Your grid integration study will need to consider various scenarios and sensitivities, which provide the foundation for evaluating how various options for your power system’s generation assets, transmission network, and operational practices impact the development of renewable energy and the broader power sector.
What You Need to Know
In the context of your grid integration study, a scenario is one possible future electric generation system. These scenarios define system conditions over a specific time period. These time periods differ by the kind of model you have chosen.
All grid integration studies consider at least three scenarios, including: a reference scenario, a base or business-as-usual (BAU) scenario, and a high-renewable energy scenario. Additional scenarios can explore the impacts of power sector policies, regulations and operational practices.
In a grid integration study, a sensitivity helps test uncertainties around key assumptions such as demand growth, policy changes, and/or cost trends for emerging technologies. Your study’s sensitivity analyses may require data above and beyond the data needed for your core grid integration study scenarios.
It is important to define the primary study scenarios before committing to a work plan as these choices will have implications for timeline and budget.
First, Understand the Basic Scenarios
Your study should run at least three scenarios.
A reference scenario focuses on the current power system and is most useful for production cost and power flow models.
A base or business-as-usual (BAU) scenario is a scenario that looks forward in time but assumes that today’s policies and operational practices will remain relatively unchanged.
A high-renewable energy scenario includes higher shares of wind and/or solar generation relative to the BAU scenario.
Now, Consider Scenarios from Other Successful Studies
Study scenarios can differ by time period and the type of model you are running. Many grid integration studies include several high renewable energy scenarios. The scenarios and sensitivity analyses you run depend on your study’s objectives, and may have budget and time-line impacts.
Read Excerpt: Pages 19-20 of Variable Renewable Energy Grid Integration Studies: A Guidebook for Practitioners by NREL.
Next, Consider the Sensitivities You Might Use
In your high renewable energy scenarios, you can explore a variety of potential sensitivities. This can include changes to assumptions for power system operations, market operations, infrastructure, climate scenarios, policy changes and more. Some of these sensitivities may require the collection of additional data.
Changes to power system operations assumptions:
More flexible operation of conventional generation (e.g., lower minimum generation levels, faster starts and ramps)
Implementation or removal of must-run policies for variable RE and/or conventional generation
Different definitions of ancillary services (including reserves) and providers (for example, allowing solar and wind generators to participate in downward reserve provision o Increased coordination with neighboring balancing areas (e.g., through reserve sharing or coordinated unit commitment and/or economic dispatch)
Implementation or improvement of variable RE power forecasting o More frequent economic dispatch intervals o Implementation of demand response programs.
Changes to market operation assumptions (if applicable):
Implementation of energy imbalance markets with neighboring power systems o Implementation of different ancillary service market products
More frequent interchange.
Changes to infrastructure assumptions:
Addition of new transmission capacity to limit congestion and/or enable RE siting in highest resource density areas
Different assumptions about the capacity and type of conventional generation additions or retirements
Deployment of additional storage capacity.
Changes to power system contextual assumptions:
Alternative demand scenarios (magnitude and profile) o Alternative fuel price (or other cost) trajectories
Different climate scenarios (e.g., low versus high hydropower years).