• Energy Research
• engineering and technology close
• US close
• Chinese Academy of Sciences close

Abstract In order to maximize the operation profit while maintaining the service quality, an effective energy management scheme is highly needed for the Photovoltaic-assisted Charging Station (PVCS). Considering the uncertainty of Electric Vehicle (EV) charging demand and PV power output, it will be challenging to determine the charging power for EVs to make informed real-time decisions. In this study, an online energy management method leveraging both offline optimization and online learning is proposed. In order to maximize the self-consumption of Photovoltaic (PV) energy and decide the power supplied from the power grid with Time-of-Use (TOU) pricing, here online learning is coupled with the rule-based decision-making to obtain a real-time online algorithm. The knowledge base for online learning is derived and updated from the results of offline optimization after every operation day. The PVCS located at workplace parking lots is used as an example to test the proposed method. The simulation results show that the method can be implemented without the information on future PV power and charging demand. The obtained results are close to the optimal results from offline optimization.

Abstract In order to maximize the operation profit while maintaining the service quality, an effective energy management scheme is highly needed for the Photovoltaic-assisted Charging Station (PVCS). Considering the uncertainty of Electric Vehicle (EV) charging demand and PV power output, it will be challenging to determine the charging power for EVs to make informed real-time decisions. In this study, an online energy management method leveraging both offline optimization and online learning is proposed. In order to maximize the self-consumption of Photovoltaic (PV) energy and decide the power supplied from the power grid with Time-of-Use (TOU) pricing, here online learning is coupled with the rule-based decision-making to obtain a real-time online algorithm. The knowledge base for online learning is derived and updated from the results of offline optimization after every operation day. The PVCS located at workplace parking lots is used as an example to test the proposed method. The simulation results show that the method can be implemented without the information on future PV power and charging demand. The obtained results are close to the optimal results from offline optimization.

AbstractImproving the long-term stability of perovskite solar cells is critical to the deployment of this technology. Despite the great emphasis laid on stability-related investigations, publications lack consistency in experimental procedures and parameters reported. It is therefore challenging to reproduce and compare results and thereby develop a deep understanding of degradation mechanisms. Here, we report a consensus between researchers in the field on procedures for testing perovskite solar cell stability, which are based on the International Summit on Organic Photovoltaic Stability (ISOS) protocols. We propose additional procedures to account for properties specific to PSCs such as ion redistribution under electric fields, reversible degradation and to distinguish ambient-induced degradation from other stress factors. These protocols are not intended as a replacement of the existing qualification standards, but rather they aim to unify the stability assessment and to understand failure modes. Finally, we identify key procedural information which we suggest reporting in publications to improve reproducibility and enable large data set analysis.

AbstractImproving the long-term stability of perovskite solar cells is critical to the deployment of this technology. Despite the great emphasis laid on stability-related investigations, publications lack consistency in experimental procedures and parameters reported. It is therefore challenging to reproduce and compare results and thereby develop a deep understanding of degradation mechanisms. Here, we report a consensus between researchers in the field on procedures for testing perovskite solar cell stability, which are based on the International Summit on Organic Photovoltaic Stability (ISOS) protocols. We propose additional procedures to account for properties specific to PSCs such as ion redistribution under electric fields, reversible degradation and to distinguish ambient-induced degradation from other stress factors. These protocols are not intended as a replacement of the existing qualification standards, but rather they aim to unify the stability assessment and to understand failure modes. Finally, we identify key procedural information which we suggest reporting in publications to improve reproducibility and enable large data set analysis.