. Maestre, C. Ocampo-Martínez and H. Ishii. Resilient distributed energy management for systems of interconnected microgrids, 57th IEEE Conference on Decision and Control, 2018, Miami, pp. 3159-3164.

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  • U. Raveendran Nair, R. Costa Castelló and A. Baños. Reset control of boost converters, 2018 American Control Conference, 2018, Milwaukee, USA, pp. 553-558.

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  • U. Raveendran Nair and R. Costa Castelló. An overview of micro-grid architecture with hybrid storage elements and its control, XV Simposio CEA de Ingeniería de Control, 2017, Salamanca, pp. 17-23.

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  • S. Siniscalchi, F. Bianchi, C. Ocampo-Martínez and M. De Prada. A wind farm operational strategy for primary frequency support optimization, 2017 Wind Europe Conference and Exhibition, 2017, Amsterdam, pp. PO.061.

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