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High shares of intermittent renewable power generation in a European electricity system will require flexible backup power generation on the dominant diurnal, synoptic, and seasonal weather timescales. The same three timescales are already covered by today’s dispatchable electricity generation facilities, which are able to follow the typical load variations on the intra-day, intra-week, and seasonal timescales. This work aims to quantify the changing demand for those three backup flexibility classes in emerging large-scale electricity systems, as they transform from low to high shares of variable renewable power generation. A weather-driven modelling is used, which aggregates eight years of wind and solar power generation data as well as load data over Germany and Europe, and splits the backup system required to cover the residual load into three flexibility classes distinguished by their respective maximum rates of change of power output. This modelling shows that the slowly flexible backup system is dominant at low renewable shares, but its optimized capacity decreases and drops close to zero once the average renewable power generation exceeds 50% of the mean load. The medium flexible backup capacities increase for modest renewable shares, peak at around a 40% renewable share, and then continuously decrease to almost zero once the average renewable power generation becomes larger than 100% of the mean load. The dispatch capacity of the highly flexible backup system becomes dominant for renewable shares beyond 50%, and reach their maximum around a 70% renewable share. For renewable shares above 70% the highly flexible backup capacity in Germany remains at its maximum, whereas it decreases again for Europe. This indicates that for highly renewable large-scale electricity systems the total required backup capacity can only be reduced if countries share their excess generation and backup power.
The transition to a future electricity system based primarily on wind and solar PV is examined for all regions in the contiguous US. We present optimized pathways for the build-up of wind and solar power for least backup energy needs as well as for least cost obtained with a simplified, lightweight model based on long-term high resolution weather-determined generation data. In the absence of storage, the pathway which achieves the best match of generation and load, thus resulting in the least backup energy requirements, generally favors a combination of both technologies, with a wind/solar PV (photovoltaics) energy mix of about 80/20 in a fully renewable scenario. The least cost development is seen to start with 100% of the technology with the lowest average generation costs first, but with increasing renewable installations, economically unfavorable excess generation pushes it toward the minimal backup pathway. Surplus generation and the entailed costs can be reduced significantly by combining wind and solar power, and/or absorbing excess generation, for example with storage or transmission, or by coupling the electricity system to other energy sectors.
Statistical physics of power flows on networks with a high share of fluctuating renewable generation
(2010)
Renewable energy sources will play an important role in future generation of electrical energy. This is due to the fact that fossil fuel reserves are limited and because of the waste caused by conventional electricity generation. The most important sources of renewable energy, wind and solar irradiation, exhibit strong temporal fluctuations. This poses new problems for the security of supply. Further, the power flows become a stochastic character so that new methods are required to predict flows within an electrical grid. The main focus of this work is the description of power flows in a electrical transmission network with a high share of renewable generation of electrical energy. To define an appropriate model, it is important to understand the general set-up of a stable system with fluctuating generation. Therefore, generation time series of solar and wind power are compared to load time series for whole Europe and the required balancing or storage capacities analyzed. With these insights, a simple model is proposed to study the power flows. An approximation to the full power flow equations is used and evaluated with Monte-Carlo simulations. Further, approximations to the distributions of power flows along the links are analytically derived. Finally, the results are compared to the power flows calculated from the generation and load data.