RT23 – CO2 Reduction Contest

CO2 Reduction Contest

Real-Time Simulation for Carbon Emissions Reduction

OPAL-RT believes in encouraging engineers and researchers with accessible, cutting-edge, real-time simulation technology to accelerate the availability of greater products and more reliable energy transmission. Offering unparalleled expertise to various industrial and academic projects, OPAL-RT continually contributes to the development of more environmentally-friendly power systems, motors, and networks.





We’re inviting university students & teachers to demonstrate their achievements in leveraging real-time simulation to combat climate change. Help us in our effort to shape a better future! Demonstrate how real-time simulation can facilitate the testing of models and devices aimed at reducing CO2 production.






The Contest

• Who: University students and teachers can participate. Teams must be made up of a maximum of 5 people.


• Why: Help us in our effort to shape a better future! Demonstrate how real-time simulation can facilitate the testing of models and devices aimed at reducing CO2 production.


• What: Use one of OPAL-RT’s platforms to build a model aimed at reducing CO2 production over a 5-year period.


• Submission Deadline: August 18th, 2023


• Prizes for the 2 final teams: One plane ticket to Lisbon, lodging for 4 nights, and a ticket to RT23 for 1 representative of each team









Project Guidelines

From May 22 to August 18, write a one-page abstract (maximum 1000 words) on how you plan to use one of OPAL-RT's platforms to build a model aimed at reducing CO2 production over a 5-year period. Present the members of your team (5 people max). ​

By August 18, participants will find out if their project has been selected for the contest and if they are moving on to the next stage.



Before September 15, submit your results in a 3-5 minutes video. Explain how you used one of OPAL-RT's platforms to build a model aimed at reducing CO2 production over a 5-year period.

The 2 finalists will be selected on September 18, and the winner will be chosen at RT23 in Lisbon, Portugal on November 15th.








Video Submission Topic Examples:

Energy Efficient Optimization

Renewable Energy Integration

Transportation and Logistics

Urban Planning and Infrastructure









Judging Criteria

CategoryParticularsGrading
ResultMagnitude of CO2 reduction on a 5-year period25%
ComplexityComplexity, size and accuracy of the model25%
RealismModel feasibility and large-scale potential25%
InnovationIntroduces a new idea, method or device15%
Presentation/VideoGood summary of results, creativity, pitch quality, use of visual elements10%

Frequently Asked Questions

If your application is selected, OPAL-RT will provide licenses and documentation for the duration of the contest.

Participation is free

• To name the 2 finalists =3 members of OPAL-RT & 2 external real-time simulation experts
• To choose the winner = Guests at RT23

OPAL-RT will not pay for visas, passport renewal, commute to your national airport, or other travel-related expenses. OPAL-RT will only pay for the plane ticket, lodging for 4 nights, and a ticket to the conference.

Yes, we invite you to provide us with all the proof of the data you show in your video. However, only the elements presented in the video will be evaluated.

You will submit your video by e-mail (via WeTransfer). We will contact you with the details.

 

Still have questions? Contact us at rt23@opal-rt.com with your queries or comments!









Selected finalists

Discover one of the two finalist projects of the RT23 – CO2 Reduction Contest developed by Ph.D. Student, Ali Hassan and Ph.D. Candidate, Shahid Khan from University of Michigan: "Second-Life Batteries for Electrical Grid Using OPAL-RT TECHNOLOGIES Simulator"

The project introduces a comprehensive model for the integration of second-life battery packs into microgrids enriched with Distributed Energy Resources (DERs). The modeling process, conducted using MATLAB's workspace and Simulink, enables diverse grid functions, including Energy Arbitrage, Peak Shaving, and Power Smoothing. Its objective is to optimize these functions in alignment with specific utility tariffs, tailoring the optimal utilization of second-life BESS across microgrids of varying sizes and DER penetration levels.

OPAL-RT's real-time simulator executes the validation and optimization of the model, ensuring its performance in simulating microgrid behavior under realistic conditions. The model integrates real-world Nissan Leaf Li-ion batteries into a mid-size (5MW) microgrid, which incorporates PV and wind generation, to replicate practical loads. A detailed cost analysis accompanies the project, covering procurement, installation, and the 5-year operational costs of second-life BESS, alongside quantifiable CO2 reduction metrics.

This initiative aims to faithfully replicate the dynamic behavior of electrical systems in real-time. The proposed model can serve as a valuable resource for utilities and microgrid operators, offering insights into cost reduction, operational efficiency, and, most importantly, the overarching objective of curbing CO2 emissions from electricity generation. These results can also support the safe inspection and due diligence associated with deploying second-life batteries in real-world microgrid scenarios.









Explore one of the two finalist projects of the RT23 – CO2 Reduction Contest developed by Research Fellow, Veerapandiyan Veerasamy and his team: Assistant Professor, Hung Dinh Nguyen, Firas Basim Ismail, Vigna Kumaran Ramachandaramurthy, and Associate Professor, Hoay Beng Gooi from the Nanyang Technological University - NTU Singapore: "A Multi-Stage Optimization and Control of Microgrids with Carbon and Peer-to-Peer Trading Market"

The energy sector's transition to renewable sources and the expansion of large-scale microgrids (MGs) are critical steps in reducing CO2 emissions. However, the inherent challenges of renewable energy uncertainty and diverse load profiles demand innovative solutions. This work introduces a multi-stage optimization model addressing energy management optimization (EMO) in MGs while considering carbon trading markets.

The model combines a 24-hour ahead schedule to reduce long-term CO2 emissions with a 30-minute interval dispatch to manage fine-grained renewable generation uncertainties. Innovative reserve strategies ensure sufficient resources for real-time deviations. EMO dispatch serves as a reference for prosumers in peer-to-peer (P2P) energy trading markets, empowering them to profit from surplus energy sales directly to buyers while procuring additional energy at lower rates during shortages. A blockchain-based energy trading platform ensures transparency and security.

To regulate MG system frequency, a Fractional-order Recurrent Neural Network (FoRNN)-based adaptive control system is introduced. It replaces conventional load frequency control (LFC) and aligns with the evolving P2P energy trading landscape. Implementation is facilitated using Python on Raspberry Pi (RPi) computers, MATLAB/Simulink for MG modeling, and the OPAL-RT simulator, ensuring system stability while enabling renewable energy prosumers' participation in the open energy market.









Outstanding Contestant

Discover the groundbreaking project: “Shore to Ship Power: Battery Energy Storage Controller Vaasa Harbour Area Smart Grid CSIL-CHIL” developed by Associate Professor/Senior Researcher Mike Mekkanen, and his team at the University of Vaasa, Finland: Jagdesh Kumar, Kimmo Kauhaniemi, and Mazaher Karimi.

The project investigates smart grid models for harbors, supporting onshore power supply and battery charging for future vessels. It also assesses Battery Energy Storage Controllers (BESC) for efficient power management within harbor grids. The BESC, initially designed using MATLAB/Simulink, is integrated into the smart grid via an FPGA-based external controller, linked with OPAL-RT’s real-time simulator using the IEC61850 communication protocol and GOOSE messages. Real data from local distribution systems and harbor operators validate the control algorithm for battery energy storage in real-world scenarios.

This initiative also tackles the environmental challenges posed by maritime transport, offering emission-free and sustainable power solutions for vessels at berth. Watch the video to delve into the technical innovations and progress toward reducing emissions and enhancing energy efficiency in harbor areas.