Network-constrained models of liberalized electricity markets: the devil is in the details

Numerical models for electricity markets are frequently used to inform and support decisions. How robust are the results? Three research groups used the same, realistic data set for generators, demand and transmission network as input for their numerical models. The results coincide when predicting competitive market results. In the strategic case in which large generators can exercise market power, the predicted prices differed significantly. The results are highly sensitive to assumptions about market design, timing of the market and assumptions about constraints on the rationality of generators. Given the same assumptions the results coincide. We provide a checklist for users to understand the implications of different modelling assumptions

Network-constrained models of liberalized electricity markets: the devil is in the details

Numerical models for electricity markets are frequently used to inform and support decisions. How robust are the results? Three research groups used the same, realistic data set for generators, demand and transmission network as input for their numerical models. The results coincide when predicting competitive market results. In the strategic case in which large generators can exercise market power, the predicted prices differed significantly. The results are highly sensitive to assumptions about market design, timing of the market and assumptions about constraints on the rationality of generators. Given the same assumptions the results coincide. We provide a checklist for users to understand the implications of different modelling assumptions.Market power, Electricity, Networks, Numeric models, Model comparison

Distribution power markets: detailed modeling and tractable algorithms

The increasing integration of renewable generation presents power systems with economic and reliability challenges, mostly due to renewables' volatility, which cannot be effectively addressed with business-as-usual practices. Fortunately, this is concurrent with rising levels of Distributed Energy Resources (DERs), including photovoltaics, microgeneration and flexible loads like HVAC loads and electric vehicles. DERs are capable of attractive time-shiftable behavior and of transacting reactive power and reserves in addition to real power. If DER capacity is optimally allocated among these three products, distribution network and economic benefits can be realized and renewable-related challenges can be mitigated, enabling increased renewable integration safety limits. In order to achieve optimal DER scheduling, this thesis proposes the formulation of a spatiotemporal marginal-cost based distribution power market and develops and implements tractable clearing algorithms. First, we formulate a centralized market clearing algorithm whose result is the optimal DER real power, reactive power and reserves schedules and the optimal nodal marginal costs. Our market formulation develops for the first time detailed and realistic models of the salient distribution network variable costs (transformer degradation, voltage sensitive loads) together with distribution network constraints (voltage bound constraints, that reflect distribution network congestion and AC load flow), and intertemporal DER dynamics and capabilities. However, the centralized algorithm does not scale, motivating the use of distributed algorithms. We propose two distributed algorithms: • A fully distributed algorithm that relies on massively parallel DER and distribution line specific sub-problem solutions, iteratively coordinated by nodal price estimates which promote and eventually enforce nodal balances. Upon convergence, nodal balances hold and optimal marginal costs are discovered. We further existing practices by using local penalty updates and stopping criteria that significantly reduce communication requirements. • A novel, partially distributed formulation in which DERs self-schedule in parallel based on centrally calculated price estimates, resulting from a load flow calculation. Nodal balances hold during all iterations. Finally, we are, to the best of our knowledge, the first to study voltage-constrained distribution market instances cleared with distributed methods. We decrease the deviation of marginal costs from their optimal values using first order optimality conditions and use voltage barrier functions for speedier convergence.2020-03-31T00:00:00

A framework for exchange-based trading of cloud computing commodities

Cloud computing is a paradigm for using IT services with characteristics such as flexible and scalable service usage, on-demand availability, and pay-as-you-go billing. Respective services are called cloud services and their nature usually motivates a differentiation in three layers: Infrastructure as a Service (IaaS) for cloud services offering functionality of hardware resources in a virtualised way, Platform as a Service (PaaS) for services acting as execution platforms, and Software as a Service (SaaS) representing applications provided in a cloud computing way. Any of these services is offered with the illusion of unlimited scalability. The infinity gained by this illusion implies the need for some kind of regulation mechanism to manage sup- ply and demand. Today’s static pricing mechanisms are limited in their capabilities to adapt to dynamic characteristics of cloud environments such as changing workloads. The solution is a dy- namic pricing approch compareable to today’s exchanges. This requires comparability of cloud services and the need of standardised access to avoid vendor lock-in. To achieve comparability, a classification for cloud services is introcuced, where classes of cloud services representing tradable goods are expressed by the minimum requirements for a certain class. The main result of this work is a framework for exchange-based trading of cloud com- puting commodities, which is composed of four core components derived from existing ex- change market places. An exchange component takes care of accepting orders from buyers and sellers and determines the price for the goods. A clearing component is responsible for the fi- nancial closing of a trade. The settlement component takes care of the delivery of the cloud service. A rating component monitors cloud services and logs service level agreement breaches to calculate provider ratings, especially for reliability, which is an important factor in cloud computing. The framework establishes a new basis for using cloud services and more advanced business models. Additionally, an overview of selected economic aspects including ideas for derivative financial instruments like futures, options, insurances, and more complex ones is pro- vided. A first version of the framework is currently being implemented and in use at Deutsche Bo ̈rse Cloud Exchange AG.Cloud Computing repra ̈sentiert eine neue Art von IT-Diensten mit bestimmten Eigenschaften wie Flexibilita ̈t, Skalierbarkeit, sta ̈ndige Verfu ̈gbarkeit und nutzungsbezogene (pay-as-you-go) Abrechnung. IT-Dienste, die diese Eigenschaften besitzen, werden als Cloud Dienste bezeichnet und lassen sich in drei Ebenen einteilen: Infrastructure as a Service (IaaS), womit virtuelle Hardware Ressourcen zur Verfu ̈gung gestellt werden, Platform as a Service (PaaS), das eine Ausfu ̈hrungsumgebung darstellt und Software as a Service (SaaS), welches das Anbieten von Applikationen als Cloud Dienst bezeichnet. Cloud Dienste werden mit der Illusion unendlicher Skalierbarkeit angeboten. Diese Unendlichkeit erfordert einen Mechanismus, der in der Lage ist, Angebot und Nachfrage zu regulieren. Derzeit eingesetzte Preisbildungsmechanismen sind in ihren Mo ̈glichkeiten beschra ̈nkt sich auf die Dynamik in Cloud Umgebungen, wie schnell wechselnde Bedarfe an Ressourcen, einzustellen. Eine mo ̈gliche Lo ̈sung stellt ein dynamischer Preisbildungsmechanismus dar, der auf dem Modell heutiger Bo ̈rsen beruht. Dieser erfordert die Standardisierung und Vergleichbarkeit von Cloud Diensten und eine standardisierte Art des Zugriffs. Um die Vergleichbarkeit von Cloud Diensten zu erreichen, werden diese in Klassen eingeteilt, die jeweils ein am Bo ̈rsenplatz handelbares Gut darstellen. Das Ergebnis dieser Arbeit ist ein Rahmenwerk zum bo ̈rsenbasierten Handel von Cloud Computing Commodities, welches aus vier Kernkomponenten besteht, die von existieren- den Bo ̈rsen und Rohstoffhandeslpla ̈tzen abgeleitet werden ko ̈nnen. Die Bo ̈rsenkomponente nimmt Kauf- und Verkaufsorders entgegen und bestimmt die aktuellen Preise der handelbaren Cloud Rohstoffe. Die Clearing Komponente stellt die finanzielle Abwicklung eines Gescha ̈ftes sicher, das Settlement ist fu ̈r die tatsa ̈chliche Lieferung zusta ̈ndig und die Rating Komponente u ̈berwacht die Cloud Dienste im Hinblick auf die Nichteinhaltung von Service Level Agree- ments und vor allem deren Zuverla ̈ssigkeit, die einen wichtigen Faktor im Cloud Computing darstellt. Das Rahmenwerk begru ̈ndet eine neue Basis fu ̈r die Cloudnutzung und ermo ̈glicht fort- geschrittenere Gescha ̈ftsmodelle. In der Arbeit wird weiters ein U ̈berblick u ̈ber o ̈konomis- che Aspekte wie Ideen zu derivaten Finanzinstrumenten auf Cloud Computing Commodities gegeben. Dieses Rahmenwerk wird derzeit an der Deutsche Bo ̈rse Cloud Exchange AG imple- mentiert und bereits in einer ersten Version eingesetzt