Abstract
Battery energy storage systems are becoming an integral part of the modern power grid, mainly to maximise the utilisation of renewable energy sources and negate the intermittence associated with different weather condition, as well as to support grid during extreme operating conditions. Precise and real-time knowledge of battery available capacity at a given instance is of paramount importance for optimal and efficient energy management of the power grid with high penetration of renewable energy sources, as well to ensure the highest utilisation of a battery life. State of Charge (SoC) is the most commonly used measure of the battery available capacity that quantifies the percentage of battery nominal capacity that is available at a given instance. An efficient SoC estimation approach for batteries in power grid is expected to possess attributes such as high accuracy, low complexity, near real-time estimation capability, chemistry agnostic nature, etc. In the literature, an overwhelming amount of battery SoC approaches with different levels of implementation complexity and accuracy have been reported. With a view to presenting critical analysis of the existing battery SoC estimation approaches from the perspective of battery energy storage systems used in power grids, this paper presents a comprehensive review of the commonly used battery SoC estimation approaches. The presented review includes a detailed description of each of the approaches and highlights their pros and cons in power grid applications.
| Original language | English |
|---|---|
| Article number | 102801 |
| Number of pages | 31 |
| Journal | Sustainable Energy Technologies and Assessments |
| Volume | 54 |
| Early online date | 21 Oct 2022 |
| DOIs | |
| Publication status | Published - Dec 2022 |
| Externally published | Yes |
Keywords
- State of charge (SoC)
- Battery capacity estimation
- Direct and indirect SoC estimation
- Kalman filter
- Coulomb counting
- Artificial Neural Networks
- Observer models
- Equivalent circuit models