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

被引:39
|
作者
Alhasnawi, Bilal Naji [1 ]
Jasim, Basil H. [1 ]
Rahman, Zain-Aldeen S. A. [1 ,2 ]
Guerrero, Josep M. [3 ]
Esteban, M. Dolores [4 ]
机构
[1] Univ Basrah, Elect Engn Dept, Basrah 61001, Iraq
[2] Southern Tech Univ, Qurna Tech Inst, Dept Elect Tech, Basra 61016, Iraq
[3] Aalborg Univ, Ctr Res Microgrids CROM, Dept Energy Technol, DK-9220 Aalborg, Denmark
[4] Univ Politecn Madrid UPM, Civil Engn Dept, Hydraul Energy & Environm, Prof Aranguren 3, Madrid 28040, Spain
关键词
renewable energy resources; diffusion algorithm; IoT; IEEE microgrid; cooperative control; cloud platform; SMART MICROGRIDS; SYSTEMS;
D O I
10.3390/ijerph18158146
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
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页数:24
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