Abstract
Renewable energy generation and energy storage systems are considered key technologies for reducing greenhouse gas emissions. Energy system planning and operation requires more accurate forecasts of intermittent renewable energy resources that consider the impact of battery degradation on the system caused by the accumulation of charging and discharging cycles. In this study, a statistical model is presented for forecasting a day-ahead photovoltaic (PV) generation considering solar radiation and weather parameters. In addition, the technical performance of energy storage systems (ESS) should be evaluated by considering battery degradation that occurs during the charge and discharge cycles of the battery. In this study, a battery degradation model based on the data-driven method is used. Based on a suitable forecasting model, ESS scheduling is performed to charge the maximum amount of PV generation and discharge for the self-consumption of the customer load when PV generation ends. Since the battery is highly dependent on operating conditions such as depth of discharge, state of charge and temperature, two different ESS charge and discharge modes are proposed. From the simulation with the battery degradation model using parameters derived from experiments, we show that the battery is degraded along with charging cycles during testing periods. Variations in state of health are observed owing to the different characteristics of the battery according to the ESS operation modes, which are divided into the low and high SOC. Through experimental validation, it is proved that the state of charge (SOC), 0.45 is the optimal threshold that can determine the low and high SOC. Finally, the simulation results lead to the conclusion that the battery degradation in different operation modes should be taken into account to extend the end of life efficiently.
Highlights
While an increase in fossil energy consumption contributes to global warming, countries are seeking pathways to reduce greenhouse gas emissions by substituting fossil energy with renewable energy after the Paris agreement in 2015 [1]
This study focuses on battery degradation in the self-consumption energy storage system (ESS), exploring a correlation between the state of charge (SOC) and the state of health (SOH) of the Li–phosphate (LFP) battery
To calculate the statistical model parameters, two weeks of PV generation data and relevant datasets are used for training, and the selected model is tested with another ten days of data
Summary
While an increase in fossil energy consumption contributes to global warming, countries are seeking pathways to reduce greenhouse gas emissions by substituting fossil energy with renewable energy after the Paris agreement in 2015 [1]. Because of increasing concerns on grid resiliency caused by volatile renewable electricity generation from solar and wind, secure grid management has risen as Electronics 2020, 9, 701; doi:10.3390/electronics9040701 www.mdpi.com/journal/electronics. The energy storage system (ESS) is expected to play a pivotal role in the distributed energy system which comprises variable renewable energy resources [2,3]. The ESS has been expected to bring benefits to market and system while stabilizing the electric market price, freeing the volatility by renewable energy, avoiding transmission congestion charges, and allowing a market-driven electricity dispatch through customer’s market participation [5].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
