Model-Based Dispatch Strategies for Lithium-Ion Battery Energy Storage Applied to Pay-as-Bid Markets for Secondary Reserve

被引:52
|
作者
Goebel, Christoph [1 ]
Hesse, Holger [1 ]
Schimpe, Michael [1 ]
Jossen, Andreas [1 ]
Jacobsen, Hans-Arno [1 ]
机构
[1] Tech Univ Munich, D-80333 Munich, Germany
关键词
Ancillary services; battery aging; economic value; lithium-ion batteries; optimization; SYSTEMS;
D O I
10.1109/TPWRS.2016.2626392
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Due to their decreasing cost, lithium-ion batteries (LiB) are becoming increasingly attractive for grid-scale applications. In this paper, we investigate the use of LiB for providing secondary reserve and show how the achieved cost savings could be increased by using model-based optimization techniques. In particular, we compare a maximum use dispatch strategy with two different cost-minimizing strategies. For the estimation of state-dependent battery usage cost, we combine an existing electrothermal LiBmodel of amature lithium-iron-phosphate battery cell with corresponding semiempirical calendar and cycle aging models. We estimate the benefit of storage operation from the system operator's point of view by gauging the avoided cost of activated reserve. Our evaluation is based on two years worth of data from the German reserve market. The proposed cost minimizing dispatch strategies yield significantly better results than a dispatch strategy that maximizes battery utilization.
引用
收藏
页码:2724 / 2734
页数:11
相关论文
共 50 条
  • [21] Operational Reliability Modeling and Assessment of Battery Energy Storage Based on Lithium-ion Battery Lifetime Degradation
    Cheng, Lin
    Wan, Yuxiang
    Zhou, Yanglin
    Gao, David Wenzhong
    JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2022, 10 (06) : 1738 - 1749
  • [22] Operational Reliability Modeling and Assessment of Battery Energy Storage Based on Lithium-ion Battery Lifetime Degradation
    Lin Cheng
    Yuxiang Wan
    Yanglin Zhou
    David Wenzhong Gao
    Journal of Modern Power Systems and Clean Energy, 2022, 10 (06) : 1738 - 1749
  • [23] Nonlinear Mixed Effect Model-Based Prognostics for Lithium-ion Battery Charge Decay
    Ossai, Chinedu, I
    Raghavan, Nagarajan
    2018 ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM (RAMS), 2018,
  • [24] Passive hybridization of a photovoltaic module with lithium-ion battery cells: A model-based analysis
    Joos, Stella
    Weisshar, Bjoern
    Bessler, Wolfgang G.
    JOURNAL OF POWER SOURCES, 2017, 348 : 201 - 211
  • [25] Robustness and Reliability of Model-based Sensor Data Fusion in a Lithium-Ion Battery System
    Schneider, Dominik
    Endisch, Christian
    2020 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA), 2020, : 685 - 691
  • [26] Experimental investigation of lithium-ion battery cells for model-based thermal management systems
    Capasso, C.
    Sebastianelli, G.
    Sequino, L.
    Vaglieco, B. M.
    Veneri, O.
    IFAC PAPERSONLINE, 2022, 55 (24): : 209 - 214
  • [27] Model-based state of X estimation of lithium-ion battery for electric vehicle applications
    Shrivastava, Prashant
    Soon, Tey Kok
    Bin Idris, Mohd Yamani Idna
    Mekhilef, Saad
    Adnan, Syed Bahari Ramadzan Syed
    INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2022, 46 (08) : 10704 - 10723
  • [28] ELECTROCHEMICAL MODEL-BASED AGING CHARACTERIZATION OF LITHIUM-ION BATTERY CELL IN ELECTRIFIED VEHICLES
    Huang, Meng
    Kumar, Mrinal
    PROCEEDINGS OF THE ASME 11TH ANNUAL DYNAMIC SYSTEMS AND CONTROL CONFERENCE, 2018, VOL 3, 2018,
  • [29] Deep Reinforcement Learning-Based Energy Storage Arbitrage With Accurate Lithium-Ion Battery Degradation Model
    Cao, Jun
    Harrold, Dan
    Fan, Zhong
    Morstyn, Thomas
    Healey, David
    Li, Kang
    IEEE TRANSACTIONS ON SMART GRID, 2020, 11 (05) : 4513 - 4521
  • [30] Analysis of the Lithium Storage Mechanism in the SiO x /C Composite Based on the Performance Variation Applied to a Lithium-Ion Battery
    Zhang, Duxin
    Fan, Meilin
    Tan, Shifeng
    Pan, Hongfei
    Tu, Wenmao
    Zhang, Haining
    Wang, Yadong
    ENERGY & FUELS, 2023, 37 (13) : 9641 - 9649