Andreas Kamper

Distribution of Evolutionary Algorithms in Heterogeneous Networks

While evolutionary algorithms (EAs) have many advantages, they have to evaluate a relatively large number of candidate solutions before producing good results, which directly translates into a substantial demand for computing power. This disadvantage is somewhat compensated by the ease of parallelizing EAs. While only few people have access to a dedicated parallel computer, recently, it also became possible to distribute an algorithm over any bunch of networked computers, using a paradigm called “grid computing”. However, unlike dedicated parallel computers with a number of identical processors, the computers forming a grid are usually quite heterogeneous. In this paper, we look at the effect of this heterogeneity, and show that standard parallel variants of evolutionary algorithms are significantly less efficient when run on a heterogeneous rather than on a homogeneous set of computers. Based on that observation, we propose and compare a number of new migration schemes specifically for heterogeneous computer clusters. The best found migration schemes for heterogeneous computer clusters are shown to be at least competitive with the usual migration scheme on homogeneous clusters. Furthermore, one of the proposed migration schemes also significantly improves performance on homogeneous clusters.

Scheduling of electrical household appliances with price signals

Due to the increasing competition in liberalized electricity markets, a succesful customer retention as well as a cost efficient allocation of electric energy become more and more important. Therefore, new, innovative strategies are sought, which promise on the one hand a long-term customer retention and assure, on the other hand, a more cost-efficient provision of electric energy.

Strategies for Decentralised Balancing Power

There are many different approaches to central load management in power supply systems, such as direct load control or price signals to control production and consumption. Despite these measures there will always be an imbalance between production and consumption, i.e. due to fluctuating resource availabilities and unforeseen changes in consumption. As CO 2 emissions and sustainable electricity production have entered the focus of attention in politics and industries, ecologically advantageous concepts avoiding inefficiencies in power supply are strongly promoted. In this article, a self-organising approach to small devices such as freezers or washing machines as well as Combined Heat and Power plants (CHP) is presented, which aims at avoiding imbalances in the power network. While each device has its own constraints and specific task (e.g. provide heat or wash clothes), most of them have a limited degree of freedom in their schedules. A P2P approach with an Evolutionary Algorithm in combination with a local search is used to identify suitable partners to cover their production or consumption and thus to adjust the load in a way to minimise network imbalances.

Future power markets

In this article we discuss the impact of the increasingly higher dynamics and transparency on future electricity markets due to a higher degree of automation along the energy supply chain. As part of the SESAM (Self Organization and Spontaneity in Liberalized and Harmonized Markets) project, we analyze the consequences of the customers’ higher willingness to change their supplier. In addition, we evaluate the major changes in load profiles caused by the use of load management systems in combination with dynamic retail electricity prices. We demonstrate that not only the consumer load but also the application of decentralized combined heat and power plants can be rescheduled. Finally, we outline further research activities.

Adaptives verteiltes Lastmanagement in Bilanzkreisen

ZusammenfassungIm Energiesystem ist der Ausgleich von Ungleichgewichten zwischen Erzeugung und Verbrauch eine wesentliche Aufgabe. Diese sogenannte Regelenergie wird hauptsächlich von Großkraftwerken bereitgestellt, welche ihre Leistung entsprechend anpassen. Zusätzlich zu den Großkraftwerken werden auch mittlere Kraftwerke oder größere schaltbare Lasten eingesetzt. In diesem Artikel wird ein selbstorganisierendes Konzept vorgestellt, mit dem kleinere Verbraucher wie Waschmaschinen, Gefrierschränke oder private Kraft-Wärme-Kopplungsanlagen ebenfalls in das System integriert werden können. Im Gegensatz zu den Großkraftwerken steht die Leistung dieser Geräte aber nicht ausschließlich für die Bereitstellung von Regelenergie zur Verfügung, da vorrangig die Anforderungen der Eigentümer hinsichtlich ihrer primären Funktion erfüllt werden müssen. Nur die zusätzlich verfügbaren Freiheitsgrade können genutzt werden. Eine hierarchische Observer/Controller-Architektur erlaubt es, die Geräte über ein P2P-Netzwerk zu einem Gerätepool zusammenzuschließen. Dadurch können alle Geräte untereinander kommunizieren, um alle Anforderungen der Eigentümer zu erfüllen und zusätzlich weitere Dienste für das Energiesystem bereitzustellen. Dies ermöglicht eine kurzfristige Reaktion der Geräte sowie das lokale Aushandeln von neuen Energiefahrplänen, die den Bedarf an Regelenergie deutlich reduzieren können.

Pricing Energy in a Multi-Utility Market

We present a solution to the problem of tariff design for an energy supplier (utility). The tariffs for electricity and — optionally — heat created with our pricing model are optimal in terms of the utility’s profit and take into account the consumers’ predicted behavior, their load curve, the utility’s generation prices, and prices for trading electricity on a day-ahead market like the European Energy Exchange (EEX). Furthermore, we analyze the repercussions of different assumptions about consumer behavior on a simulated market with four competing utilities.