This paper considers the scenario of a big new energy source connecting to an existing network of generators and loads. To be able to maintain such a network at the correct settings, the well known load flow equations have to be solved. Since existing software has trouble with solving the load flow equations in the scenario of a very large generator, new software was created using Matlab’s inherent fsolve function. This software was consequently used in combination with existing software of the MATPOWER package to calculate the optimal way of connecting a new large generator to an existing network. This was done for a relatively small case using a brute force method which iterated over all possible options. @en

Spreadsheets are popular end-user computing applications and one reason behind their popularity is that they offer a large degree of freedom to their users regarding the way they can structure their data. However, this flexibility also makes spreadsheets difficult to understand. Textual documentation can address this issue, yet for supporting automatic generation of textual documentation, an important pre-requisite is to extract metadata inside spreadsheets. It is a challenge though, to distinguish between data and metadata due to the lack of universally accepted structural patterns in spreadsheets. Two existing approaches for automatic extraction of spreadsheet metadata were not evaluated on large datasets consisting of user inputs. Hence in this paper, we describe the collection of a large number of user responses regarding identification of spreadsheet metadata from participants of a MOOC. We describe the use of this large dataset to understand how users identify metadata in spreadsheets, and to evaluate two existing approaches of automatic metadata extraction from spreadsheets. The results provide us with directions to follow in order to improve metadata extraction approaches, obtained from insights about user perception of metadata. We also understand what type of spreadsheet patterns the existing approaches perform well and on what type poorly, and thus which problem areas to focus on in order to improve.@en