Digital Twin decarbonizes the energy systems by bringing all technologies together. The virtual twin can model energy flows and changes of variables in real-time.

Initially, designers and engineers used it to build prototypes of new products, but it proved to have more practical uses. Moreover, integrating the Internet of Things and AI has strengthened it to carry out multiple tasks. 

Digital Twin can model a raft of internally connected systems through big data analytics. So, Digital twin can aid the reduction of CO2 and other greenhouses gases released into the earth's atmosphere. 

Digital Twin can map out all the aspects of the energy systems to help with decarbonization. Starting from electrical production to distribution losses and localized demand, it would lay out the whole system in the virtual environment. 

The use of Digital Twin is expanding as we are developing the technology to be more effective with time. For example, it has proven effective in energy management, electrically powered public transport infrastructure management, and sector coupling. 

It is not possible to derive the best outcomes from the Digital Twin without knowing the factors. Therefore, one needs to know these factors below to decarbonize the energy systems without failure with Digital Twin.

Get Digital Twin Experts on Board: 

When you are up for decarbonization of energy systems, you'll need technical know-how. So we are expecting that your in-house talents already possess the understanding of electrical generation, supply, and distribution. 

Next, you will need a more profound working knowledge of Digital Twin to use this for the digital decarbonization of energy systems. 

You must have a clear understanding of building digital twins aligned with each phase of the decarbonization process. Additionally, you need to know how to deal with data modeling and intelligent data technology to make digital twin work for you. 

It's better to outsource the Digital Twin project to experts if you lack the in-house skills needed to make this project successful. Companies have to deal with the unique sets of challenges of building and deploying a digital twin. 

Digital Twin is a framework for building a bridge between the physical and digital worlds. Therefore, you must satisfy a range of requirements to develop and deploy virtual twins successfully, including: 

• CAD modeling & connectivity 
• Cloud computing 
• IoT software platforms 
• Physics-based simulation
• Machine learning 
• Systems integration
• Remote monitoring 

 The biggest challenge of deploying a digital twin is that it shares the same characteristics as the physical entity. The Digital Twin (DT) decarbonizes the energy systems better if the team can deal with the challenges below: 

• DT must capture the material properties with its exact size and simulate its behavior according to the real object like a car or a person.
• DT must embody a human user as an avatar to interact with other avatars or digital twins
• DT should work collaboratively with its composite inside and with other digital twins outside
• DT must have the self-awareness  to respond to changes of size and functionality in real-time and modify itself as needed 
• DT must detect the execution of conflicts and resolve them automatically for uninterrupted communications.

Make use of your best Datasets: 

Preparing the data set should be the next step in your list before building the digital twin. 

We're living in the big data age where high-quality data sets are crucial to success. Feed high-quality data into the Digital Twin and you can expect fantastic outcomes. Feed trash into the twin system and the result will be the other way round. 

To sum it up, it means that you need to clean up, gather and structure data sets to set up the twin system.  Also, cross-check the Data's relevancy in real-world settings to ensure you will be feeding high-quality sensible data into the twin system. 

When you are swamped with data and need to analyze different sets for different purposes, it adds complexity. 

For instance, analyzing meteorological data like temperature, dew point, wind direction, and speed next to electrical consumption in buildings from photovoltaic, solar thermal, and hydropower plants at locations worldwide can become messy. 

In brief, you'll need to combine patience and years of professional experience to locate, collect and prepare the best data sets. 

Digital Twin Decarbonizes the Energy Systems Better if You Avoid Preconceptions About Model or Configuration: 

Start building and deploying Digital Twin with an open mind. Don't keep any preconceived notions about which specific model or design will work for your program. 

Keeping an open mind will give you the flexibility to draw the best model and configuration from a variety of ideas and solutions. 

Your digital twin will end up with average quality outcomes if you have a preconceived technological pathway and follow it. 

Examine all the possible solutions to decarbonization before going with one specific approach. In this way, you can make the best out of the digital modeling and AI computing calculations and stats.

Adopt Digital Twin for the whole system:

Before starting your digital twin program, you must figure out the pathway to optimize the entire energy system. 

You'll need to conduct an end-to-end analysis of the initial situation and the entire technological framework conditions. Digital Twin decarbonizes the energy systems better if you consider the parameters below of each site individually for decarbonization of the energy system: 

• Technical lifetime
• Maximum capacity
• Minimum operating and downtime metrics against the maximum 
• Investment 
• Maintenance cost
• Energy demand against relative efficiency

Prepare the decarbonization strategy before jumping into the program: 

You must set clear goals before starting the decarbonization program with the digital twin. Digital Twin decarbonizes the energy systems better if these factors are implemented: 

• Set a clear benchmark of the outcomes you are expecting
• Ensure that the electric system modeling in the digital twin is offering a transparent decarbonization roadmap. It should align with your standards. 
• Consider the monetization details of the present against the targeted carbon footprint that comes into play. 
• Consider the present and future private or public business models that may get challenged due to their inherent carbon intensity based on the goods and services they produce.  
• Ensure you are not brushing off the sustainability reporting if it exposes uncomfortable facts about management to personal liability.

Don't look for Instant success: 

It's not possible to achieve success within a short period with digital decarbonization as it's a high multi-dimensional program. 

The digital twinning of the energy system will need care because it's a complex model. So, building the model may take a few weeks to months, depending on the size of the venture. Also, onboarding the right people for the fieldwork and synchronizing all the steps together cannot happen overnight. 

How Digital Decarbonization can Change the World? 

Digital Twin decarbonizes the energy systems in a different class when you apply a tactical approach. Reducing carbon emissions in the atmosphere will help climate change and keep our earth greener. Both the private and public sectors will feel the impact of using digital twins in decarbonization. 

Adopting decarbonization applies mainly to the utility sector. However, other high energy demanding sectors such as the chemical industries should think about it as well. 

We cannot deny that buildings are responsible for about 40 percent of all current carbon emissions. So, digital decarbonization of energy systems can make a massive difference to the climate of tomorrow. 

However, the question may arise: Is decarbonization possible?

Digital decarbonization would be hard to implement but not impossible to achieve. We can reduce indirect carbon emissions through electrification and clean energy only. It is hard to control direct carbon emissions. So, we cannot deny that heavy industries would still be responsible for at least 20% of GHG emissions.

Digitalization of industries has already begun. So, companies that won't embrace modern trends like digital decarbonization processes will be left out. Decarbonization and digitalization are getting popular. As a result, industries have to switch from their traditional business models to stay relevant. 

Every company must adopt the digital decarbonization process. At present, businesses are in a situation where they need to decide on a sustainability strategy that will work from the economic perspective. To do that, they must transform into a lower-carbon business model company.

 Suddenly, this change of direction cannot take place overnight. Therefore, cooperation between industries is required to implement a lower-carbon business model. The enterprises will need to review climate strategy, set measurable goals, and clearly define their action plans. They will also need to assess their performance from time to time and optimize as necessary. 

Adopting digital decarbonization can benefit industries in many ways. For example, businesses can run cost-efficient systems designed for specific localities when Digital Twin decarbonizes the energy systems. 

Digital decarbonization can aid district heating systems and energy storage management systems of the community. In addition, it can help to increase the capacity of electric vehicle charging stations while ensuring saving potentials in environments. Moreover, digital decarbonization can reduce electricity waste and daily operational costs. 

Businesses that adopt digital decarbonization will gain the rewards of CSR too. First, they will achieve better brand recognition as environmentally friendly companies. It, in turn, will strengthen their brand image among the public. 

Therefore, implementing Digital Decarbonization is a win-win situation for businesses, our environment, and society.