Pattern-based Automatic Translation of Structured Power System Data to Functional Models for Decision Support Applications

Improved information and insight for decision support in operations and design are central promises of a smart grid. Well-structured information about the composition of power systems is increasingly becoming available in the domain, e.g. due to standard information models (e.g. CIM or IEC61850) or otherwise structured databases. More measurements and data do not automatically improve decisions, but there is an opportunity to capitalize on this information for decision support. With suitable reasoning strategies data can be contextualized and decision-relevant events can be promoted and identified. This paper presents an approach to link available structured power system data directly to a functional representation suitable for diagnostic reasoning. The translation method is applied to test cases also illustrating decision support

Explanations of comparative facts: A shift in focus.

A comparative fact can be presented in two ways. ‘Among white evangelical Christians, Obama had 40% fewer votes than McCain.’ or ‘Among white evangelical Christians, McCain had 40% more votes than Obama.’ Focusing on why Obama had fewer votes than McCain may result in a different explanation from focusing on why McCain had more votes than Obama, although it is the same fact. Thus what determines whether we focus in our explanation on Obama or McCain? In two studies, we show that people generally focused more on the first part of the comparative fact. However, when the comparative fact is presented in a negative frame (‘less … than’) there was a shift in focus from the first to the second part of the fact. For neutral items this moderating effect did not occur. The Principle of Lexical Marking (Clark, 1969) and Loss Aversion (Kahneman & Tversky, 1979) are discussed as possible accounts for this shift in focus

Now I like it, now I don’t: Delay effects and retrospective judgment.

The present paper tests the widely accepted hypothesis that on-line judgment implies functional independence between memory for, and judgment of, verbal stimuli (e.g., Anderson, 1989; Hastie & Park, 1986). In the present study, participants recalled lists of words, after having assessed each for its pleasantness. Presentation position of a negative item within the lists was manipulated. Also, items memorability was manipulated after their presentation – by inserting a filled delay between presentation and the judgment task; in this way, on-line judgment formation was spared. The memory manipulation reduced recall rates for negative items presented in the last position – and their negative influence on pleasantness ratings accordingly. These results contradict the predictions of pure on-line approaches to judgment formation (e.g., Betsch, Plessner, Schwieren, & Gütig, 2001) and suggest that even in on-line judgment tasks, memory plays a role

Preference Stability and Memory: Two Unlikely Companions

Do people have stable risk preferences? This important question has engaged normativ

Raising argument strength using negative evidence: A constraint on models of induction

Both intuitively, and according to similarity-based theories of induction, relevant evidence raises argument strength when it is positive and lowers it when it is negative. In three experiments, we tested the hypothesis that argument strength can actually increase when negative evidence is introduced. Two kinds of argument were compared through forced choice or sequential evaluation: single positive arguments (e.g., “Shostakovich’s music causes alpha waves in the brain; therefore, Bach’s music causes alpha waves in the brain”) and double mixed arguments (e.g., “Shostakovich’s music causes alpha waves in the brain, X’s music DOES NOT; therefore, Bach’s music causes alpha waves in the brain”). Negative evidence in the second premise lowered credence when it applied to an item X from the same subcategory (e.g., Haydn) and raised it when it applied to a different subcategory (e.g., AC/DC). The results constitute a new constraint on models of induction

ERIGrid Holistic Test Description for Validating Cyber-Physical Energy Systems

Smart energy solutions aim to modify and optimise the operation of existing energy infrastructure. Such cyber-physical technology must be mature before deployment to the actual infrastructure, and competitive solutions will have to be compliant to standards still under development. Achieving this technology readiness and harmonisation requires reproducible experiments and appropriately realistic testing environments. Such testbeds for multi-domain cyber-physical experiments are complex in and of themselves. This work addresses a method for the scoping and design of experiments where both testbed and solution each require detailed expertise. This empirical work first revisited present test description approaches, developed a newdescription method for cyber-physical energy systems testing, and matured it by means of user involvement. The new Holistic Test Description (HTD) method facilitates the conception, deconstruction and reproduction of complex experimental designs in the domains of cyber-physical energy systems. This work develops the background and motivation, offers a guideline and examples to the proposed approach, and summarises experience from three years of its application.This work received funding in the European Community’s Horizon 2020 Program (H2020/2014–2020) under project “ERIGrid” (Grant Agreement No. 654113)