As solar PV installations and electric vehicles (EVs) continue to grow, our distribution networks are facing new challenges — from higher peak demand and voltage instability to increased power losses.
To tackle these challenges, Battery Energy Storage Systems (BESS) are emerging as a key enabler for a more resilient and efficient power grid.
The Research
A recent IEEE study explored how optimal placement and sizing of BESS can enhance grid stability and reduce system costs.
Three advanced optimization algorithms were tested:
- PSO (Particle Swarm Optimization)- Excellent for technical optimization — like improving voltage profile, reducing losses, and peak shaving. Stable, proven, and widely used in power systems
- AVOA (African Vultures Optimization Algorithm)- Strong in economic optimization — finds solutions with faster payback periods or lower investment cost.
- SSA (Salp Swarm Algorithm)- Fast computation speed — finds good (though not always perfect) solutions quickly.
The systems were tested on IEEE 33 & 69 bus networks to evaluate performance across various scenarios.
Key Findings
- PSO delivered the best technical performance, improving voltage profile, reducing losses, and enabling effective peak shaving.
- AVOA achieved the fastest payback period, proving beneficial for projects focused on ROI.
- SSA offered the fastest computation time, ideal for large-scale simulation and rapid analysis.
The Takeaway
Smart optimization means smarter BESS investments. Depending on the project goal — technical performance, financial return, or computation speed — different algorithms can deliver the best results.
As renewable energy and EV adoption accelerate, strategic BESS planning will be crucial for creating stable, efficient, and future-ready power grids.
Reference:
Optimal Placement and Capacity of Battery Energy Storage System in Distribution Networks Integrated With PV and EVs Using Metaheuristic Algorithms.
IEEE Access — Read Here
Also read: Ultra-Fast EV Charging: A New Load Challenge to the Grid (EPR Magazine)
