4.8 Article

A Dynamic Analysis of Energy Storage With Renewable and Diesel Generation Using Volterra Equations

Journal

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 16, Issue 5, Pages 3451-3459

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2019.2932453

Keywords

Batteries; Mathematical model; Load modeling; Integral equations; Biological system modeling; Renewable energy sources; Deep Q-network (DQN); gated recurrent units (GRU); inverse problem; isolated power system; load forecasting; regularization; state of charge (SoC); state of health (SoH); storage control; Volterra integral equation (VIE)

Funding

  1. National Natural Science Foundation of China (NSFC)-Russian Foundation for Basic Research (RFBR) Exchange Program under NSFC Grant [61911530132]
  2. National Natural Science Foundation of China (NSFC)-Russian Foundation for Basic Research (RFBR) Exchange Program under RFBR Grant [19-58-53011]
  3. RFBR [18-31-00206]
  4. [III.17.3]
  5. [AAAA-A17-117030310442-8]
  6. [III.17.4]
  7. [AAAA-A17-117030310438-1]

Ask authors/readers for more resources

Energy storage systems will play a key role in the power system of the 21st century considering the large penetrations of variable renewable energy, growth in transport electrification, and decentralization of heating loads. Therefore, reliable real-time methods to optimize energy storage, demand response, and generation are vital for power system operations. This article presents a concise review of battery energy storage and an example of battery modeling for renewable energy applications and details an adaptive approach to solve this load leveling problem with storage. A dynamic evolutionary model based on the first-kind Volterra integral equation is used in both cases. A direct regularized numerical method is employed to find the least-cost dispatch of the battery in terms of the integral equation solution. Validation on real data shows that the proposed evolutionary Volterra model effectively generalizes a conventional discrete integral model taking into account both the state of health and the availability of generation/storage.

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