Mario Ragwitz

On the Success of Policy Strategies for the Promotion of Electricity from Renewable Energy Sources in the Eu

In recent years, a wide range of strategies has been implemented in different EU-countries to increase the share of electricity generation from renewable energy sources. This paper evaluates the success of different regulatory strategies. The most important conclusions of this analysis are: (i) regardless of which strategy is chosen, it is of overriding importance that there should be a clear focus on the exclusive promotion of newly installed plants; (ii) a well-designed (dynamic) feed-in tariff system ensures the fastest deployment of power plants using Renewable Energy Sources at the lowest cost to society; (iii) promotion strategies with low policy risks have lower profit requirements for investors and, hence, cause lower costs to electricity customers.

Promotion of renewable energy sources: effects on innovation

To meet existing and future targets for renewable energy sources, national governments, EU policymakers and electricity market stakeholders have a pronounced interest in designing optimal instruments for the promotion of Renewable Energy Sources in the Electricity sector (RES-E). This paper characterises the present status of the RES-E markets in Europe, the portfolio of promotional instruments currently applied across the EU and the progress the Member States have made in reaching the targets. In particular, existing support schemes are analysed in terms of their effectiveness in achieving additional RES-E generation and in terms of their ability to meet the targets at minimum costs (efficiency). Our empirical findings show that instruments which are effective also tend to be efficient. Further, the short- and long-term diffusion of specific RES technologies depends on the support schemes in place. Finally, the paper discusses the compatibility of different instruments to support RES-E in the context of more general energy policy objectives.

Market Integration of Renewable Electricity Generation — The German Market Premium Model:

Feed-in tariffs for renewable electricity have proven to be an effective and cost-efficient instrument because they provide long-term investment security; however, they do not incentivize grid and market integration. Feed-in premiums are a relatively novel instrument designed with the objective of keeping investment risks low while allowing for improved grid and market integration. This article analyses the German feed-in premium. The evaluation of the operation during the first year gives first indications that the market premium can contribute to the system and market integration of renewable energies, while still maintaining investment security. First impacts can be seen in the following fields: Diversity of market actors, forecast accuracy, improved remote control and participation in the reserve markets. In general, it can be concluded that the German market premium has been able to trigger significant developments. However, additional assessments of the instrument are necessary in order to see whether the observed changes are sustainable and lead to the expected developments.

Financing Instruments to Promote Energy Efficiency and Renewables in Times of Tight Public Budgets

In the past, many countries have financed schemes to promote energy efficiency and renewable heat generation mainly through public budgets; support schemes to renewable electricity already have a broader financing basis but have been criticised for providing too little incentives for market integration of renewables. This is why it is essential to overhaul the existing financing instruments by tapping new financing sources in addition to the state budgets and by making them more efficient. This objective is examined in four areas: Market-oriented financing schemes for energy efficiency options, financing options for the thermal renovation of the building stock, efficient schemes for renewable electricity generation and future promotion schemes for renewable energy sources for heat generation. The special issue shows that many financing options are either able to mobilise private capital or to supplement public capital in order to provide the additional investments needed for energy efficiency and renewables. The task which remains at the policy level is to establish an efficient framework based on a mixture of private and public funds which mitigates the risks for companies, is tailored to the technological needs and triggers synergetic policies addressing non-economic barriers.

Short Time Prediction of Wind Speeds from Local Measurements

Summary. We compare different schemes for the short time (few seconds) predic-tion of local wind speeds in terms of their performance. Special emphasis is laid onthe prediction of turbulent gusts, where data driven continuous state Markov chainsturn out to be quite successful. A test of their performance by ROC statistics isdiscussed in detail. Taking into account correlations of several measurement posi-tions in space enhances the predictability. As a striking result, stronger wind gustspossess a better predictability. 16.1 Wind Speed Predictions Whereas the three dimensional velocity field of the air in the atmospherecan be supposed to be described by the deterministic Navier–Stokes equa-tions, possibly augmented by equations for the temperature and humidity(and hence density of the air) and with suitable boundary conditions, a localmeasurementyieldsdatawhichappeartoberandom.Infact,deterministicbe-haviour of the local velocities is very unprobable, since (a) the Navier–Stokesequations contain already non-local interactions through the self-generatedpressure field, and (b) the local wind speed changes due to the drift of theglobal wind field across the measurement position.Data analysis of wind speed recordings yields results which are fully con-sistent with stochastic data. We use time series recorded in Lammefjord bythe Riso research centre [1]. These data are obtained from cup anemometersmounted on measurement masts at heights of 10, 20, and 30m above ground,taken with 8Hz sampling rate. The data sets report the absolute values of thewind speeds in the

PHASE SPACE RECONSTRUCTION AND NONLINEAR PREDICTIONS FOR STATIONARY AND NONSTATIONARY MARKOVIAN PROCESSES

We analyze prediction schemes for stochastic time series data. We propose that under certain conditions a scalar time series, obtained from a vector-valued Markov process, can be modeled as a finite memory Markov process in the observable. The transition rules of the process are easily computed using simple nonlinear time series predictors originally proposed for deterministic chaotic signals. The optimal time lag entering the embedding procedure is shown to be significantly smaller than in the deterministic case. The same concept can be extended to nonstationary stochastic processes, where an increase of the embedding dimension can help to identify instantaneous dynamical properties, and where redundant information in the past is exploited in an optimal way.

State Budget Independent, Market-Based Instruments to Finance Renewable Heat Strategies

At present, expanding the use of renewable energy sources for heating (RES-H) relies predominantly on publicly funded support instruments. As these are subject to subsidy cuts and suspensions, these instruments do not provide long-term security for investors and technology suppliers. Although feed-in tariffs and quota-based systems are the major support schemes for renewable energy sources in the electricity sector, similar policy designs have not been applied to RES-H. This paper presents and evaluates three different policy instruments which have the potential to finance RES-H without using public funds: A physical quota system for biomass, a technology-based quota system (Portfolio Model) and a remuneration-based system (Premium model). The assessment suggests that while the Portfolio Model and the Premium Model are both promising policies to enhance RES-H deployment, there is greater acceptance among stakeholders for the Premium Model.

Lessons Learned from Recent Promotion Strategies for Electricity from Renewables

To increase the share of renewable energy for electricity generation is a major target in many countries world-wide. Yet, to bring about a significant breakthrough a series of barriers has to be overcome and proper policy strategies have to be launched. In recent years, a wide range of such strategies has been implemented in different EU-countries. The major ones were investment subsidies, feed-in tariffs (FIT), tax incentives, quota-based tradable green certificates (TGC) and tendering systems. Which of the different instruments is most effective for increasing the dissemination of renewables still remains a controversial topic. The major objective of this paper is to evaluate the performance of various strategies in EU member states in recent years and to present the lessons learned.

Extreme events in surface wind: Predicting turbulent gusts

The potential to create extreme events is an inherent property of complex systems. Since our highly structured society is particularly sensitive to extreme events such as larger power failures in electric networks, stock market crashes, epedemics caused by new types of viruses, flash floods by summer storms, their potential predictability is of highest relevance. In this contribution we assume a physical point of view and concentrate on a specific phenomenon, namely on turbulent wind gusts. We show how a rather general model, namely a continuous state Markov chain, can be employed for data driven predictions of strong wind gusts. A Markov chain can represent arbitrary finite memory processes within the range of deterministic chaotic systems on the one extreme to uncorrelated white noise on the other, but its particular strenght lies in between: Nonlinear stochastic processes. Clearly, the modelling of the turbulent flow at a single site by a Markov chain is an approximation, whose accuracy will be discuss...

Nonlinear determinism in time series measurements of two- dimensional turbulence

Experiments on two-dimensional and three-dimensional turbulent flows in a rotating annulus are analyzed using linear and nonlinear time series predictors. The models are used to predict the time series, a time S ahead and to calculate the velocity incrementu S = u(sn + S) − u(sn) between the current value of the time series sn and a point time S apart. For two-dimensional flow, the nonlinear model provides superior predictions to the linear model foru S positive and large. In contrast, for three-dimensional turbulence the prediction of the nonlinear model is no better than the linear model. For two-dimensional turbulence, the probability density functions for the predictedu S from the linear model have an exponential tail, while for the nonlinear model the tail exhibits power law decay. The scaling exponent of this power law can be explained using arguments of the Kolmogorov 1941 theory. Our findings contradict the common assumption that two-dimensional turbulence shares the unpredictability properties of three-dimensional turbulent flows.