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
| 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. | Modify ramp rates and minimum utilisation rate record types. |
| 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. | Modify ramp rates and minimum utilisation rate record types. |
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. |