Experimental study of mini SCADA renewable energy management system on microgrid using Raspberry Pi

Tridianto, Erik; Permatasari, Prima Dewi; Ali, Ikbal

doi:10.1088/1742-6596/983/1/012061

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…A renewable energy management system (REMS) is a gadget that monitors power in a microgrid. The goal of this system is to optimize power utilization generated by renewable energy, reducing power demand from the grid [21], [22]. However, due to the massive communication and computation requirements of linked power systems across a large region, it is challenging to implement a centralized REMS strategy.…”

Section: Introductionmentioning

confidence: 99%

Multi-microgrids system’s resilience enhancement

Chalah,

Belaidi

2024

IJEECS

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Nowadays, electricity consumption is increasing rapidly which leads to conventional power systems exhaustion. Therefore, micro-grids (MGs) implantation can enhance the resilience of power systems by implication of new resources, such as renewable energy sources (solar panel and wind power systems), electric vehicles (EV), and energy storage systems (ESS). This paper proposes a new strategy for optimal power consumption inside one microgrid; then, the approach will be extended to optimize the power consumption to enhance the resilience in the case of multi-MGs systems. The system controller of each microgrid has been implemented using ESP32 microcontroller and Raspberry IP4. The proposed approach intends to enhance the resilience of the system to react to any contingency in the system such as loss of power linkage between MG and the network in case of any natural disaster, especially in the rural area. Two controllers are implemented; the first one ensures MG autonomy by the efficient use of its own sources. The second one handles the system resilience cases by demanding/delivering power from/into neighbor microgrids. Hence, this work enhances the system resilience with an optimal cost. Thus, the MG can offer ancillary services for the neighboring MGs.

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Section: Introductionmentioning

confidence: 99%