Browsing by Author "Hufendiek, Kai"

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Open Access
Asset profitability in the electricity sector : an iterative approach in a linear optimization model
(2022) Gillich, Annika; Hufendiek, Kai
In a competitive electricity market, generation capacities can exactly cover their full costs. However, the real market deviates from this ideal in some aspects. One is the concern of non-existent or insufficient scarcity prices. We present an iterative method in a linear optimization model to investigate the profitability of assets in the absence of scarcity prices and how the system changes when this risk is incorporated into investors’ expectations. Therefore, we use a two-step optimization of capacity planning and unit commitment. Iteratively, mark-ups at the height of uncovered costs are added to investment costs. This typically leads to a system with better investment profitability while keeping the system cost increase low. The methodology is applied to a simplified brownfield generation system, targeting CO2-free power generation within 25 years. In a model with annual foresight of actors, iterations result in a generation system with significantly lower (or even no) uncovered costs for new investments within ten or fewer iterations. Our example case with full foresight shows that early-added gas (combined cycle) and wind onshore capacities are able to recover their full costs over a lifetime, even without scarcity prices. However, the contribution margin gap remains high, especially for storage and biomass.
Open Access
Discussing the actual impact of optimizing cost and GHG emission minimal charging of electric vehicles in distributed energy systems
(2021) Schulz, Maximilian; Hufendiek, Kai
Electric vehicles represent a promising opportunity to achieve greenhouse gas (GHG) reduction targets in the transport sector. Integrating them comprehensively into the energy System requires smart control strategies for the charging processes. In this paper we concentrate on charging processes at the end users home. From the perspective of an end user, optimizing of charging electric vehicles might strive for different targets: cost minimization of power purchase for the individual household or - as proposed more often recently - minimization of GHG emissions. These targets are sometimes competing and cannot generally be achieved at the same time as the results show. In this paper, we present approaches of considering these targets by controlling charging processes at the end users home. We investigate the influence of differently designed optimizing charging strategies for this purpose, considering the electrical purchase cost as well as the GHG emissions and compare them with the conventional uncontrolled charging strategy using the example of a representative household of a single family. Therefore, we assumed a detailed trip profile of such a household equipped with a local generation and storage system at the same time. We implemented the mentioned strategies and compare the results concerning effects on annual GHG emissions and annual energy purchase costs of the household. Regarding GHG emissions we apply a recently proposed approach by other authors based on hourly emission factors. We discuss the effectivity of this approach and derive, that there is hardly no real impact on actual GHG emissions in the overall system. As incorporating this GHG target into the objective function increases cost, we appraise such theoretical GHG target therefore counterproductive. In conclusion, we would thus like to appeal for dynamic electricity prices for decentralised energy systems, leading at the same time to cost efficient charging of electric vehicles unfolding clear incentives for end users, which is GHG friendly at the end.
Open Access
Einsatz künstlicher neuronaler Netze bei der kurzfristigen Lastprognose
(1998) Hufendiek, Kai; Kaltschmitt, Martin
Um die erweiterten Möglichkeiten des Stromhandels, die sich durch die geplante Liberalisierung des Strommarktes ergeben, optimal nutzen zu können, muß die Planung zur Deckung der Stromnachfrage in Energieversorgungs- und anderen Unternehmen auf einer verläßlichen Lastprognose beruhen. Künstliche neuronale Netze, über deren Möglichkeiten bei der Lastprognose ein kurzer Überblick gegeben wird, weisen in diesem Zusammenhang, u. a. gegenüber der klassischen multiplen Regression, Vorteile auf. Anhand typischer Merkmale werden die Lastprognosesysteme mit künstlichen neuronalen Netzen, die teilweise bereits mit Erfolg eingesetzt werden, kurz charakterisiert. Darüber hinaus werden noch vorhandene Probleme im Umgang mit dieser Methode aufgezeigt, die vor allem darin bestehen, daß die Entwicklung solcher Systeme bisher weitgehend auf Versuch und Irrtum basiert. Daher wird abschließend eine entsprechende Entwicklungsmethodik vorgestellt und diskutiert, die zwar im Detail noch auszugestalten ist, auf die aber für eine breite wirtschaftliche Anwendung individuell angepaßter Systeme nicht verzichtet werden kann.
Open Access
Impact of long-term water inflow uncertainty on wholesale electricity prices in markets with high shares of renewable energies and storages
(2020) Scheben, Heike; Klempp, Nikolai; Hufendiek, Kai
Renewable energy shares in electricity markets are increasing and therefore also require an increase in flexibility options. Conventional electricity price modelling with optimisation models in thermally dominated markets is not appropriate in markets with high shares of renewable energies and storages because price structures are not adequately represented. Previous research has already identified the impact of uncertainty in renewable energy feed-in on investment and dispatch decisions. However, we are not aware of any work that investigates the influence of uncertainties on price structures by means of optimisation models. Appropriate modelling of electricity price structures is important for investment and policy decisions. We have investigated the influence of uncertainty concerning water inflow by applying a second stage stochastic dual dynamic programming approach in a linear optimisation model using Norway as an example. We found that the influence of uncertainty concerning water inflow combined with high shares of storages has a strong impact on the electricity price structures. The identified structures are highly influenced by seasonal water inflow, electricity demand, wind, and export profiles. Additionally, they are reinforced by seasonal primary energy source prices and import prices. Incorporating uncertainties in linear optimisation models improves the price modelling and provides, to a large extent, an explanation for the seasonal patterns of Norwegian electricity market prices. The paper explains the basic pricing mechanisms in markets with high shares of storages and renewable energies which are subject to uncertainty. To identify these fundamental mechanisms, we focused on uncertainty regarding water inflow, but the basic results hold true for uncertainties regarding other renewable energies as well.
Open Access
Impact of network charge design in an energy system with large penetration of renewables and high prosumer shares
(2021) Schick, Christoph; Klempp, Nikolai; Hufendiek, Kai
The transformation of our energy system toward zero net CO2 emissions correlates with a stronger use of low energy density renewable energy sources (RES), such as photovoltaic (PV) energy. As a source of flexibility, distributed PV systems, in particular, are oftentimes installed in combination with battery storage systems. These storage systems are dispatchable, i.e., controllable by the operating owners, who can thereby take over an active market role as energy prosumers. The particular battery operation modes are based on the individual prosumer decisions, which, in turn, are strongly affected by the regulatory framework in place. Regulatory frameworks differ from country to country, but almost all regulatory frameworks feature a network charge mechanism, which allocates network infrastructure and operating costs to the end customers. This raises the question of the extent to which different network charges lead to different prosumer decisions, i.e., battery operation modes, and thus different energy system configurations (system costs). In order to evaluate this question we apply (a) a fundamental linear optimization model of the energy wholesale market, which we stringently link to (b) an analysis of peak-coincident network capacity utilization as well as (c) an evaluation of the complete costs of energy for prosumers and consumers. This stringent cycle of analysis is applied to two prototypical network allocation schemes. We demonstrate that network allocation schemes that are orientated to peak-coincident network capacity utilization could both better incentivize a distribution network-oriented behaviour and better share financial burdens between prosuming and purely consuming households than would be the case for volumetric network charge designs. This paper further demonstrates that network-oriented battery operation does not, per se, result in optimal RES integration at the wholesale market level and CO2 emissions reduction. To identify effects from increasing sector integration, an analysis is both performed for a setting without and with consideration of widespread e-mobility. As a broader conclusion, our results demonstrate that future regulatory frameworks should have a stronger focus on prosumer integration by means, among other things, of an adequate network charge design reflecting the increasingly distributed nature of our future energy system.
Open Access
Das Kopernikus-Projekt ENavi - Die Transformation des Stromsystems mit Fokus Kohleausstieg
(2019) Fahl, Ulrich; Gaschnig, Hannes; Hofer, Claudia; Hufendiek, Kai; Maier, Beatrix; Pahle, Michael; Pietzcker, Robert; Quitzow, Rainer; Rauner, Sebastian; Sehn, Vera; Thier, Pablo; Wiesmeth, Michael; Hufendiek, Kai; Pahle, Michael
In diesem Bericht wird die Transformation des Stromsystems als zentrale Stellschraube zur Erreichung der Klimaziele analysiert. Dabei wird die Dekarbonisierung, insbesondere der Ausstieg aus der Kohleverstromung, in den Fokus gerückt. Anhand einer systematischen Vorgehensweise werden Transformationsszenarien für das deutsche Energiesystem identifiziert, analysiert und bewertet. Die Analyse erfolgt mithilfe unterschiedlicher computergestützter Modelle, um die Auswirkungen im gesamten System abschätzen zu können. Es werden sowohl Wechselwirkungen im Stromsystem und im Energiesystem, als auch im Wirtschaftssystem und im Bereich Ressourcen und Umwelt untersucht.
Open Access
Long-term distributional impacts of European cap-and-trade climate policies : a CGE multi-regional analysis
(2019) Cunha Montenegro, Roland; Lekavičius, Vidas; Brajković, Jurica; Fahl, Ulrich; Hufendiek, Kai
Carbon pricing is a policy with the potential to reduce CO2 emissions in the household sector and support the European Union in achieving its environmental targets by 2050. However, the policy faces acceptance problems from the majority of the public. In the framework of the project Role of technologies in an energy efficient economy-model-based analysis of policy measures and transformation pathways to a sustainable energy system (REEEM), financed by the European Commission under the Horizon 2020 program, we investigate the effects of such a policy in order to understand its challenges and opportunities. To that end, we use a recursive-dynamic multi-regional Computable General Equilibrium model to represent carbon pricing as a cap-and-trade system and calculate its impacts on consumption of energy goods, incidence of carbon prices, and gross income growth for different income groups. We compare one reference scenario and four scenario variations with distinct CO2 reduction targets inside and outside of the EU. The results demonstrate that higher emission reductions, compared to the reference scenario, lead to slower Gross Domestic Product growth, but also produce a more equitable increase of gross income and can help reduce income inequalities. In this case, considering that the revenues of carbon pricing are paid back to the households, the gross income of the poorest quintile grows as much as, or even more in some cases, than the gross income of the richest quintile.
Open Access
A more realistic heat pump control approach by application of an integrated two-part control
(2020) Schulz, Maximilian; Kemmler, Thomas; Kumm, Julia; Hufendiek, Kai; Thomas, Bernd
Heat pumps are a vital element for reaching the greenhouse gas (GHG) reduction targets in the heating sector, but their system integration requires smart control approaches. In this paper, we first offer a comprehensive literature review and definition of the term control for the described context. Additionally, we present a control approach, which consists of an optimal scheduling module coupled with a detailed energy system simulation module. The aim of this integrated two-part control approach is to improve the performance of an energy system equipped with a heat pump, while recognizing the technical boundaries of the energy system in full detail. By applying this control to a typical family household situation, we illustrate that this integrated approach results in a more realistic heat pump operation and thus a more realistic assessment of the control performance, while still achieving lower operational costs.
Open Access
Policy Brief: Folgen des Kohleausstiegs und der Energiewende für die Haushalte in Deutschland
(Stuttgart : Universität Stuttgart, Institut für Energiewirtschaft und Rationelle Energieanwendung, 2019) Fahl, Ulrich; Dobbins, Audrey; Hofer, Claudia; Hufendiek, Kai; Hufendiek, Kai
Der aktuell diskutierte „Kohleausstieg“ sowie das geplante Klimaschutzgesetz verursachen Kosten. Die Bepreisung von Kohlendioxyd (CO2) ist in diesem Zusammenhang als kosteneffizientes Instrument zu beurteilen und daher aus ökonomischer Sicht vorteilhaft. Durch die CO2-Bepreisung entstehen einerseits Kosten für den Systemumbau, andererseits werden staatliche Einnahmen generiert. Werden diese Mehreinnahmen jedoch nicht zur Entlastung der Verbraucher genutzt, so kommt es auf Haushaltsebene zu erheblichen Mehrbelastungen. Um diese Mehrbelastungen zu vermeiden, sind flankierende Ausgleichsmaßnahmen unbedingt notwendig.
Open Access
Quantification of the flexibility potential through smart charging of battery electric vehicles and the effects on the future electricity supply system in Germany
(2021) Guthoff, Felix; Klempp, Nikolai; Hufendiek, Kai