A probabilistic multi objective decision framework for reactive power planning in der integrated microgrids enhancing sustainability and resilience in the egyptian grid

The integration of high-penetration Distributed Energy Resources (DERs) into conventional grids is pivotal for de-carbonization but introduces significant stability challenges. This study addresses voltage violations and feeder congestion in Egyptian distribution networks using a probabilistic four-dimensional multi-objective optimization framework that supports Sustainable Development Goals (SDGs) 7 (Affordable and Clean Energy) and 13 (Climate Action). The methodology combines the Two-Point Estimation Method (2PEM) for uncertainty quantification with the NSGA-II algorithm to optimize technical, economic, environmental, and social objectives for an IEEE 33-bus test system. Results demonstrate that optimal DER sizing alone is insufficient and that dedicated reactive power planning is essential. Among five evaluated planning strategies, a hybrid configuration of inverters and D-STATCOMs delivers superior performance. This optimal scenario achieves the best voltage profile (0.975 p.u.), the highest annual loss savings ($61,900), and creates 52 per MW at full-time equivalent jobs, thereby advancing SDG 8 (Decent Work and Economic Growth) while reducing grid dependency to 22%. Although it requires a higher initial investment, its techno-economic and social benefits justify adoption for strengthening modern grids. The study provides a critical decision-support framework for policymakers to enhance the resilience and sustainability of renewable-integrated power systems in Egypt and similar emerging economies.

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Publication Details

Journal
Scientific Reports
Published
2026-08-20
DOI
https://doi.org/10.1038/s41598-026-66944-w
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
0.00

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article

A probabilistic multi objective decision framework for reactive power planning in der integrated microgrids enhancing sustainability and resilience in the egyptian grid

Abdallah Mohammed, Rasha Elazab, Eman Kamal Sakr, Maged Abo-Adma
Scientific Reports
Optimal Power Flow Distribution
article

A probabilistic multi objective decision framework for reactive power planning in der integrated microgrids enhancing sustainability and resilience in the egyptian grid

Abdallah Mohammed, Rasha Elazab, Eman Kamal Sakr, Maged Abo-Adma
article en

Abstract

The integration of high-penetration Distributed Energy Resources (DERs) into conventional grids is pivotal for de-carbonization but introduces significant stability challenges. This study addresses voltage violations and feeder congestion in Egyptian distribution networks using a probabilistic four-dimensional multi-objective optimization framework that supports Sustainable Development Goals (SDGs) 7 (Affordable and Clean Energy) and 13 (Climate Action). The methodology combines the Two-Point Estimation Method (2PEM) for uncertainty quantification with the NSGA-II algorithm to optimize technical, economic, environmental, and social objectives for an IEEE 33-bus test system. Results demonstrate that optimal DER sizing alone is insufficient and that dedicated reactive power planning is essential. Among five evaluated planning strategies, a hybrid configuration of inverters and D-STATCOMs delivers superior performance. This optimal scenario achieves the best voltage profile (0.975 p.u.), the highest annual loss savings ($61,900), and creates 52 per MW at full-time equivalent jobs, thereby advancing SDG 8 (Decent Work and Economic Growth) while reducing grid dependency to 22%. Although it requires a higher initial investment, its techno-economic and social benefits justify adoption for strengthening modern grids. The study provides a critical decision-support framework for policymakers to enhance the resilience and sustainability of renewable-integrated power systems in Egypt and similar emerging economies.

Scientific ReportsVol. 16(1)
Helwan University (EG)
Science and Technology Development Fund, Helwan University
Openalex Percentile: Top 19%
Optimal Power Flow Distribution
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