University of Rhode Island PV Battery Energy Storage Dataset for SOC Tracking (URI-PBEST)

The URI-PBEST dataset is a comprehensive experimental dataset initiated at the Array Signal Processing for Information REtrieval (ASPIRE) Lab at the University of Rhode Island (URI). The main goal of the project is to support research on state-of-charge (SOC) estimation in photovoltaic-coupled battery energy storage systems (PV-BESS). The dataset provides real-world measurements capturing the interaction between environmental conditions and battery behavior. It was collected during 2024–2025 at the URI Kingston Campus and is designed to enable the development and evaluation of both data-driven and model-based SOC estimation techniques under realistic operating conditions. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Data Collection Overview: Charging Data:Collected using a PV-BESS setup where a portable solar panel is connected to a lithium-ion battery system. Measurements are recorded at a 1-minute interval, providing moderate-to-high temporal resolution suitable for time-series modeling. Data were collected in 3-hour segments (Quarters), and the data length for each segment is consistent. Discharging Data:Compiled under controlled discharging experiments using a programmable electronic load (DL24P tester) in constant current mode to ensure repeatability and consistency. Discharge tests are performed at multiple current levels (e.g., 1 A, 1.5 A, 2 A), providing benchmark data for evaluating battery performance, degradation behavior, and SOC estimation algorithms under known load conditions. Open-Circuit Data:Measurements were taken when the battery was in open-circuit condition, enabling the OCV-SOC mapping of the battery, suitable for model-based SOC estimation. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Dataset Organization The dataset is distributed as a compressed ZIP file containing multiple Excel files, organized according to experiment type: · charge-data.xlsx — PV-BESS charging data · discharge-data.xlsx — BESS discharging data · open-circuit-charge.xlsx — Open-circuit measurements during charging · open-circuit-discharge.xlsx — Open-circuit measurements during discharging --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 1. charge-data.xlsx Sheets: 22 sheets, each named mmddyyyy(Q#) where Q# = Quarter Number Features and Units: time: Timestamp of measurement (HH:MM) ghi: Global Horizontal Irradiance (W/m²) current: PV panel current/ BESS charging current (Amps) voltage: BESS terminal voltage (Volts) soc: State of charge (Reference/ground-truth) (%) panel_temp: Solar panel temperature (°C) amb_temp: Ambient air temperature (°C) humidity: Relative humidity (%) p_dc: DC power of BESS (voltage × current) (Watts) date: Recording date (MM-DD-YYYY) quarter: Quarter of the year (1–4) weather: Weather categorization (e.g., sunny, partly-cloudy, overcast) wind: Average wind speed accorss the period (km/hr) --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 2. discharge-data.xlsx Sheets: 12 sheets, each named mm.dd.yy(@#Amps) Features and Units: time : Elapsed time since start of discharge (minutes) voltage: Battery terminal voltage (Volts) dis_power: Discharge power output (Watts) bat_res: Internal battery resistance (milliOhm) bat_temp: Battery temperature (°C) dis_cap: Cumulative discharged capacity (mAh) dis_energy: Cumulative discharged energy (Wh) soc: State of charge (Reference/ground-truth) (%) amb_temp: Ambient temperature (°C) humidity: Relative humidity (%) dis_current: Discharge current (Amps) --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 3. open-circuit-charge.xlsx Sheets: 1 sheet Features and Units soc: State of charge (Reference/ground-truth) (%) v_open: Open-circuit voltage at given SOC (Volts) current rate: Charge/discharge current rate (Amps) --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 4. open-circuit-discharge.xlsx Sheets: 3 sheets, each named @#Amp Features and Units: time: Elapsed time since start (HH:MM:SS) v_open: Open-circuit voltage (Volts) v_close: Closed-circuit voltage (under load) (Volts) soc: State of charge (Reference/ground-truth) (%) bat_cap: Cumulative discharge capacity (mAh) bat_energy: Cumulative discharge energy (Wh) bat_res: Internal battery resistance (milliOhm) bat_temp: Battery temperature (°C) dis_ckt_res: Resistance of discharge circuit (milliOhm) power: Power output during discharge (Watts) --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Matlab Scripts: Three matlab scripts are uplaoded along with the dataset. the scipts visualize portion of the dataset and illustrate the OCV-SOC relation of the battery, plots SOC level duing different charing and discharging conditions. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Several Publications utilizes the dataset. A data descriotpr article has also been made that describe the dataset in more detail. Data Descriptor Article: More detailed information about the dataset is available in the data descriptor article. [1] S. Rahman, K. Adhikari, and K. Icer, “Descriptor: University of Rhode Island Photovoltaic Battery Energy Storage Dataset for SOC Tracking (URI-PBEST),” unpublished, in preparation. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Publications: Users are strongly encouraged to review the associated published work for an in-depth understanding of the dataset and to cite all relevant publications where appropriate. [1] S. Rahman and K. Adhikari, "Feature Evaluation in Machine Learning-Based Soc Estimation for PV Battery Systems," 2025 IEEE International Conference on Energy Technologies for Future Grids (ETFG), Wollongong, Australia, 2025, pp. 1-6, doi: 10.1109/ETFG61999.2025.11401241. [2] S. Rahman and K. Adhikari, "Evaluation of Bayesian SOC Estimators in PV System with and without Missing Measurements," 2025 International Conference on Electrical and Computer Engineering Researches (ICECER), Antananarivo, Madagascar, 2025, pp. 1-7, doi: 10.1109/ICECER65523.2025.11401349. [3] S. Rahman and K. Adhikari, "Extended and Unscented Kalman Filter Variants for Tracking the State of Charge of PV Battery Systems," 2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET), Paris, France, 2025, pp. 1-6, doi: 10.1109/ICECET63943.2025.11472367. [4] K. Icer, S. Rahman and K. Adhikari, "Autoregressive Modeling of Time Series in Renewable Energy Systems," 2024 IEEE 15th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), Yorktown Heights, NY, USA, 2024, pp. 372-378, doi: 10.1109/UEMCON62879.2024.10754746. [5] S. Rahman and K. Adhikari, Specialized State Space Battery Modeling for EKF-based SOC Estimation in Photovoltaic Battery Storage Systems, under review, 2025. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Contacts: For more information please contact Primary contact person: Showrov Rahman ([e-mail]) Additional Contact information: Kaushallya Adhikari ([e-mail])