Research Question Catalogue - TransitionZero

Long-term Decarbonisation

Research Question	Scenario Builder Feature / Zonal Application	Long-term Investment (tz-OSeMOSYS)	Zonal Dispatch (PyPSA)	Scenario Builder Implementation
What is the least-cost generation mix for the entire country to reach Net Zero by a specific year (e.g., 2040, 2050)?	Set a Net Zero emission limit for a target year. Scenario Builder optimizes the build-out of technologies to meet this constraint at the lowest cost.	Optimises the multi-decade investment pathway to meet the target at lowest system cost.	Checks if the optimised capacity mix in each year can actually meet load in every hour without blackouts.	Change the emissions target record type, choosing a year where emissions will be 0.
How does a carbon price of $X/tCO2 affect the retirement schedule of the fossil fuel fleet?	Determines how the optimal capacity mix shifts when the internalised cost of emissions changes the Long Run Marginal Cost (LRMC) of fossil generation	Identifies the “tipping point” year where paying the carbon tax becomes more expensive than building new wind/solar.	Shows how the carbon price changes the hourly “merit order” (dispatch rank).	Change the penalty record type adding a carbon price per year.
What is the total system cost impact of a “No new fossil” policy?	Add constraints to the model to stop any buildout of new fossil technologies from a certain year.	Calculates the incremental system cost of forcing more expensive alternatives over cheap gas/coal.	Verifies if the grid remains stable and reliable without the firm capacity provided by new fossil plants.	Change Maximum Additional Capacity to 0 for fossil based technologies from a given year.
At what learning rate does technology X become competitive with incumbent fossil generation.	Input decreasing CAPEX projections to determine the specific year a technology (Wind, Solar, Batteries) reaches cost parity.	Uses learning curves to decide when to start investing in a technology based on its evolving CAPEX.	N/A	Change the capital cost record type for specific technologies you want to analyse.
How does the marginal cost of abatement ($/tCO2) increase as we push the grid from 90% decarbonisation to 100%?	Run sequential scenarios with tightening constraints (e.g., “Max Emissions” = 10Mt, 5Mt, 0Mt). Plot the Total System Cost against the emission limits to visualize the “hockey stick” cost curve.	Maps the exponential rise in Total System Cost as emission constraints tighten.	Explains why costs rise (e.g., showing massive curtailment and storage needs in the final 10%).	Change renewable generation targets over the period of each scenario, increasing the end point incrementally up to 100%.

Dunkelflaute

Research Question	Scenario Builder Feature / Zonal Application	Long term Investment (tz-OSeMOSYS)	Production cost (PyPSA)	Scenario Builder Implementation
To survive a 2-week “Dunkelflaute” (no wind/sun), is it cheaper to overbuild renewable capacity by 3x (and accept massive curtailment) or to build Clean Firm power (e.g., Nuclear, CCS, Green Hydrogen)?	Compare a “100% Renewable” scenario (Wind/Solar/Batteries only) against a “Technology Neutral” scenario (allows Nuclear/Geothermal). The difference in total system cost reveals the “premium” paid for excluding firm power.	Calculates the massive CAPEX difference between “3x Solar” vs. “1x Nuclear”..	Demonstrates the operational risk of the “Overbuild” strategy during extreme weather events.	Set renewable generation targets to 100% and in one scenario set firm power Maximum Additional Capacity to 0 to force variable renewables and storage to meet the load during the dunkelflaute.

Inter-Zonal Grid Planning

Research Question	Scenario Builder Feature / Zonal Application	Long term Investment (tz-OSeMOSYS)	Production cost (PyPSA)	Scenario Builder Implementation
What are the emission and cost benefits of establishing a new interconnection between Zone X and Zone Y?	Add an interconnector between two countries in your scenario to compare the impact it has on emissions and total system cost.	Optimises the trade-off between building the cable (CAPEX) vs. building local generation in each zone.	Simulates hourly power flows to confirm the cable actually relieves congestion and reduces curtailment.	Modify the installed capacities record type between two zones or countries.
What is the benefit in terms of cost and emissions of upgrading interconnector X by 500MW?	Compare Total System Cost in a “Business-as-Usual Grid” scenario vs. an “Upgraded Grid” scenario.	Compares total system cost of “Base Grid” vs. “Upgraded Grid” to find the value of the upgrade.	Shows exactly when (which hours/seasons) the extra 500MW is utilized to avoid dumping cheap renewable power.	Modify the installed capacities record type between two zones or countries.
How much renewable energy is curtailed in the North specifically because it cannot be exported?	Tracks curtailment that occurs specifically when the inter-zonal transmission links are saturated.	N/A	Calculates hourly curtailment caused by inability to export power across saturated links.	Modify the installed capacities record type between two zones or countries.

Reliability & Resilience (Zonal)

Research Question	Scenario Builder Feature / Zonal Application	Long term Investment (tz-OSeMOSYS)	Production cost (PyPSA)	Scenario Builder Implementation
Does X zone have enough domestic firm capacity to survive if the interconnector from Y fails?	Apply a “Minimum Domestic Production” constraint to a specific zone to ensure resilience against link failure.	Enforces “Security Constraints” to force the build-out of local backup capacity.	Stress-tests the zone in “island mode” to see if it survives peak demand hours without the interconnector.	Change the minimum utilisation rate record type for the zone you want to look at.
What is the Loss of Load Expectation (LOLE) for the Industrial Zone during a 2-week “Dunkelflaute” (no wind/sun)?	Runs hourly dispatch to check if the zone’s firm capacity + imports can meet demand every hour.	Run your capacity expansion model with ambitious targets to get residual capacities.	Analyses the full annual dispatch to identify specific loss-of-load events, with particular focus on stress-testing low-renewable weeks.”	Once you have run your highly ambitious capacity expansion scenario, modify the residual capacities in a dispatch model to see if it can meet load in every hour.
What is the minimum Reserve Margin required to handle a climate-driven heatwave?	Increase zonal peak demand inputs to match heatwave projections and solve for the necessary backup capacity.	Sizes the total fleet capacity to meet the inflated peak demand constraint.	Confirms that the specific fleet mix (e.g., batteries vs. gas) can sustain output during the prolonged heat stress.	Change the demand profile and demand magnitude record types.

Thermal Flexibility

Thermal plants’ minimum stable levels, start-up costs and minimum run times are represented with unit commitment.

Research Question	Scenario Builder Feature / Zonal Application	Long term Investment (tz-OSeMOSYS)	Production cost (PyPSA)	Scenario Builder Implementation
Does the gas fleet in the Central Zone have sufficient ramping capability to balance the solar drop-off?	Uses the ramp rates of all units in the zone to ensure the total fleet can track the total net load change.	N/A	Shows the operational benefit: avoiding negative pricing and curtailment by turning thermal plants down further.	Modify ramp rates and minimum utilisation rate record types.
Does flexibilising thermal generators enable more VRE to enter the system in country X.	Take off minimum generation constraints for thermal generators and add appropriate ramp rates to see how they impact generation of renewables.	N/A	Verifies if the retrofitted coal plant is actually flexible enough to compete with the battery’s speed.	Enable unit commitment on thermal generators, lower their Minimum stable generation, and modify ramp rates.
Is it more cost-effective to retrofit the coal fleet for lower minimum stable levels or to build batteries?	Model a “Retrofit” investment option that lowers the minimum generation constraint, comparing its cost against new battery CAPEX.	Compares the investment cost (Retrofit CAPEX vs. Battery CAPEX).	Verifies if the retrofitted coal plant is actually flexible enough to compete with the battery’s speed.	Enable unit commitment on the coal fleet, compare the current and retrofitted Minimum stable generation, and modify ramp rates.

Demand & Electrification

Research Question	Scenario Builder Feature / Zonal Application	Long term Investment (tz-OSeMOSYS)	Production cost (PyPSA)	Scenario Builder Implementation
How does the electrification of Steel in country X impact the need for imports?	Add additional demand and change demand profile for “Steel Electrification” to the specific zone and observe the change in required imports/generation.	Sizes the new generation capacity required to feed the massive new industrial load.	Checks if the grid can supply the constant “baseload” shape of industrial furnaces during low-wind weeks.	Change demand profile and demand magnitude record types.
How does a “High Electrification” scenario (rapid EV/Heat Pump uptake) change the optimal generation mix compared to baseline?	Run two scenarios with different aggregate demand curves. Analyze how the “High” scenario changes the ratio of baseload vs. peaking capacity needed.	Shifts investment toward technologies that suit the new load shape (e.g., more solar for AC peaks).	Manages the new ramping challenges introduced by “peaky” residential loads (EVs/Heat pumps).	Change demand profile and demand magnitude record types.
What is the system cost saving if EV charging is “Managed” (V1G) vs. “Unmanaged” (charging at peak)?	Compare a scenario with a fixed “Evening Peak” EV profile vs. a scenario where EV demand is defined as “Flexible/Shiftable” load within a 24-hour window.	Sees a lower peak demand, resulting in less need for peaker plants.	Optimizes the charging profiles hour-by-hour to fill “valleys” in renewable generation, reducing system costs.	Change the demand profile record type.
How does Energy Efficiency in buildings (e.g., retrofits) reduce the need for peak capacity investment?	Scale down the residential demand profile (specifically the heating/cooling peaks) and observe the reduction in required gas peaker/battery capacity.	Directly reduces the investment need for expensive “peaker” plants.	Shows higher reserve margins and less stress on the system during peak hours.	Change the demand profile record type and demand magnitude record type.