Viet Nam

Emissions Reduction Profile:

• With just domestic measures, Viet Nam is able to reach zero emissions.
• For emissions reductions up to 75% below a no-action scenario, offshore wind may play a substantial role.
• As emissions drop further, rapid deployment of onshore wind, alongside less pronounced development of NH₃ storage and open field PV is required for reaching zero emissions.
• Further, to reach the final reduction of 10 Mt CO₂e deployment of battery storage is essential.
• This suggests that Viet Nam could consider an early shift towards onshore wind when aiming for deeper emissions cuts, with parallel investment in storage technologies to replace the flexibility of dispatchable fossil generation and both open field and rooftop PV.

Evolving role of Offshore Wind

• As mentioned, offshore wind could be a key technology to achieve the initial 75% emissions reduction from BAU no-action scenario. However, this technology becomes substantially less important (almost unnecessary) as emissions constraints tighten.
• The investment in offshore wind changes from USD6.1 Billion when emissions are at 25% of emissions in a no-action scenario, to USD0.5 Billion for zero emissions.
• It may therefore not be convenient for Viet Nam to invest more than half a billion USD in offshore wind to avoid technological lock-ins and investment regrets.
• When planning for 100% emissions reduction, it would be more beneficial and result in lower overall costs to start investments in onshore wind early, and complement these with storage, both NH₃ and batteries.

Role of industrial heating

• From the initial reduction of 75% below emission in a no-action scenario, Viet Nam requires investment in electric industrial heating.
• Ammonia industrial high temperature heating is only used to abate the last 3% of emissions, and completely remove the need for fossil heaters to meet this end use.

International Collaboration Necessity:

• In the absence of international collaboration (autarky), Viet Nam is able to reach zero emissions in the power sector under these scenarios. This requires mitigation cost of USD15.10/tCO₂e.
• In collaboration arrangements, the mitigation cost ranges from USD10.69 - USD12.60/tCO₂e

We have included some illustrative case studies of effective policy interventions in particular countries and cities. 

1. Power
2. Energy
3. Industry
4. Transport
5. Agriculture

National and International Collaboration Modelling (STEVFNs)

National and international modelling was performed using STEVFNs energy system model generator. Modelling was performed by setting annual emissions limits and finding the cost-

optimal technology mix that meets all hourly demands with the emissions constraints.

This modelling assumes a greenfield model built in 2050 to meet fixed electricity and high-temperature heating demand, minimising the net present value of a 30-year project.

 First, a baseline case study for no action was set up for Viet Nam with its current energy mix, determining the no-action emissions on its own (autarky). From this baseline, a linear reduction towards zero emissions was determined that would constrain the scenarios. A total of eleven scenarios with emissions constraints ranging from those obtained for no action to zero were run to build the cost-optimal technology mixes shown in the Dynamic Pareto Abatement Cost Curve (D-PACC).

 After determining the total mitigation potential in autarky for Viet Nam, two additional case studies were created:

1.     A combination of countries in autarky, with maximum total emissions defined as the sum of their individual autarky emissions  

2.     A combination of countries collaborating (adding electricity and ammonia transport between them), with maximum total emissions defined as the sum of their individual autarky emissions  

Then, the methodology implementing emissions constraints in eleven scenarios with respect to the sum of the set of countries no action emissions were set up. Results from these then build the D-PACC for collaboration and for the set of countries without collaboration. In some cases, the set will not be able to reach zero emissions in the modelled sectors when modelled independently, as their individual reductions make the problem infeasible at some level of constraint for total emissions. These, however, may reach zero (or at least higher emissions reduction) when energy trade is enabled through green electricity and ammonia transport.

 Data

Electricity and high-temperature heating demand are projected to 2050, following the estimates from high-resolution modelling performed in OSeMOSYS. Technology capital and operational costs were translated from detailed OSeMOSYS modelling where available, and estimated based on literature figures for technologies, including high-voltage direct current (HVDC) submarine cables. See detailed methodology for specifics on this data.

 Additional Detailed National Modelling 

In the pilot, additional “detailed national modelling” was performed using OSeMOSYS energy system model-generator. These are supposed to emulate potentially different energy system models currently used by different countries. In future phases of GMPA, countries will be encouraged to share their national models and data. These will be translated to the generalised STEVFNs system-of-systems model-generator. 

 This is done for the following benefits: 

1.     Reduce barrier to entry for countries to engage with GMPA. 

2.     Leverage on national modeling efforts around the world instead of repeating modelling efforts. 

3.     Have a scalable, distributed method of managing and updating national modelling data. 

4.     Ensure the input assumptions on GMPA are “owned” by countries so that they are comfortable enough with the results for the results to be useful as a basis to bring parties onto the negotiation table. 

In the pilot, a detailed national modelling was performed for Viet Nam by building a “0th order” OSeMOSYS“starter data kit” using the methodology developed by Climate for Compatible Growth (CCG) that is applied to more than 60 countries around the world. The model determines the least cost optimal technology mix pathway from 2015-2070 to meet all end-use energy demands given some emissions constraints. The sectors included are power, transport, industry, household, and commercial sectors.  

If you would like to see D-PAC curves for detailed national modelling, please contact GMPA.