To integrate renewables into the grid some management techniques need to be developed. However when enough affordable storage is available then it will become easier.
The following are from two reports. One is the way China is approaching it by clever software and management, the other is the German blitzkrieg approach of over capacity. In reality until large scale affordable storage is available, it is best to design and manage grids with what is available and use DC transmission lines for long distance transmission.
Some countries are managing this well while others are heading into the dark ages (pun intended) to legislate against the use of renewable energies (5 states in the USA so far)
China: The power of wind energy and how to use it
Distributed Model Predictive Load Frequency Control of Multi-area Power System with DFIGs
Wind offers an immense, never ending source of energy that can be successfully harnessed to power all of the things that currently draw energy from non-renewable resources. The wind doesn’t always blow, though.
Researchers from North China Electric Power University and North China University of Science and Technology recently developed a model to help predict wind frequency and potential contributions to more traditional energy sources. The scientists published their paper in IEEE/CAA Journal of Automatica Sinica (JAS).
“Reliable load frequency control is crucial to the operation and design of modern electric power systems,” wrote Yi Zhang, a doctoral student at the North China Electric Power University and an author on the paper. “Due to the randomness and intermittence of the wind power, the controllability and availability of wind power significantly differs from conventional power generation.”
Their method is based on “Model Predictive Control,” wherein checkpoints across a power grid can exchange information and adjust accordingly. The researchers decentralized this model, so that a problem in one area could be solved to benefit the entire grid. The computer algorithm predicts the variables that influence the grid (demand, supply, etcetera) and applies those constraints for any problem that any part of the system might encounter.
A traditionally controlled grid could, for example, redirect otherwise unused energy from sleeping citizens to a power-hungry hospital or some other entity that continues to require energy even during typical off times. In a decentralized system, like the one modeled by Zhang and her colleagues, the system works the same way, but instead of having to clear the redirection with every checkpoint, the variables are assumed and the action is nearly immediate.
To test their algorithm, the researchers compared the volume output and dependability of a four-part system – four plants sharing responsibility for generating power in different areas – with and without the incorporation of wind power.
In the analysis of a conventional power plant, the researchers found that their model required much less computational time compared to the traditional Model Predictive Control. That’s a major advantage, as the computing process is expensive in both time and energy.
When the researchers added the hard-to-predict wind turbines as a source of power in the model, it still worked as well. According to the scientists, the major flaw is that computational needs will increase to maintain system stability, which cannot be guaranteed in their algorithm.
“Our future work is focused on [pursuing] the implementation of [our algorithm] with guaranteeing stability and feasibility while reducing the computation and communication requirements,” Zhang wrote.
Fulltext of the paper is available: http://ieeexplore.
Germany: 100 percent renewable energy sources require overcapacity
To switch electricity supply from nuclear to wind and solar power is not so simple.
Germany decided to go nuclear-free by 2022. A CO2-emission-free electricity supply system based on intermittent sources, such as wind and solar – or photovoltaic (PV) – power could replace nuclear power. However, these sources depend on the weather conditions. In a new study published in EPJ Plus, Fritz Wagner from the Max Planck Institute for Plasma Physics in Germany analysed weather conditions using 2010, 2012, 2013 and 2015 data derived from the electricity supply system itself, instead of relying on meteorological data. By scaling existing data up to a 100% supply from intermittent renewable energy sources, the author demonstrates that an average 325 GW wind and PV power are required to meet the 100% renewable energy target. This study shows the complexity of replacing the present primary energy supply with electricity from intermittent renewable sources, which would inevitably need to be supplemented by other forms of CO2-free energy production.
Intermittent sources are, by definition, unsteady. Therefore, a back-up system capable of providing power at a level of 89% of peak load would be needed. This requires creating an oversised power system to produce large amounts of surplus energy. A day storage to handle surplus is ineffective because of the day-night correlation of surplus power in the winter. A seasonal storage system loses its character when transformation losses are considered; indeed, it only contributes to the power supply after periods with excessive surplus production.
The option of an oversized, intermittent renewable-energy-sources system to feed the storage is also ineffective. This is because, in this case, energy can be taken directly from the large intermittent supply, making storage superfluous. In addition, the impact on land use and the transformation of landscape by an unprecedented density of wind convertors and transmission lines needs to be taken into consideration. He also warns of the risk that it will intensify social resistance.
F. Wagner (2017), Surplus from and storage of electricity generated by intermittent sources, Eur. Phys. J. Plus 131: 445, DOI 10.1140/epjp/i2016-16445-3