Steve Burns | A Linear Programming Model to Support a Solar Grand Plan - Presentation Transcript
A Linear Programming Model to Support Development and Maintenance of a Solar Grand Plan Deployment Schedule Institute for the Analysis of Solar Energy Kick-Off Symposium April 24, 2009 Presented by: Steven Burns
Renewable energy’s role in the future energy supply
Transmission capacity limits
Power grid stability
Load scheduling and energy storage
Spinning reserve requirements
Project construction timelines
Material availability
The vision to bring power from remote resources to population centers… …is being refined through accounting of the technological barriers
Technical limitations of large-scale solar deployment
Timelines identified through optimization of annual electricity supply and demand
Scenarios allow for introduction of hybrid vehicle energy demand (and associated infrastructure requirements)
Model focused on technical as opposed to market limitations
Intent is to identify limiting deployment factors on an annual basis
Transmission upgrades to increase solar potential
Organic transmission growth versus (inter-)regional planning
Transmission needs with increased load but offset by better scheduling, demand response, and storage
Timing and location of upgrades
The congested transmission system requires upgrades to incorporate large amounts of renewable energy capacity Chronically congested power lines
Planning necessary to maintain power grid stability
Balancing authority demand profiles compared to available power output
Load scheduling and the need to maintain spinning reserve
Ability to transfer power to/from other regions
Over 100 balancing authorities are charged with maintaining grid stability Authorities noted by color
Planned deployment to accelerate market penetration
Renewable energy development requires a balance of market factors, regulation, and technology
Model allows for market and regulatory limitations but focuses on technical barriers
Model also steps beyond typical regional technical planning
Identifying limiting deployment factors allows for the optimization of deployment timelines
Ultimately, cost-effective clean energy will be available to the market earlier
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