Conversion loss modeling plays a crucial role in hybrid AC/DC microgrid (MG) energy management (EM). However, accurate calculation of the conversion losses is often very costly. Additionally, existing surrogate models typically rely on fixed-voltage DC buses, leading to excessive voltage magnitudes. To overcome these limitations, we propose surrogate models based on piecewise linear neural networks (NNs) that estimate conversion losses using converter power and variable-voltage DC buses.

DOI Link: 
10.21227/n4x4-yg82
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[1] Xuan Liu, "More Efficient Energy Management for Hybrid AC/DC Microgrids with Hard Constrained Neural Network-Based Conversion Loss Surrogate Models", IEEE Dataport, 2023. [Online]. Available: http://dx.doi.org/10.21227/n4x4-yg82. Accessed: Mar. 15, 2025.
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doi = {10.21227/n4x4-yg82},
url = {http://dx.doi.org/10.21227/n4x4-yg82},
author = {Xuan Liu },
publisher = {IEEE Dataport},
title = {More Efficient Energy Management for Hybrid AC/DC Microgrids with Hard Constrained Neural Network-Based Conversion Loss Surrogate Models},
year = {2023} }
TY - DATA
T1 - More Efficient Energy Management for Hybrid AC/DC Microgrids with Hard Constrained Neural Network-Based Conversion Loss Surrogate Models
AU - Xuan Liu
PY - 2023
PB - IEEE Dataport
UR - 10.21227/n4x4-yg82
ER -
Xuan Liu. (2023). More Efficient Energy Management for Hybrid AC/DC Microgrids with Hard Constrained Neural Network-Based Conversion Loss Surrogate Models. IEEE Dataport. http://dx.doi.org/10.21227/n4x4-yg82
Xuan Liu, 2023. More Efficient Energy Management for Hybrid AC/DC Microgrids with Hard Constrained Neural Network-Based Conversion Loss Surrogate Models. Available at: http://dx.doi.org/10.21227/n4x4-yg82.
Xuan Liu. (2023). "More Efficient Energy Management for Hybrid AC/DC Microgrids with Hard Constrained Neural Network-Based Conversion Loss Surrogate Models." Web.
1. Xuan Liu. More Efficient Energy Management for Hybrid AC/DC Microgrids with Hard Constrained Neural Network-Based Conversion Loss Surrogate Models [Internet]. IEEE Dataport; 2023. Available from : http://dx.doi.org/10.21227/n4x4-yg82
Xuan Liu. "More Efficient Energy Management for Hybrid AC/DC Microgrids with Hard Constrained Neural Network-Based Conversion Loss Surrogate Models." doi: 10.21227/n4x4-yg82