Renewable Integration & Optimization Essentials Training by Tonex
Integrating high shares of renewables in microgrids requires sophisticated forecasting, control, and optimization to manage variability and ensure reliability. This advanced course explores DER modeling, forecasting techniques, stochastic optimization, DERMS, and VPP strategies. Participants learn to co-optimize renewables, storage, and demand response using advanced simulation frameworks and case-based learning.
Learning Objectives
- Model and forecast PV, wind, and hybrid DER generation.
- Implement forecasting techniques using statistical and ML-based methods.
- Apply stochastic and robust optimization for uncertain renewables.
- Integrate storage, renewables, and flexible demand for optimal operation.
- Design DERMS and virtual power plant (VPP) architectures.
- Balance system reliability with high renewable penetration.
Audience
- Renewable energy engineers and planners
- Microgrid system designers and operators
- EMS/DERMS developers
- Research and R&D professionals in smart grids
2-Day Agenda
Day 1 – Renewable Modeling & Control
- Modeling PV, wind, and other DERs for microgrid integration
- Forecasting techniques: time-series, machine learning, ensemble forecasting
- Intermittency management: ramp-rate control, curtailment, synthetic inertia
- Hands-on: PV and wind forecasting + integration simulation
Day 2 – Optimization & Advanced System Integration
- Stochastic and robust optimization frameworks for renewables
- Co-optimization of renewables, storage, and demand response
- DER aggregation, VPP architectures, and DERMS platforms
- Case study: Designing a renewable-dominated microgrid for islanded operation
- Hands-on: Optimization lab using real-world renewable profiles