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Decomposition of observed voltages and currents into harmonic terms that are phasesynchronised to the grid voltage is a challenge in real-time systems. Kalman observers are used to achieve this with the additional advantage of avoiding explicit phase-locking while producing quadrature components useful in instantaneous calculation of reactive power and in providing feed-forward compensation terms.

In photovoltaic (PV) projects, it is important to establish a common practice for professional risk assessment, which serves to reduce the risks associated with related investments. The objective of this paper is to present a methodology on how to improve the current understanding of several key aspects of technical risk management during the PV project lifecycle, with the identification of technical risks and their economic impact. To achieve this, available statistical data of failures during a PV project have been collected with the aim to (i) suggest a guideline for the categorisation of failure and (ii) develop a methodology for the assessment of the economic impact of failures occurring during operation but which might have originated in previous phases. The risk analysis has the aim to assess the economic impact of technical risks and how this can influence various business models and the levelised cost of electricity. This paper presents the first attempt to implement cost-based failure modes and effects analysis to the PV sector and to define a methodology for the estimation of economic losses because of planning failures, system downtime and substitution/repair of components. The methodology is based on statistical analysis and can be applied to a single PV plant or to a large portfolio of PV plants in the same market segment. The quality of the analysis depends on the amount of failure data available and on the assumptions taken for the calculation of a cost priority number. The overall results can be linked to the cost of periodic and corrective maintenance and form the basis to estimate the impact of various risk and mitigation scenarios in PV business models.

Due to the increasing integration of solar power into the electrical grid, forecasting short-term solar irradiance has become key for many applications, e.g. operational planning, power purchases, reserve activation, etc. In this context, as solar generators are geographically dispersed and ground measurements are not always easy to obtain, it is very important to have general models that can predict solar irradiance without the need of local data. In this paper, a model that can perform short-term forecasting of solar irradiance in any general location without the need of ground measurements is proposed. To do so, the model considers satellite-based measurements and weather-based forecasts, and employs a deep neural network structure that is able to generalize across locations; particularly, the network is trained only using a small subset of sites where ground data is available, and the model is able to generalize to a much larger number of locations where ground data does not exist. As a case study, 25 locations in The Netherlands are considered and the proposed model is compared against four local models that are individually trained for each location using ground measurements. Despite the general nature of the model, it is shown show that the proposed model is equal or better than the local models: when comparing the average performance across all the locations and prediction horizons, the proposed model obtains a 31.31% rRMSE (relative root mean square error) while the best local model achieves a 32.01% rRMSE. (Jesus Lago) forecasting irradiance over short time horizons. In particular, in addition to activation of reserves to manage the grid stability, short-term forecasts of solar irradiance are paramount for operational planning, switching sources, programming backup, short-term power trading, peak load matching, scheduling of power systems, congestion management, and cost reduction [2][3][4].

2Photovoltech SA, c/o IMEC vzw, B-3001 Leuven, Belgium Islanding is still one of the major controversial subjects in the international harmonization of grid connection requirements for distributed generation, and particularly photovoltaics. As long as islanding is not intended in order to back up a loss of mains, it should be avoided. The present study reviews the theory of unintentional islanding and assesses the probability of occurrence of the phenomenon, based on previous studies and theoretical considerations. While islanding is virtually impossible if only a small number of distributed generation units is connected to a distribution grid, with higher distributed generation densities, the possibility of islanding becomes realistic. The risk associated with unintentional islanding is estimated, and adequate requirements for functional safety of protection devices are determined in order to ensure the necessary additional degree of safety to be introduced by an islanding prevention device. Finally, a fundamental set of requirements with regard to islanding, to be included in an international grid connection guideline, is derived from the study.