Liang Min - Academia.edu (original) (raw)
Papers by Liang Min
Nature Energy, Sep 22, 2022
IEEE Transactions on Energy Conversion
![Research paper thumbnail of The Pandemic: An Unprecedented Impact to Grid Operation [Guest Editorial]](https://attachments.academia-assets.com/118222049/thumbnails/1.jpg)
](IEEE Power and Energy Magazine
arXiv (Cornell University), Mar 13, 2018
IEEE Open Access Journal of Power and Energy, 2021
IEEE Electrification Magazine, 2019
2007 International Conference on Intelligent Systems Applications to Power Systems, 2007
IEEE Power Engineering Society General Meeting, 2005
2007 International Conference on Intelligent Systems Applications to Power Systems, 2007
A power system with multiple interconnected areas needs to be operated coordinately for the purpo... more A power system with multiple interconnected areas needs to be operated coordinately for the purposes of the system reliability and economic operation, although each area has its own ISO under the market environment. In consolidation of different areas under a common grid ...
Social Science Research Network, 2024
Adopting Artificial Intelligence (AI) in electric utilities signifies vast, yet largely untapped ... more Adopting Artificial Intelligence (AI) in electric utilities signifies vast, yet largely untapped potential for accelerating a clean energy transition. This requires tackling complex challenges such as trustworthiness, explainability, privacy, cybersecurity, and governance, balancing these against AI's benefits. This article aims to facilitate dialogue among regulators, policymakers, utilities, and other stakeholders on navigating these complex issues, fostering a shared understanding and approach to leveraging AI's transformative power responsibly. The complex interplay of state and federal regulations necessitates careful coordination, particularly as AI impacts energy markets and national security. Promoting data sharing with privacy and cybersecurity in mind is critical. The article advocates for 'realistic open benchmarks' to foster innovation without compromising confidentiality. Trustworthiness (the system's ability to ensure reliability and performance, and to inspire confidence and transparency) and explainability (ensuring that AI decisions are understandable and accessible to a large diversity of participants) are fundamental for AI acceptance, necessitating transparent, accountable, and reliable systems. AI must be deployed in a way that helps keep the lights on. As AI becomes more involved in decision-making, we need to think about who's responsible and what's ethical. With the current state of the art, using generative AI for critical, near real-time decision-making should be approached carefully. While AI is advancing rapidly both in terms of technology and regulation, within and beyond the scope of energy specific applications, this article aims to provide timely insights and a common understanding of AI, its opportunities and challenges for electric utility use cases, and ultimately help advance its adoption in the power system sector, to accelerate the equitable clean energy transition.
Energy Law Journal, 2024
Adopting Artificial Intelligence (AI) in electric utilities signifies vast, yet largely untapped ... more Adopting Artificial Intelligence (AI) in electric utilities signifies vast, yet largely untapped potential for accelerating a clean energy transition. This requires tackling complex challenges such as trustworthiness, explainability, privacy, cybersecurity, and governance, balancing these against AI's benefits. This article aims to facilitate dialogue among regulators, policymakers, utilities, and other stakeholders on navigating these complex issues, fostering a shared understanding and approach to leveraging AI's transformative power responsibly. The complex interplay of state and federal regulations necessitates careful coordination, particularly as AI impacts energy markets and national security. Promoting data sharing with privacy and cybersecurity in mind is critical. The article advocates for 'realistic open benchmarks' to foster innovation without compromising confidentiality. Trustworthiness (the system's ability to ensure reliability and performance, and to inspire confidence and transparency) and explainability (ensuring that AI decisions are understandable and accessible to a large diversity of participants) are fundamental for AI acceptance, necessitating transparent, accountable, and reliable systems. AI must be deployed in a way that helps keep the lights on. As AI becomes more involved in decision-making, we need to think about who's responsible and what's ethical. With the current state of the art, using generative AI for critical, near real-time decision-making should be approached carefully. While AI is advancing rapidly both in terms of technology and regulation, within and beyond the scope of energy specific applications, this article aims to provide timely insights and a common understanding of AI, its opportunities and challenges for electric utility use cases, and ultimately help advance its adoption in the power system sector, to accelerate the equitable clean energy transition.
Nature Energy, Sep 22, 2022
IEEE Transactions on Energy Conversion
IEEE Power and Energy Magazine
arXiv (Cornell University), Mar 13, 2018
IEEE Open Access Journal of Power and Energy, 2021
IEEE Electrification Magazine, 2019
2007 International Conference on Intelligent Systems Applications to Power Systems, 2007
IEEE Power Engineering Society General Meeting, 2005
2007 International Conference on Intelligent Systems Applications to Power Systems, 2007
A power system with multiple interconnected areas needs to be operated coordinately for the purpo... more A power system with multiple interconnected areas needs to be operated coordinately for the purposes of the system reliability and economic operation, although each area has its own ISO under the market environment. In consolidation of different areas under a common grid ...
Social Science Research Network, 2024
Adopting Artificial Intelligence (AI) in electric utilities signifies vast, yet largely untapped ... more Adopting Artificial Intelligence (AI) in electric utilities signifies vast, yet largely untapped potential for accelerating a clean energy transition. This requires tackling complex challenges such as trustworthiness, explainability, privacy, cybersecurity, and governance, balancing these against AI's benefits. This article aims to facilitate dialogue among regulators, policymakers, utilities, and other stakeholders on navigating these complex issues, fostering a shared understanding and approach to leveraging AI's transformative power responsibly. The complex interplay of state and federal regulations necessitates careful coordination, particularly as AI impacts energy markets and national security. Promoting data sharing with privacy and cybersecurity in mind is critical. The article advocates for 'realistic open benchmarks' to foster innovation without compromising confidentiality. Trustworthiness (the system's ability to ensure reliability and performance, and to inspire confidence and transparency) and explainability (ensuring that AI decisions are understandable and accessible to a large diversity of participants) are fundamental for AI acceptance, necessitating transparent, accountable, and reliable systems. AI must be deployed in a way that helps keep the lights on. As AI becomes more involved in decision-making, we need to think about who's responsible and what's ethical. With the current state of the art, using generative AI for critical, near real-time decision-making should be approached carefully. While AI is advancing rapidly both in terms of technology and regulation, within and beyond the scope of energy specific applications, this article aims to provide timely insights and a common understanding of AI, its opportunities and challenges for electric utility use cases, and ultimately help advance its adoption in the power system sector, to accelerate the equitable clean energy transition.
Energy Law Journal, 2024
Adopting Artificial Intelligence (AI) in electric utilities signifies vast, yet largely untapped ... more Adopting Artificial Intelligence (AI) in electric utilities signifies vast, yet largely untapped potential for accelerating a clean energy transition. This requires tackling complex challenges such as trustworthiness, explainability, privacy, cybersecurity, and governance, balancing these against AI's benefits. This article aims to facilitate dialogue among regulators, policymakers, utilities, and other stakeholders on navigating these complex issues, fostering a shared understanding and approach to leveraging AI's transformative power responsibly. The complex interplay of state and federal regulations necessitates careful coordination, particularly as AI impacts energy markets and national security. Promoting data sharing with privacy and cybersecurity in mind is critical. The article advocates for 'realistic open benchmarks' to foster innovation without compromising confidentiality. Trustworthiness (the system's ability to ensure reliability and performance, and to inspire confidence and transparency) and explainability (ensuring that AI decisions are understandable and accessible to a large diversity of participants) are fundamental for AI acceptance, necessitating transparent, accountable, and reliable systems. AI must be deployed in a way that helps keep the lights on. As AI becomes more involved in decision-making, we need to think about who's responsible and what's ethical. With the current state of the art, using generative AI for critical, near real-time decision-making should be approached carefully. While AI is advancing rapidly both in terms of technology and regulation, within and beyond the scope of energy specific applications, this article aims to provide timely insights and a common understanding of AI, its opportunities and challenges for electric utility use cases, and ultimately help advance its adoption in the power system sector, to accelerate the equitable clean energy transition.