scholarly journals DC Microgrid Utilizing Artificial Intelligence and Phasor Measurement Unit Assisted Inverter

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6086
Author(s):  
Raziq Yaqub ◽  
Mohamed Ali ◽  
Hassan Ali

Community microgrids are set to change the landscape of future energy markets. The technology is being deployed in many cities around the globe. However, a wide-scale deployment faces three major issues: initial synchronization of microgrids with the utility grids, slip management during its operation, and mitigation of distortions produced by the inverter. This paper proposes a Phasor Measurement Unit (PMU) Assisted Inverter (PAI) that addresses these three issues in a single solution. The proposed PAI continually receives real-time data from a Phasor Measurement Unit installed in the distribution system of a utility company and keeps constructing a real-time reference signal for the inverter. To validate the concept, a unique intelligent DC microgrid architecture that employs the proposed Phasor Measurement Unit (PMU) Assisted Inverter (PAI) is also presented, alongside the cloud-based Artificial Intelligence (AI), which harnesses energy from community shared resources, such as batteries and the community’s rooftop solar resources. The results show that the proposed system produces quality output and is 98.5% efficient.

Electricity ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 330-341
Author(s):  
Raziq Yaqub

DC microgrids are set to change the landscape of future energy markets. However, a wide-scale deployment faces three major issues: initial synchronization of microgrid with the utility grid, slip management during its operation, and mitigation of distortions produced by the inverter. This paper proposes a Phasor Measurement Unit (PMU) Assisted Inverter (PAI) that addresses these three issues in a single solution. The proposed PAI continually receives real-time data from a Phasor Measurement Unit installed in the distribution system of a utility company and keeps constructing a real-time reference signal for the inverter. A well-constructed, real-time reference signal plays a vital role in addressing the above issues. The results show that the proposed PAI is 97.95% efficient.


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