Autonomous control of DC microgrid based on a hybrid droop control scheme for total generation cost and transmission power loss reduction

Saeidinia, Y.; Arabshahi, M. R.; Mousavi, Seyyed Yousef Mousazadeh; Biglari, Manochehr

doi:10.1007/s00202-022-01662-w

Cited by 11 publications

(15 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method aims to optimize power-sharing in an MG while minimizing transmission line power losses. Equation ( 8) defines this function, where P Loss,i denotes the transmission line power loss and I i represents the injecting current of the i th DG, with R L,i denoting the resistance of the line connecting the load bus to the i th DG [37].…”

Section: Loss-based Droop Methodsmentioning

confidence: 99%

“…As a result, it is possible to reduce the PC without the need for any communication infrastructure. The following equation is utilized to calculate the PC of the DC MG with n number of inputs [37]:…”

Section: Ic D Techniquementioning

confidence: 99%

“…This helps minimize the PC without requiring any communication infrastructure. This approach is formulated as follows [37]:…”

Section: Ic D Techniquementioning

confidence: 99%

“…This means that each DG is given priority based on its cost-to-value ratio relative to the most expensive unit. Equation (7) ensures economic validity in the mentioned method by maintaining voltage equality among the DGs [37].…”

Section: Ic D Techniquementioning

confidence: 99%

“…In reference [35], a frequency‐based control method with an embedded cost‐based criterion was suggested. Meanwhile, studies such as [34] and [37] demonstrated that by appropriately selecting weighting and scaling factors, the

{C}_D

scheme can significantly diminish the production cost (PC) in comparison to the classical droop method.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Enhancing DC microgrid performance through machine learning‐optimized droop control

Saeidinia,

Arabshahi,

Aminirad

et al. 2024

IET Generation Trans & Dist

View full text Add to dashboard Cite

A machine learning‐based optimized droop method is suggested here to simultaneously reduce the production cost (PC) and power line losses (PLL) for a class of direct current (DC) microgrids (MGs). Traditionally, a communication‐less technique known as the hybrid droop method has been employed to decrease PC and PLL in DC MGs. However, achieving the desired reduction in either PC or PLL requires arbitrary adjustments of weighting coefficients for each distributed generator in the conventional hybrid droop method. To address this challenge, this paper introduces a systematic approach that capitalizes on the benefits of artificial intelligence to accurately predict both the PC and PLL in a DC MG. Furthermore, an optimization technique relying on the gradient descendent method is employed to independently optimize both PC and PLL for each scenario. The effectiveness of the proposed method is confirmed through a comparative study with classical and hybrid droop coordination schemes under various scenarios such as rapid load changes.

show abstract

Section: Loss-based Droop Methodsmentioning

confidence: 99%

Section: Ic D Techniquementioning

confidence: 99%

“…This helps minimize the PC without requiring any communication infrastructure. This approach is formulated as follows [37]:…”

Section: Ic D Techniquementioning

confidence: 99%

Section: Ic D Techniquementioning

confidence: 99%