Dynamic optimization of shared storage for renewable driven grids with insights from Egypt.

Area of Science:

• Energy Systems Engineering
• Renewable Energy Integration
• Optimization Algorithms

Background:

• Egypt's renewable energy sector faces challenges with integrating variable sources like solar and wind.
• Existing Shared Energy Storage (SES) models often use fixed allocations or fully cooperative approaches, limiting flexibility.
• There is a need for adaptive frameworks that can respond to dynamic grid conditions and market signals.

Purpose of the Study:

• To develop and evaluate an adaptive Shared Energy Storage (SES) framework for Egypt's renewable energy landscape.
• To enable flexible, real-time leasing of centralized SES units by multiple renewable energy producers.
• To enhance grid reliability and economic resilience through improved storage utilization.

Main Methods:

• Integration of dynamic SES partitioning and Nash bargaining-based cooperation.
• Application of a distributed Alternating Direction Method of Multipliers (ADMM) optimization algorithm.
• Simulation analysis comparing the adaptive SES framework with fixed-allocation models under various operational scenarios.

Main Results:

• The adaptive SES framework increased storage utilization by over 40% compared to fixed allocation.
• The system demonstrated economic viability and stable operation despite forecast uncertainty and battery degradation.
• Equitable benefit sharing was achieved between producers and the SES operator via the Nash bargaining mechanism.

Conclusions:

• The adaptive SES framework effectively enhances renewable integration and grid reliability in emerging energy systems.
• The market-aware SES model supports Egypt's Vision 2035 by improving economic resilience.
• The distributed ADMM algorithm ensures scalable and near-real-time coordination for SES deployment.