Intelligent Microgrids

Center for Electromechanic

Smart dual thermal network

Conventional district heating (DH) systems enable demand aggregation at district level and can provide high centralized heat generation performance values. However, thermal Renewable Energy Sources (RES) deployment at building level still remains low, and exploitation suboptimal, as it is limited by the instantaneous thermal load and storage capacity availability of each building. Buildings play the role of consumers that request a variable amount of heat over time and the thermal network the role of unidirectional heat supplier, without any smart interaction. The FP7 project A2PBEER has developed an innovative Smart Dual Thermal Network concept based on RES and Combined Heat and Power (CHP) as generation technologies, that enables transforming existing suboptimal DH systems, into integrated thermal networks with optimized performance and building level RES system production exploitation. It is based on an innovative Smart Dual Building Thermal Substation concept, which allows a bidirectional heat exchange of the buildings with the thermal network, and to aggregate district level distributed production and storage capacity (Virtual District Plant). With this approach buildings become prosumers maximizing decentralized RES production exploitation, as any possible local heat production surplus on any building of the district, will be delivered to the network to be used by other buildings. Additionally, this thermal network allows the delivery of the energy necessary to meet the heating and cooling demand of the buildings through a single hot water distribution network. In this way, it is possible to upgrade conventional DH systems to district heating and cooling systems, without the construction of a district cooling plant and a dedicated cooling distribution network. Cooling is produced at building level through sorption technologies using locally deployed solar collectors and the thermal network as energy sources. Finally, the district typologies and climatic conditions that maximize the potential of this thermal network concept have been identified.The research activities leading to the described developments and results, were funded by the FP7 project A2PBEER, under grant agreement No 906090. Special thanks to Olof Hallström and ClimateWell AB for making the TRNSYS model of the innovative sorption system and developing the component level simulation work

Zooplankton variability at four monitoring sites of the Northeast Atlantic shelves differing in latitude and trophic status

Zooplankton abundance series (1999–2013) from the coastal sites of Bilbao 35 (B35), Urdaibai 35 (U35), Plymouth L4 (L4) and Stonehaven (SH), in the Northeast Atlantic were compared to assess differences in the magnitude of seasonal, interannual and residual scales of variability, and in patterns of seasonal and interannual variation in relation to latitudinal location and trophic status. Results showed highest seasonal variability at SH consistent with its northernmost location, highest interannual variability at U35 associated to an atypical event identified in 2012 in the Bay of Biscay, and highest residual variability at U35 and B35 likely related to lower sampling frequency and higher natural and anthropogenic stress. Interannual zooplankton variations were not coherent across sites, suggesting the dominance of local influences over large scale environmental drivers. For most taxa the seasonal pattern showed coherent differences across sites, the northward delay of the annual peak being the most common feature. The between-site seasonal differences in spring–summer zooplankton taxa were related mainly to phytoplankton biomass, in turn, related to differences in latitude or anthropogenic nutrient enrichment. The northward delay in water cooling likely accounted for between-site seasonal differences in taxa that increase in the second half of the year

Knowledge-based gene expression classification via matrix factorization

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks. Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients.Siemens AG, MunichDFG (Graduate College 638)DAAD (PPP Luso - Alem˜a and PPP Hispano - Alemanas

An Efficient Switch Model for Simulating Large Power Systems with Many Power Converters

Frequent matrix factorizations due to power electronic switch commutations are computationally expensive. This paper addresses this burden by treating power electronic switches as dependant sources instead of time-varying resistors. The resulting network matrix is constant, and does not require re-factorization when switches commutate. Three power electronic switches are presented and discussed for both nodal and mesh equation formulations. A case study at the end shows that the run-time for a power system with >200 switches when using the switching approach presented herein can reduce from 8 hours to under 15 minutes, which is a speedup of 40x.Center for Electromechanic