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TY - JOUR AU - Shaterabadi, Mohammad PY - 2025 DA - 2025/12/10 TI - Stochastic Optimal Energy Planning of the Multi-connected Grids by the Presence of Bi-facial PV Panels: Interaction of Micro-nano and Main Grid JO - Sustainable Energy Control and Optimization T2 - Sustainable Energy Control and Optimization JF - Sustainable Energy Control and Optimization VL - 1 IS - 2 SP - 53 EP - 60 DO - 10.62762/SECO.2025.864874 UR - https://www.icck.org/article/abs/SECO.2025.864874 KW - bi-facial photovoltaic (BPV) KW - energy management (EM) KW - multi-grids optimization (MGO) KW - renewable energy sources (RES) KW - solar energy AB - The increasing greenhouse gas (GHG) emissions from fossil fuel-based energy systems have accelerated the global push toward cleaner technologies. Bi-facial photovoltaic (BPV) panels, capable of capturing solar irradiance from both sides, have emerged as a promising solution due to their higher energy yield and comparable costs to traditional PV systems. This paper explores the integration of BPV panels into a multi-connected grid comprising nano-, micro-, and main grid layers. A stochastic optimization framework is developed to address the uncertainties of solar irradiance. The problem is formulated as a Mixed-Integer Linear Programming (MILP) model and solved using the Augmented Epsilon Constraint (AEC) method in the General Algebraic Modeling System (GAMS) environment. Results demonstrate that incorporating BPV panels reduces microgrid operational costs by approximately 20%, boosts nano-grid profits by about 81%, and cuts emissions by about 10%, highlighting their potential to enhance system efficiency, flexibility, and sustainability. SN - 3068-7330 PB - Institute of Central Computation and Knowledge LA - English ER -
@article{Shaterabadi2025Stochastic,
author = {Mohammad Shaterabadi},
title = {Stochastic Optimal Energy Planning of the Multi-connected Grids by the Presence of Bi-facial PV Panels: Interaction of Micro-nano and Main Grid},
journal = {Sustainable Energy Control and Optimization},
year = {2025},
volume = {1},
number = {2},
pages = {53-60},
doi = {10.62762/SECO.2025.864874},
url = {https://www.icck.org/article/abs/SECO.2025.864874},
abstract = {The increasing greenhouse gas (GHG) emissions from fossil fuel-based energy systems have accelerated the global push toward cleaner technologies. Bi-facial photovoltaic (BPV) panels, capable of capturing solar irradiance from both sides, have emerged as a promising solution due to their higher energy yield and comparable costs to traditional PV systems. This paper explores the integration of BPV panels into a multi-connected grid comprising nano-, micro-, and main grid layers. A stochastic optimization framework is developed to address the uncertainties of solar irradiance. The problem is formulated as a Mixed-Integer Linear Programming (MILP) model and solved using the Augmented Epsilon Constraint (AEC) method in the General Algebraic Modeling System (GAMS) environment. Results demonstrate that incorporating BPV panels reduces microgrid operational costs by approximately 20\%, boosts nano-grid profits by about 81\%, and cuts emissions by about 10\%, highlighting their potential to enhance system efficiency, flexibility, and sustainability.},
keywords = {bi-facial photovoltaic (BPV), energy management (EM), multi-grids optimization (MGO), renewable energy sources (RES), solar energy},
issn = {3068-7330},
publisher = {Institute of Central Computation and Knowledge}
}
Copyright © 2025 by the Author(s). Published by Institute of Central Computation and Knowledge. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 
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