Nicolas Höning

Flexible consumers reserving electricity and offering profitable downward regulation

Previous work on demand response in smart grids considers dynamic real-time prices, but has so far neglected to consider how consumers can also be involved in planning ahead, both for scheduling of consumption and reserving their ability to regulate downward during balancing. This work models a flexible consumer in a novel two-settlement electricity auction. The consumer buys electricity on an ahead market and offers downward regulation on the balancing market. Bidding in two-settlement procedures is a hard problem and the use case of a flexible consumer is a novel problem setting. This poses a challenge for the design of smart ICT that automates bidding in smart grid operations. In a decision-theoretic model that takes the viewpoint of a flexible consumer, we implement a novel, unified format that simplifies computation of bids and can make the guarantee that offering downward regulation increases overall utility. Simulations show that the unified format, when compared to a benchmark format with two independent bids, attains the same utility under a wide range of market conditions despite its simplicity of use. Furthermore, it ensures that the consumers offer for downward regulation is indeed executed with the UNI format, which is often not the case with the benchmark format.

Reducing Electricity Consumption Peaks with Parametrised Dynamic Pricing Strategies Given Maximal Unit Prices

Demand response is a crucial mechanism for flattening of peak loads. For its implementation, we not only require consumers who react to price changes, but also intelligent strategies to select prices. We propose a parametrised meta-strategy for dynamic pricing and identify suitable strategies for given scenarios through offline optimisation using a population model. We also model an important and novel constraint: a price cap (a maximal unit price) for consumer protection. We show in computational simulations that the maximal unit price influences the peak reduction potential of dynamic pricing. We compare our dynamic pricing approach with a constant pricing approach and show that our approach, used by a profit-optimising seller, is both peak-reducing and equally profitable.

Fast and revenue-oriented protection of radial LV cables with smart battery operation

Low-voltage radial electricity cables will have more and more difficulties to carry the increasing load of novel consumption devices (e.g, electric vehicles) and the expected generated input of decentrally-generated power (e.g, from photovoltaic cells). One solution to avoid replacement is to install a battery at the end of a cable which is expected to be overloaded frequently. The intelligent operation of this battery needs to combine the protection of the cable with optimizing its revenue, in order to be economically viable. This paper formulates the offline optimization problem and proposes two robust heuristic online strategies. We show in computer simulations that these heuristics, which make fast just-in-time responses, reliably deliver good results. Our second heuristic, H2, reaches up to 83% of the approximated theoretical optimum.

Designing Comprehensible Self-Organising Systems

Self-organising systems are a popular engineering concept for designing decentralised autonomic computing systems. They are able to find solutions in complex and versatile problem domains, but as they capture more complexity in their own design, they are becoming less and less comprehensible to their users (be they humans or intelligent agents). We describe a design challenge that relates to usability theory in general and in particular resembles an observation made by Phoebe Senger, who noted that software agents tend to become incomprehensible in their behaviour as they grow more complex. In the manifestation of self-organising systems, the problem is more urgent (since we find ourselves using them more and more) and harder to solve at the same time (since these systems are not centrally controlled). We describe the problem domain and propose three system properties that could be used as quality indicators in this regard: Stability, Learn ability and Engage ability. We demonstrate their usage in a simple model of dynamic pricing markets (e.g. the electricity domain) and evaluate them in different ways.