Worldwide the installed capacity of renewable technologies for electricity production is
rising tremendously. The German market is particularly progressive and its regulatory
rules imply that production from renewables is decoupled from market prices and electricity
demand. Conventional generation technologies are to cover the residual demand
(defined as total demand minus production from renewables) but set the price at the
exchange. Existing electricity price models do not account for the new risks introduced
by the volatile production of renewables and their effects on the conventional demand
curve. A model for residual demand is proposed, which is used as an extension of
supply/demand electricity price models to account for renewable infeed in the market.
Infeed from wind and solar (photovoltaics) is modeled explicitly and withdrawn from
total demand. The methodology separates the impact of weather and capacity. Efficiency
is transformed on the real line using the logit-transformation and modeled as a stochastic process. Installed capacity is assumed a deterministic function of time. In a case study the residual demand model is applied to the German day-ahead market
using a supply/demand model with a deterministic supply-side representation. Price trajectories are simulated and the results are compared to market future and option
prices. The trajectories show typical features seen in market prices in recent years and the model is able to closely reproduce the structure and magnitude of market prices.
Using the simulated prices it is found that renewable infeed increases the volatility of forward prices in times of low demand, but can reduce volatility in peak hours. Prices
for different scenarios of installed wind and solar capacity are compared and the meritorder effect of increased wind and solar capacity is calculated. It is found that wind
has a stronger overall effect than solar, but both are even in peak hours.
CRISPR/Cas has become the state-of-the-art technology for genetic manipulation in diverse
organisms, enabling targeted genetic changes to be performed with unprecedented efficiency. Here we report on the first establishment of robust CRISPR/Cas editing in the important necrotrophic plant pathogen Botrytis cinerea based on the introduction of optimized
Cas9-sgRNA ribonucleoprotein complexes (RNPs) into protoplasts. Editing yields were further improved by development of a novel strategy that combines RNP delivery with cotransformation of transiently stable vectors containing telomeres, which allowed temporary
selection and convenient screening for marker-free editing events. We demonstrate that
this approach provides superior editing rates compared to existing CRISPR/Cas-based
methods in filamentous fungi, including the model plant pathogen Magnaporthe oryzae.
Genome sequencing of edited strains revealed very few additional mutations and no evidence for RNP-mediated off-targeting. The high performance of telomere vector-mediated
editing was demonstrated by random mutagenesis of codon 272 of the sdhB gene, a major
determinant of resistance to succinate dehydrogenase inhibitor (SDHI) fungicides by in bulk
replacement of the codon 272 with codons encoding all 20 amino acids. All exchanges were
found at similar frequencies in the absence of selection but SDHI selection allowed the identification of novel amino acid substitutions which conferred differential resistance levels
towards different SDHI fungicides. The increased efficiency and easy handling of RNPbased cotransformation is expected to accelerate molecular research in B. cinerea and
other fungi.