Photovoltaic (PV) waste, associated to the exponentially growing PV installations on global scale, presents today an emerging environmental challenge but also brings unprecedented and multifold value creation opportunities. In this context, significant PV business and research and development (R&D) efforts shift towards establishing a more sustainable, environmentally friendly and economically viable end-of-life (EoL) management for PV modules: including recycling, recovery of raw materials, repair/refurbishment and even re-use of decommissioned or failed PV modules. In the CIRCUSOL project, PV partners aspire to formalize the repair/refurbish and reuse value chains in the PV industry and propose a circular business model, based on a product-service system (PSS). Towards these goals, this review study introduces the relevant research groundwork, a status overview and today's R&D and business challenges in PV recycling, repair/refurbishment and re-certification aspects for second-life PV modules. The topics and the relevant reported literature are examined from both circular economy and technology perspective. The review indicates a considerable technological and operational know-how in PV EoL management that already exists and continuously evolves in mature PV markets. On the other hand, R&D in repair/refurbishment of decommissioned and/or failed PV modules remains scarce, and best practices and commercial services for reliability testing/recertification and trading of second-life PV modules are neither standardized nor consolidated into any PSS or business model.
Even if Electrochemical Storage (ES) devices are nowadays commonly used in a wide range of applications of different power, one application cannot be clearly addressed by only one specific technology of ES. Moreover, operating conditions such as charge/discharge rates or ambient temperatures have a huge influence on both ES real-time performance and lifetime. In this article, a new indicator of the energetic reserve, the State-of-Energy (SoE), is proposed to deal with modern Battery Management Systems (BMS) attendees: easy-to-implement, reliable given the operating conditions, using the power as a direct input parameter to manage the battery reserve. After a complete description of the SoE and the experimental characterization procedures, the paper presents some detailed examples of the SoE applications like storage technology comparison, smoothing of solar or wind production and finally on-line forecasting in advanced applications such as smart grids or electrical vehicle.Electrochemical Storage (ES) devices are now available in all fields of our daily lives, from portable electronic devices to health implants, in households for autonomous power supply, rural electrification, satellites for telecommunications and aerospace, defense and military applications. In particular, in the few past decades, ES devices have become a huge factor of development for intermittent renewable energies, for electric and hybrid vehicles and also for smart grids. 1,2 Electrochemical storage is thus one field within which the technologies are making constant progress to match the needs of the applications. Nowadays, storage systems provide a wide range of energy, power and cycling resistance ability, necessarily involving a wide diversity of packaging, assembling and materials. ES devices can now match applications from a few mWh to several MWh. 3 Today, as systems require more and more intelligence, predictability, precision and accuracy (e.g. electric vehicles and smartgrids), improvements have to be made to develop energetic models of ES that -are easy-to-implement, -use the power as a direct parameter of control, -have an acceptable reliability given the operating conditions, -can be easily upgraded during the lifetime.In the first section, the authors underline the mismatch of usual modeling approaches, mainly based on a double modeling of the capacity and the voltage, and the real needs for Energy Demand Size (EDS) and Energy Management Systems (EMS). The second section presents the State-of-Energy (SoE), as an indicator designed to address these requirements. In particular, the characterization procedures used to parameterize this SoE indicator are detailed. The third section describes how to operate this indicator in an easy-to-implement algorithm that is able to forecast the available energy for any power and temperature conditions. Dynamic Stress Tests (DST), with several severities operated, allowed the validation of this methodology, with an error inferior to +/− 3%, on commercially-available Li-ion batteries. Finally, th...
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