The Role of Electric Grid Research in Addressing Climate Change
Addressing the urgency of climate change necessitates a coordinated and inclusive effort from all relevant stakeholders. Critical to this effort is the modeling, analysis, control, and integration of technological innovations within the electric energy system, which plays a crucial role in scaling up climate change solutions. This perspective article presents a set of research challenges and opportunities in the area of electric power systems that would be crucial in accelerating Gigaton-level decarbonization. Furthermore, it highlights institutional challenges associated with developing market mechanisms and regulatory architectures, ensuring that incentives are aligned for stakeholders to effectively implement the technological solutions on a large scale.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
RL for Mitigating Cascading Failures: Targeted Exploration via Sensitivity Factors
Electricity grid's resiliency and climate change strongly impact one another due to an array of technical and policy-related decisions that impact both. This paper introduces a physics-informed machine learning-based fra…
Physics-informed machine learningSensitivityEnergy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutrality
The transition towards carbon-neutral electricity is one of the biggest game changers in addressing climate change since it addresses the dual challenges of removing carbon emissions from the two largest sectors of emitt…
Decision MakingDesigning realistic RL environment for power systems
Power grids are critical infrastructure: ensuring they are reliable, robust and secure is essential to humanity,to everyday life, and to progress. With increasing renewable generation, growing electricity demand, and mor…
Reinforcement Learning (RL)Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods
With the growing popularity of electric vehicles as a means of addressing climate change, concerns have emerged regarding their impact on electric grid management. As a result, predicting EV charging demand has become a …
Time Series ForecastingFoundation Models for the Electric Power Grid
Foundation models (FMs) currently dominate news headlines. They employ advanced deep learning architectures to extract structural information autonomously from vast datasets through self-supervision. The resulting rich r…