Petr Maule

Wind and Photovoltaic Large-Scale Regional Models for Hourly Production Evaluation

This work presents two large-scale regional models used for the evaluation of normalized power output from wind turbines and photovoltaic power plants on a European regional scale. The models give an estimate of renewable production on a regional scale with 1h resolution, starting from a mesoscale meteorological data input and taking in account the characteristics of different plants technologies and spatial distribution. An evaluation of the hourly forecasted energy production on a regional scale would be very valuable for the transmission system operators when making the long-term planning of the transmission system, especially regarding the cross-border power flows. The tuning of these regional models is done using historical meteorological data acquired on a per-country basis and using publicly available data of installed capacity.

Adequacy of operating reserves for power systems in future european wind power scenarios

Wind power generation is expected to increase in Europe by large extent in future. This will increase variability and uncertainty in power systems. Imbalances caused due to uncertainty in wind power forecast can trigger frequency instability in the system. These imbalances are handled using operating reserves. To study the effects of these imbalances, anticipated wind scenarios for European power systems are modelled for 2020 and 2030. Wind power forecasts for different time scales and real-time available wind power are modelled. Based on these studies, this paper qualitatively analyzes the adequacy of primary and secondary reserves requirements for future European power systems. This paper also discusses the challenges due to the uncertainty in wind power forecasts and their possible solutions for wind installation scenarios for 2020 and 2030.

Large-scale wind generation simulations: From the analysis of current installations to modelling the future

Modelling and understanding variability in wind generation will be increasingly important in the future with growing shares of wind power in energy systems. Crucially, the modelling needs to be extended to future scenarios, also considering the expected technological development of installations. Reanalysis data is often used in large-scale simulations to model the variability in wind. Wind power plant (WPP) data is also required, but may be only partially available. In this paper, a methodology for estimating missing hub height data is presented, using multiple regression models and large WPP and turbine datasets. The resulting estimated hub heights are presented on a pan-European level, and a scenario with capacity factor development until 2050 for two example countries is shown in detail.