NEWS

May 29, 2020

NM SMART Grid Center Research Highlights from Year 2

Two computers with data flowing between them

NM EPSCoR

By Brittney Van Der Werff

Every year the NM SMART Grid Center is required to submit three highlights from the previous project year to the National Science Foundation. For Project Year 2, the research themed highlights focused on work by Assistant Professor Ali Bidram and his PhD student Binod Poudel at UNM and advancements by Assistant Professor David Mitchell and his team at NMSU.

Here is what these outstanding team members are working on - summarized in 250 words or less.

Enjoy!

 

Cracking the code: Improving the Efficiency of Error-Correcting Codes for the Future of Communications David Mitchell, NMSU

What is the outcome or accomplishment?

Assistant Professor David Mitchell and his team at New Mexico State University have made unprecedented improvements to the performance of LDPC (Low-Density Parity-Check) codes — a type of error-correcting code used in nearly all modern high-speed digital communications.

What is the impact?

LDPC codes are used extensively in modern high-speed communications, and improvements in their performance will lead to significant reductions in energy consumption, transmission errors, and data exchange lag times for smartphones, smart cars, smart homes, and many other machine-to-machine applications integral to next-generation networks.

What explanation/background does the lay reader need to understand the significance of this outcome? 

Our healthcare, education, and economy all rely to some degree on network connectivity, as do an ever-increasing number of smart appliances, phones, and cars. Accordingly, experts predict that the number of networked devices will be three times the global population by 2023, an increase that will challenge the carrying capacity of communications infrastructure on a global scale. Advancements made by Assistant Professor David Mitchell and his students at New Mexico State University address the data deluge by improving the performance of LDPC codes inherent in most next-generation wireless technology (5G) communications. Their algorithms demonstrate previously unachievable gains in computational efficiency that lessen the energy costs of digital information exchange and enable efficient monitoring and management of our nation’s power resources in the future.

Cybersecurity and DC Microgrids: Securing power of the future. Binod Poudel, Ali Bidram, UNM

What is the outcome or accomplishment? 

University of New Mexico PhD student Binod Poudel and Assistant Professor Ali Bidram have developed cybersecurity schemes that can detect False Data Injection (FDI) attacks on distributed direct current (DC) microgrid control systems and rapidly mitigate destructive impacts.

What is the impact?

An increasing number of universities, military bases, and hospitals in the United States have transitioned to microgrid power systems in the past decade. Improving the resilience of microgrids through cybersecure distributed control systems has beneficial implications for the nation as a whole and will enable key research, defense, and healthcare operations to continue uninterrupted.

What explanation/background does the lay reader need to understand the significance of this outcome? 

Microgrids can rapidly respond to power disruptions and efficiently function with or without power from the larger electrical grid. Many existing microgrids rely on a single control center, that if compromised, could shut down the entire system. “Distributed control” microgrids divide control of the system across devices connected to the microgrid. This distributed control framework, operating with DC power, can revolutionize future microgrid systems and improve reliability, scalability, and resilience. However, distributed control DC microgrids are also vulnerable to cyberattacks through their multiple layers of linked devices.

The cyberattack detection and mitigation schemes developed by PhD student Binod Poudel and Assistant Professor Ali Bidram are among the first described in scientific literature capable of accurately distinguishing FDI attacks from legitimate events and rapidly mitigating the adverse impacts of such an attack on a distributed control DC microgrid.