Dynamic Droop Control for Optimal Power Sharing in Renewable Rich Hybrid Islanded Microgrids

A stepwise optimal droop control method is designed in this paper to enhance the integration of renewable energy sources (RES) and ensure economical power sharing among dispatchable sources. This novel control strategy prioritizes the use of RES, thereby promoting a cleaner and more sustainable energy mix. Following this prioritization, the method utilizes an incremental cost droop control mechanism to optimize power and decrease the generation cost of the overall system. Additionally, an adaptive gradient parameter is introduced in cost-based droop control to fully exploit the potential of dispatchable sources while maintaining system frequency stability. This adaptive feature ensures the system's stability even if any dispatchable source reaches its maximum capacity. It dynamically removes that source from the incremental cost droop control, allowing the remaining sources to continue following the equal incremental cost criteria. This adaptive feature allows the system to respond dynamically to fluctuating demand and supply conditions, ensuring optimal performance and reliability.

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Publication Details

Published
2024-12-18
DOI
https://doi.org/10.1109/pedes61459.2024.10960870
Citations
2
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.66
Controls
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article

Dynamic Droop Control for Optimal Power Sharing in Renewable Rich Hybrid Islanded Microgrids

Amit Kumar Gupta, P. C. Sekhar
2 citations
Microgrid Control and Optimization
0.66
article

Dynamic Droop Control for Optimal Power Sharing in Renewable Rich Hybrid Islanded Microgrids

Amit Kumar Gupta, P. C. Sekhar
article en
2 citations

Abstract

A stepwise optimal droop control method is designed in this paper to enhance the integration of renewable energy sources (RES) and ensure economical power sharing among dispatchable sources. This novel control strategy prioritizes the use of RES, thereby promoting a cleaner and more sustainable energy mix. Following this prioritization, the method utilizes an incremental cost droop control mechanism to optimize power and decrease the generation cost of the overall system. Additionally, an adaptive gradient parameter is introduced in cost-based droop control to fully exploit the potential of dispatchable sources while maintaining system frequency stability. This adaptive feature ensures the system's stability even if any dispatchable source reaches its maximum capacity. It dynamically removes that source from the incremental cost droop control, allowing the remaining sources to continue following the equal incremental cost criteria. This adaptive feature allows the system to respond dynamically to fluctuating demand and supply conditions, ensuring optimal performance and reliability.

Indian Institute of Technology Bhubaneswar (IN)
Affordable and clean energy
Openalex Percentile: Top 27%
Microgrid Control and Optimization
0.66
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