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.
Authors
- Abdallah Mohammed (ORCID: https://orcid.org/0000-0002-2088-8831)
- Rasha Elazab (ORCID: https://orcid.org/0000-0002-6251-2322)
- Eman Kamal Sakr
- Maged Abo-Adma
Institutions
- Helwan University (EG)
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
Funders
- Science and Technology Development Fund
- Helwan University