PVGnosis Project Objectives

PVgnosis aims to develop and demonstrate technical solutions to advance the operation and maintenance of PV plants towards the massive adoption of solar energy (see figure 1). Project results will benefit the photovoltaic industry and all related stakeholders by reducing the Levelised Cost of Electricity (LCoE) of PVs, extending their lifetime and competitiveness.

This project is built on two main axes: the development of an ICT platform for advancing the diagnosis, maintenance and management of several PV plants, and the progress of PV inverters with multi-functional operating modes and advanced fault diagnosis capabilities. Such solutions intercommunication and data exchange will improve and accelerate the maintenance procedure and effectively regulate the operation of each PV plant within the smart grid framework. 

Targeted use cases: in terms of the predictive maintenance toolkit, commercial & industrial solar instalments (>100kWp) are considered to be better suited for such application (i.e. costlier equipment and cumbersome assets’ maintenance tasks). For the inverter advances-side, these can be easily scalable and applicable for both small and large PV inverters. Especially for small PVs, the detection or diagnosis of a fault in the inverter can be reported through the web-service of the inverter in order to improve the maintenance procedure of the system and its reliability.

The main objectives, targets, key performance indicators (KPIs) and challenges of this project are described below:

  • Objective 1: Advanced visual analytics and automated diagnosis: Appropriate sensors’ installation and distribution, drones, thermal cameras and Inverter-based information gathered from real, PV plants and analysed via machine learning based pattern recognition techniques. Challenges: identify optimal sensor placement topology; correlate historical and real-time data in computationally efficient manner; introduce intuitive recommendation messages and graphics for alerting the platform's end user on the status of PV assets; Target and KPIs: identification of 96% of total abnormalities; reach 99% accuracy in anomalies classification; 
  • Objective 2: Improve the reliability of PV inverter(s) by developing a Fault Detection Isolation and Accommodation (FDIA) scheme to overcome actuator or sensor failures. Challenges: apply advanced model based fault diagnosis theory in a practical application such the PV inverters; the method should provide immunity against grid disturbances and harmonic distortion; distinguish between grid faults and inverter failures; accommodate single and multiple sensor failures; enable the exploitation of this scheme in commercial inverters as a software license. Target and KPIs: improve the reliability of PV inverter and extent its lifetime by 2-3 years in average; detect and accommodate of 95% of possible sensor failures, accelerate the maintenance procedure by 20%; reduce the cost of maintenance by 15%.
  • Objective 3: Develop flexible PV inverter(s) that can provide support and ancillary services to the grid under the smart grid framework with ultra-high penetration of solar energy. Challenges: develop control techniques to allow the operation of PV plants according to new functional modes; design a novel fault ride through support scheme considering the resistive characteristics of distribution lines; enable phase balancing operational mode for PV inverters; aware about the maximum available power during delta power limit operating mode; define business models for the exploitation of new ancillary services; include the proposed support scheme in the grid codes. Target and KPIs: develop new multi-functional products (i.e., PV inverters); increase by 20% the maximum allowable limit for PV penetration in the distribution grid; increase the profit of prosumers/producers by exploiting the ancillary services enabled by the PV inverter; increase by 10% the utilization of existing grid capacity by symmetrizing the operation of a distribution feeder through phase balancing mode; reduce by 10% the System Average Interruption Duration Index (SAIDI) by avoiding thermal limits and voltage constraints violations; improve by 5% the distribution grid voltage stability.
  • Objective 4: Develop an ICT platform for advancing the maintenance and operation procedure of PV plants to improve the competiveness of PV plants. Challenges: enable the communication between the ICT platform and several inverters, sensors etc., via developed APIs; address cyber-security concerns for the platform; address the need of PV plants operator for remote, fast and low-cost maintenance procedure; coordinate the operation (ancillary services) of PV systems to maximize their profit and ensure power grid concerns. Target and KPIs: remote and automated maintenance of several PV plants; remote management and coordination of PV plants; accelerate the maintenance procedure by 40%; reduce the cost of maintenance by 30%.