Predicting Battery Cycle Life with Few-Shot Transfer Learning over Heterogeneous Datasets

Runyao Yu^1,2,3, Jiaqi Wang¹, Yongsheng Han¹, Chi Zhang¹, Teddy Szemberg O’Connor³, Jochen L. Cremer^1,2

¹Delft University of Technology; ²Austrian Institute of Technology; ³Rimac Technology

Redesign of Large-Scale Irrigation Systems for Flexible Energy Storage

Sergi Costa-Dilmé, Juan Carlos Olives-Camps, Paula Muñoz-Peña, Pau Garcia-Motilla, Oriol Gomis-Bellmunt, Eduardo Prieto-Araujo

CITCEA-UPC, Spain

Electrical Storage Design in Multi-Energy Systems: Impact of Component Model Choice

Philipp Glücker^1,2,3, Sleiman Mhanna³, Thiemo Pesch¹, Pierluigi Mancarella^3,4, Andrea Benigni^1,2,5

¹Forschungszentrum Jülich GmbH, Institute of Climate and Energy Systems, ICE-¹Energy Systems Engineering, Jülich 52425, Germany; ²RWTH Aachen University, Aachen 52056, Germany; ³The University of Melbourne, Department of Electrical and Electronic Engineering, Parkville 3010, Victoria, Australia; ⁴University of Manchester, Department of Electrical and Electronic Engineering, M13 9PL Manchester, UK; ⁵JARA-Energy, Jülich 52425, Germany

Battery Storage Considerations for Mitigating the Impact of Increased Integration of Renewable Sources: Case Study for Spain

Alicia Mortera-Canga^1,2, Diego Iribarren¹, Milan Prodanovic¹

¹IMDEA Energy, Spain; ²Rey Juan Carlos University, Spain

Optimal Planning of Large-Scale Wind-Storage Power Plant Considering AC Power Flow Based on Stackelberg Game Theory

Miao Cheng^1,2, Qinfei Long^1,2, Yunhe Hou^1,2, Liang Liang³, Xiaodong Xu⁴

¹The University of Hong Kong, Hong Kong S.A.R., China; ²HKU Shenzhen Institute of Research and Innovation, Shenzhen, China; ³Harbin Institute of Technology, Shenzhen, China; ⁴State Grid Shanghai Municipal Electric Power Company, Shanghai, China

Energy Management of Large-Scale Battery Storage Systems: Field Evaluation of Battery Aging and System Efficiency

Lucas Koltermann^1,2,3, Mauricio Celi Cortés^1,2,3, Sebastian Zurmühlen^1,2,3, Dirk Uwe Sauer^1,2,3,4,5

¹Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, 52074 Aachen, Germany; ²Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, 52074 Aachen, Germany; ³Jülich Aachen Research Alliance, JARA-Energy, 52056 Aachen, 52425 Jülich, Germany; ⁴Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research Helmholtz-Institute Münster: Ionics in Energy Storage (IEK-12), 52425 Jülich, Germany; ⁵Center for Ageing, Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems (CARL), RWTH Aachen University, 52074 Aachen, Germany, Germany

A Novel Deep Learning Method for Real-Time Estimation of Lithium-Ion Battery Capacity

Zihuan Zhang, ZHONG FAN, Cesar Ruiz

Exeter University, United Kingdom

Optimizing Second-Life Battery Use in Renewable Energy Storage: A Deep Reinforcement Learning Approach

YUANHAO WU, ZHONG FAN

Exeter University, United Kingdom

Linear energy storage and flexibility model with ramp rate, ramping, deadline and capacity constraints

Md Umar Hashmi¹, Dirk Van Hertem¹, Aleen van der Meer², Andrew Keane²

¹KU Leuven & EnergyVille, Genk, Belgium; ²University College Dublin, Dublin, Ireland