
When
Event Type
Battery Energy Storage Systems (BESS) represent a significant investment. Are you capturing maximum value from your assets? Join us to discover how sophisticated trading strategies and automation can dramatically increase your returns while maintaining battery health.
Key challenges we’ll address:Â
- State of Charge Management:Â Unlike traditional generation, BESS requires strategic charging cycles for optimal dispatch
- Revenue Co-Optimization:Â Balancing energy arbitrage with ancillary services to maximize overall returns
- Real-Time Market Adaptability:Â Responding effectively to rapidly shifting market conditions
- Decision-Making Under Uncertainty:Â Creating profitable hedging strategies despite price forecast variability
- Automated Market Participation:Â Tools for seamless offer submissions as forecasts update
- Evolving Market Rules:Â Staying compliant while maximizing opportunities in changing markets
Join Dwaraknaath Varadharajan in navigating the challenges on BESS participating in today’s Energy markets and understand how PCI BatteryTrader could help you in this process.
Here’s what you’ll learn:Â
- Revenue stream optimization across major ISO/RTO markets
- PCI’s AI/ML-based market price forecasting methodology
- Essential input parameters for effective co-optimization
- How to select, test, and implement the right trading strategies for DA and RT markets
- Key performance indicators and metrics specific to BESS operations
Who will benefit from this webinar:Â Â
- Battery Asset Owners/Operators: Stand-alone, hybrid, and co-located storage facilities
- Market Traders: DA and RT operators submitting offers into ISOs/RTOs
- Energy Analysts: Professionals evaluating trading strategy effectiveness
- Revenue Optimization Teams: Those seeking to balance maximum returns with battery longevity
Speakers:Â
Dwaraknaath Varadharajan brings over more than five years of expertise in the energy industry and software development, having been an integral member of PCI since May 2019. Currently serving as the Product Manager for the BatteryTrader and Forecaster products, Dwaraknaath leads initiatives to enhance our capabilities and drive strategic development of products. Dwaraknaath’s skillset encompasses proficiency in multiple programming languages, generative AI, machine learning, business intelligence, and cloud software development. Dwaraknaath holds a master of science in electrical engineering with a specialized focus on power systems and minor focus on statistics from North Carolina State University.