Energy Systems Division
Operations & Maintenance (O&M) for Offshore Wind Energy: Opportunities and Challenges
Presented by the IISE Energy Systems Division
Speakers: Dr. Shawn Sheng, Noah Myrent, and Jade Mcmorland
Wednesday, March 27, 1 p.m. ET
Offshore wind energy is poised to play a major role in the transition toward a more sustainable energy landscape. However, fully unlocking the potential of offshore wind energy entails addressing unique operations and maintenance (O&M) challenges including a harsh and dynamic marine environment, special logistical requirements,
and complex reliability considerations. This panel will dive into the research challenges and opportunities of O&M in offshore wind energy through the perspectives of three O&M experts.
Watch Video
Machine Learning For End-To-End Power Systems Operations
Presented by the IISE Energy Systems Division
2 p.m. ET Feb. 21
Presenter: Pascal Van Hentenryck
This talk reviews progress in machine learning for power systems. In particular, it focuses on optimization proxies for market-clearing algorithms, including unit commitment, reliability commitment, economic dispatch, and end-to-end risk management. The talk will cover both novel methodology developments, as well as their applications to large-scale power systems. It will also review future research in this topic.
Watch Video
Data Science for Wind Energy
Presented by the IISE Energy Systems (ES) Division
3 p.m. ET Dec. 9
Presenter: Dr. Yu Ding
Wind energy is one of the fastest-growing clean energy sources. Despite the significant growth in the past two decades, wind energy missed some intermediate goals set forth earlier. In his book, Data Science for Wind Energy, Dr. Yu Ding demonstrates how statistical and machine learning methods can help address research needs in wind energy applications.
Dr. Ding will discuss some challenges encountered in wind applications and present use cases in which statistical/machine learning models and solutions make sensible impacts.
Download Presentation
Incentive and Social Welfare Implications of Carbon Capture and Storage Policies
A Webinar presented by the IISE Energy Systems Division
March 2, 10 a.m. ET
Presenter: Joseph E. Duggan, Dr. Jonathan Ogland-Hand
Carbon Capture and Storage (CCS) is increasingly being seen as a powerful tool in decarbonizing the power sector and ameliorating the effects of climate change. We examine a stylized model of carbon capture and storage given different regulatory and market structure regimes to examine the incentive effects and social welfare implications of proposed regulatory frameworks.
Watch Video
A Stochastic Programming Framework for Resource Allocation on a Farm Under Climate and Weather Uncertainty
Nov. 18, 2021
Presenter: Erick C. Jones Jr.
Climate change, extreme weather events, and water scarcity have severely impacted the agricultural sector. Under scarce conventional water supplies, a farm faces a decision between reducing production through deficit irrigation and leveraging alternative water and energy resources to continue producing large quantities of crops and these investments would have to be balanced against an unknown climate. Therefore, we develop a framework for farm investment decisions structured as a two-stage stochastic quadratically constrained linear program that maximizes farm profit over a 25-year period while considering an uncertain future climate and the costs of investing and operating various electricity and water technologies. We create four representative climate futures and two climate probability distributions that represent different beliefs that the decision maker might have about the likelihood of each climate scenario occurring.
Download Presentation |
There has been a rapid growth of distributed energy resources (DERs) at the distribution level of power systems, which, if managed properly, can help improve the entire power grid’s efficiency and reliability, offset electricity price volatility, and promote renewable energy.
Real-time thermal rating (RTTR) is a smart grid technology that can significantly improve the utilization of existing transmission and distribution systems infrastructure by allowing the ratings of electrical conductors and equipment to be increased based on real-time weather
information.
In this webinar, we will present the copula-based prognosis method for proactive maintenance of the lithium-ion battery by accurately predicting its remaining useful life.