Abstract
This paper presents an energy storage system (ESS) sizing model and reliability assessment framework to quantify reliability improvements due to ESS of electric energy systems with high penetration of renewables. The model formulation takes into account: (a) variable generation (VG) forced outage rates (FORs), (b) reserve and demand requirements, and (c) conventional generation (CG) operational constraints and practices. Correlation coefficients among wind speed, solar radiation, and demand are computed using the least square estimation method (LSE). Depending on the correlation, probabilistic models for the composite demand are computed and integrated into the ESS sizing model. Subsequently, the ESS optimal sizes are computed along with the ESS optimal charging and discharging schedules. Then, the reliability is quantified using the probabilistic production costing (PPC) method. A case study is presented in which one VG was approximated as independent variable because of its low correlation with demand and other VG. The case study compares the error when treating the VG as independent.
| Original language | English |
|---|---|
| Pages (from-to) | 106-117 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 37 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jan 2022 |
Bibliographical note
Publisher Copyright:© 1969-2012 IEEE.
Keywords
- Energy storage sizing
- loss of load probability
- production costing
- seasonal correlation
- variable generation
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering