GridPath
Advanced Software for Power-System Planning
GridPath is a versatile grid-analytics platform developed and maintained by Sylvan Energy Analytics. The GridPath platform allows for integration across capacity expansion, production cost, and resource adequacy analyses for planning, price forecasting, and asset valuation applications, all within the same software ecosystem and leveraging a common database structure.
Driving innovation in clean energy planning
GridPath was developed to catalyze innovation in resource planning and decarbonization strategy. It is designed to empower users to navigate the complexities of modern power systems. Whether it’s evaluating the integration of renewable energy sources, assessing the impact of new regulatory frameworks, or planning for long-term resource adequacy, GridPath's comprehensive capabilities can provide the detailed, actionable insights needed to make informed decisions.
Open-source
GridPath is open-source and available on GitHub, with comprehensive documentation on Read the Docs.
Built by industry practitioners for today's realities and tomorrow's planning questions
Developed by industry practitioners, GridPath is designed to address real-world challenges. Its flexible, modular architecture adapts easily to different systems and emerging technologies, making it a powerful tool for both current and future grid planning questions. GridPath includes database-building tools, an interactive results-visualization suite, extensive validation and testing suites, and a user interface.
Trusted by industry leaders
GridPath is trusted by a diverse set of organizations, including utilities, national laboratories, consulting firms, and NGOs. Users and contributors have included Portland General Electric, Seattle City Light, Ava Community Energy, Valley Clean Energy, Pacific Northwest National Lab, Lawrence Berkeley National Lab, Environment and Climate Change Canada, Moment Energy Insights, Telos Energy, Energy Strategies, First Principles Advisory, Strategen, UCSB CET Lab, WRI, and Prayas Energy Group, among others.
Key features
Capacity Expansion
Fully customizable temporal granularity, geo-spatial granularity, and sampling methodology
Endogenous retirements, transmission expansion, and DSM selection
Stochastic optimization for planning under uncertainty*
Automated integration with resource adequacy and production cost modeling via iterative optimization*
Production Cost
Multi-stage scheduling, commitment, and dispatch optimization
Fully customizable temporal and geo-spatial granularity
Zonal, nodal pipe flow, and DC power flow transmission options
Market energy and ancillary service* price-responsive dispatch
Resource Adequacy
Time-sequential and energy-constrained dispatch simulation
Zonal transmission constraints and path limits
Synchronized or Monte Carlo weather treatment for loads and resource availability over wide areas
Weather-driven Monte Carlo outages
* These features not available in open source version at this time.