A Novel Internet of Energy Based Optimal Multi-Agent Control Scheme for Microgrid including Renewable Energy Resources

Bilal Naji Alhasnawi, Basil H. Jasim, Zain-Aldeen S. A. Rahman, Josep M. Guerrero and M. Dolores Esteban
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Bilal Naji Alhasnawi: Electrical Engineering Department, University of Basrah, Basrah 61001, Iraq
Basil H. Jasim: Electrical Engineering Department, University of Basrah, Basrah 61001, Iraq
Zain-Aldeen S. A. Rahman: Electrical Engineering Department, University of Basrah, Basrah 61001, Iraq
Josep M. Guerrero: Center for Research on Microgrids (CROM), Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark
M. Dolores Esteban: Civil Engineering Department, Hydraulics, Energy and Environment/Profesor Aranguren 3, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain

IJERPH, 2021, vol. 18, issue 15, 1-24

Abstract: The increasing integration of Renewable Energy Resources (RERs) in distribution networks forms the Networked Renewable Energy Resources (NRERs). The cooperative Peer-to-Peer (P2P) control architecture is able to fully exploit the resilience and flexibility of NRERs. This study proposes a multi-agent system to achieve P2P control of NRERs based Internet of Things (IoT). The control system is fully distributed and contains two control layers operated in the agent of each RER. For primary control, a droop control is adopted by each RER-agent for localized power sharing. For secondary control, a distributed diffusion algorithm is proposed for arbitrary power sharing among RERs. The proposed levels communication system is implemented to explain the data exchange between the distribution network system and the cloud server. The local communication level utilizes the Internet Protocol (IP)/Transmission Control Protocol (TCP), and Message Queuing Telemetry Transport (MQTT) is used as the protocol for the global communication level. The effectiveness of the proposed system is validated by numerical simulation with the modified IEEE 9 node test feeder. The controller proposed in this paper achieved savings of 20.65% for the system, 25.99% for photovoltaic, 35.52 for diesel generator, 24.59 for batteries, and 52.34% for power loss.

Keywords: renewable energy resources; diffusion algorithm; IoT; IEEE microgrid; cooperative control; cloud platform (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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