Virtual Power Plants (VPPs) Training Course
Virtual Power Plants (VPPs) Training Course provides a practical and strategic understanding of VPP architecture, distributed energy resource aggregation, demand response, energy flexibility, grid-interactive technologies, energy markets, AI-driven optimization, IoT connectivity, and real-time energy management.
Course Overview
Virtual Power Plants (VPPs) Training Course
Introduction
Virtual Power Plants (VPPs) are transforming modern energy systems by aggregating distributed energy resources (DERs) such as solar PV, battery energy storage systems (BESS), electric vehicles (EVs), smart loads, and flexible generation into intelligent, digitally coordinated power portfolios. Virtual Power Plants (VPPs) Training Course provides a practical and strategic understanding of VPP architecture, distributed energy resource aggregation, demand response, energy flexibility, grid-interactive technologies, energy markets, AI-driven optimization, IoT connectivity, and real-time energy management. Participants will explore how VPPs improve grid reliability, renewable energy integration, resilience, flexibility, and economic value.
Through practical exercises and real-world case studies, learners will examine how VPP platforms coordinate thousands of distributed assets and participate in ancillary services, frequency regulation, capacity markets, demand-side management, energy trading, and grid balancing. The course also addresses cybersecurity, interoperability, forecasting, regulatory frameworks, business models, and emerging VPP trends, enabling participants to evaluate, design, manage, and scale VPP projects in rapidly evolving electricity markets.
Course Duration
5 days
Course Objectives
- Understand VPP architecture, DER aggregation, and grid flexibility.
- Analyze distributed energy resources and their operational characteristics.
- Design VPP strategies for renewable energy integration and grid balancing.
- Apply AI, machine learning, and predictive analytics to VPP optimization.
- Understand battery energy storage integration and optimization.
- Evaluate demand response and flexible-load management strategies.
- Explore EV charging, vehicle-to-grid (V2G), and EV flexibility.
- Understand real-time energy management and digital grid technologies.
- Evaluate participation in energy, capacity, and ancillary-service markets.
- Develop VPP business models, revenue streams, and investment strategies.
- Identify cybersecurity, data governance, interoperability, and resilience requirements.
- Analyze international VPP regulations, policies, standards, and market frameworks.
- Develop practical strategies for VPP deployment, scalability, decarbonization, and net-zero energy systems.
Target Audience
- Energy utility and electricity-grid professionals
- Renewable energy and solar PV professionals
- Battery energy storage and BESS specialists
- Power-system engineers and electrical engineers
- Energy managers and sustainability professionals
- EV, smart-charging, and V2G professionals
- Energy-market, trading, and regulatory specialists
- Project developers, consultants, investors, and technology providers
Course Modules
Module 1: VPP Fundamentals and Energy-System Transformation
- VPP concepts, definitions, evolution, and market drivers
- Centralized versus decentralized VPP architectures
- Distributed energy resources and flexibility aggregation
- Grid modernization, decarbonization, and energy transition
- Case Study: A utility-scale VPP integrating solar, batteries, and flexible loads
Module 2: VPP Architecture, Digital Platforms, and DER Aggregation
- VPP control layers and distributed asset orchestration
- IoT, smart meters, edge computing, and cloud platforms
- DER communication, interoperability, and data exchange
- SCADA, APIs, EMS, ADMS, and digital-grid integration
- Case Study: Multi-asset DER aggregation using a cloud-based VPP platform
Module 3: Renewable Energy, BESS, and Flexibility Management
- Solar and wind integration within VPP portfolios
- Battery energy storage sizing, dispatch, and optimization
- Energy flexibility and load-shifting strategies
- Forecasting renewable generation and energy demand
- Case Study: Battery-backed renewable VPP for peak-demand management
Module 4: Demand Response, Smart Loads, and EV Integration
- Demand-response program design and optimization
- Industrial, commercial, residential, and smart-building flexibility
- EV charging optimization and managed charging
- Vehicle-to-grid (V2G) and vehicle-to-home (V2H) concepts
- Case Study: EV fleet aggregation providing grid flexibility
Module 5: AI, Automation, Forecasting, and VPP Optimization
- AI and machine learning for VPP forecasting
- Automated dispatch and real-time optimization
- Predictive analytics for demand, generation, and prices
- Digital twins and advanced energy-management systems
- Case Study: AI-enabled VPP optimization for renewable intermittency
Module 6: Energy Markets, Ancillary Services, and VPP Revenue
- Wholesale electricity and flexibility markets
- Frequency regulation and ancillary services
- Capacity markets and demand-response participation
- Energy arbitrage and portfolio optimization
- Case Study: VPP participation in ancillary-service and flexibility markets
Module 7: Cybersecurity, Regulation, Resilience, and Risk
- VPP cybersecurity architecture and threat management
- Data privacy, identity management, and secure communications
- Grid codes, regulatory frameworks, and market access
- Reliability, resilience, contingency planning, and risk management
- Case Study: Cyber-resilient VPP architecture for critical energy infrastructure
Module 8: VPP Business Models, Implementation, and Future Trends
- VPP feasibility studies and implementation roadmaps
- Business models, investment, financing, and revenue stacking
- KPIs, performance monitoring, and portfolio scalability
- Net-zero strategies, energy communities, and transactive energy
- Case Study: Designing a scalable VPP for a renewable-energy community
Training Methodology
- Interactive lectures and presentations.
- Group discussions and brainstorming sessions.
- Hands-on exercises using real-world datasets.
- Role-playing and scenario-based simulations.
- Analysis of case studies to bridge theory and practice.
- Peer-to-peer learning and networking.
- Expert-led Q&A sessions.
- Continuous feedback and personalized guidance.
Register as a group from 3 participants for a Discount
Send us an email: info@datastatresearch.com or call +254724527104
Certification
Upon successful completion of this training, participants will be issued with a globally- recognized certificate.
Tailor-Made Course
We also offer tailor-made courses based on your needs.
Key Notes
a. The participant must be conversant with English.
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
c. Course duration is flexible and the contents can be modified to fit any number of days.
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
e. One-year post-training support Consultation and Coaching provided after the course.
f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.