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Energy Forecasting. Focus: Natural gas
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This work explores the possibilities of forecasting German gas imports and German gas consumption in detail by:
• Identifying proper terminology, with initial thoughts on the status quo of forecasting, using analogies with music (section 3.1),
• Understanding forecasting models based on statistics and machine learning (section 3.2),
• Applying domain knowledge while constructing data sets (data acquisition) - various models have been tested on low resolution data sets (monthly and yearly data). In classical forecasting, forecasts are conducted at company level (e.g. electricity load forecasting) for a short-term period fulfilling the requirement of profit maximization.
In contrast, this work’s forecasts spatially cover 1) all import nodes into Germany, 2) gas consumption in Germany with the focus on energy security.
• Examining various notions of complexity in relation to forecasting
Novelty in methodology
• Considering infrastructure as the upper limit for the forecasting model (section 4.1)
• Testing models for ex post forecasting of gas imports into Germany (section 4.2)
• Testing models for ex post forecasting of gas consumption in Germany (section 4.3). Producing an ex ante forecast by answering “what will be the future gas consumption in Germany in next ten years”
would cause the forecasting error to increase dramatically due to the
uncertainty of future input values, such as population (lower risk)
or, weather (higher uncertainty), which would lead to prediction
intervals being too wide to make any statement about the future
imports or consumption.
• Applying complexity measures such as approximate entropy ApEn
and sample entropy to two self-constructed real-world data sets on
gas imports to Germany and gas consumption in Germany (section
3.3)Diese Arbeit untersucht die Möglichkeiten zur Prognose von
Deutschen Gasimporten sowie des Gasverbrauchs in Deutschland im Detail, wie folgt:
• Identifikation klarer Terminologie, mit ersten Gedanken zum Status Quo der Prognosetechnik (Abschnitt 3.1)
• Erweiterung des Verständnisses von Prognosemodellen, die aus den Themenbereichen der Statistik und des maschinellen Lernens stammen (Abschnitt 3.2)
• Anwendung von Fachwissen bei der Konstruktion von Datensätzen (Data acquisition) - verschiedene Modelle wurden auf niedrig aufgelösten Daten getestet. Bei der klassischen Vorgehensweise werden Prognosen auf Unternehmensebene (z.B. Stromlastprognose) für einen kurzfristigen Zeitraum durchgeführt, der die Anforderung der Gewinnmaximierung erfüllt. Im Gegensatz dazu umfassen in
diesem Werk präsentierte Prognosen räumlich 1) alle Importknotenpunkte nach Deutschland und 2) den Gasverbrauch in Deutschland mit dem Fokus auf die Energiesicherheit.
• Untersuchung verschiedener Begriffe von Komplexität in Bezug auf Prognosen
Neuerungen in der Methodik
• Betrachtung der Infrastrukturkapazität als Obergrenze für das Prognosemodell (Abschnitt 4.1)
• Testen von Modellen für die Ex-post-Prognose von Gasimporten nach Deutschland (Abschnitt 4.2)
• Testen von Modellen für die Ex-post-Prognose des Gasverbrauchs in Deutschland (Abschnitt 4.3). Erstellung von Ex-Ante-Prognosen durch Beantwortung der Frage: "Wie hoch wird der zukünftige Gasverbrauch in Deutschland in den nächsten zehn Jahren sein?" würde dazu führen, dass der Prognosefehler aufgrund der Unsicherheit der zukünftigen Werte von Inputs wie Bevölkerung (geringeres Risiko) oder Wetter (höhere Unsicherheit) dramatisch ansteigt. Dadurch
würden die Vorhersageintervalle zu groß, um eine zutreffende
Aussage über die zukünftigen Importe oder den Verbrauch
zu treffen.
• Die Anwendung von Komplexitätsmaßen wie der ungefähren Entropie (ApEn) und der Probenentropie auf zwei selbst konstruierte Realwelt-Datensätze zu Gasimporten nach Deutschland und Gasverbrauch in Deutschland (Abschnitt 3.3
Irritations and Reactions: Art and Urban Planning
Get PDFKunst und Planung werden als soziale Systeme betrachtet, um deren Interaktionen beschreibbar zu machen. Am Fallbeispiel der PlanBude Hamburg werden der Modus Operandi Kunst und der Modus Operandi Planung untersucht, Parameter für transversale Prozesse abgeleitet sowie die Gestaltung tri- und multispährischer Prozesse in der Stadtentwicklung aufgezeigt
Automatic content‐based georeferencing of historical topographic maps
Get PDFOld maps are more than a cultural artefact: they are data. Data about the past still hold value for science and decision-making today. Libraries and archives have come a long way in digitising their inventories of thousands, sometimes millions, of historical maps using high-resolution scanning. Unfortunately, even with digital images the rich spatial and semantic information is inaccessible for people without a strong background in history and cartography. Only with georeferencing can historical maps be used in GIS and thus processed and compared with modern geospatial data. We introduce content-based image retrieval to automatically localise and georeference map images from topographic map series. We align the maps by extracting a subset of their symbols and cross-referencing them with online reference data from OpenStreetMap. We demonstrate our method with the Karte des Deutschen Reiches at 1: 100,000 scale, obtaining 96% correct location predictions and a median georeferencing error of 101 m
Five dimensions of climate governance: a framework for empirical research based on polycentric and multi‐level governance perspectives
Get PDFGovernance of climate mitigation and adaptation has been discussed within polycentric and multi-level governance perspectives. Both perspectives on climate governance are intimately related but yet in some regards are distinctly different - as one perspective has evolved from empirical research within the United States and the other in the European Union. Within an increasingly global discourse on climate governance, there is a need in the literature to bring both discourses together. The findings are based on a systematic literature review of 42 climate governance papers published since 2000. This paper discusses how multi-level and polycentric climate governance perspectives converge and diverge along five dimensions. The five dimensions provide insights for applying a multi-level or polycentric governance perspective to empirical research
Deep Learning based Detection, Segmentation and Counting of Benthic Megafauna in Unconstrained Underwater Environments
Get PDFAssessing and monitoring benthic communities is increasingly important in view of global alteration of marine environments. Deep learning has proven to effectively detect marine specimen in underwater imagery but still face problems with small input datasets, unconstrained environments and class imbalance. This study evaluates a data augmentation strategy to alleviate these limitations. Through synthetically derived image compositions, the entire input dataset was greatly extended from 700 to 12700 images. Additionally, specimen numbers of brittle stars, soft corals and glass sponges are equalized resulting in a mean average precision increase of 24 %. The overall mean average precision for box detections yields 76.7 and for instance segmentation 67.7 at an intersection over union threshold of 0.5. This study shows that deep architectures such as the deployed CenterMask via ResNeXt-101 model can successfully be trained with few original images from varying underwater scenes
RECOG RL01: correcting GRACE total water storage estimates for global lakes/reservoirs and earthquakes
Get PDFObservations of changes in terrestrial water storage (TWS) obtained from the satellite mission GRACE (Gravity Recovery and Climate Experiment) have frequently been used for water cycle studies and for the improvement of hydrological models by means of calibration and data assimilation. However, due to a low spatial resolution of the gravity field models, spatially localized water storage changes, such as those occurring in lakes and reservoirs, cannot properly be represented in the GRACE estimates. As surface storage changes can represent a large part of total water storage, this leads to leakage effects and results in surface water signals becoming erroneously assimilated into other water storage compartments of neighbouring model grid cells. As a consequence, a simple mass balance at grid/regional scale is not sufficient to deconvolve the impact of surface water on TWS. Furthermore, non-hydrology-related phenomena contained in the GRACE time series, such as the mass redistribution caused by major earthquakes, hamper the use of GRACE for hydrological studies in affected regions.
In this paper, we present the first release (RL01) of the global correction product RECOG (REgional COrrections for GRACE), which accounts for both the surface water (lakes and reservoirs, RECOG-LR) and earthquake effects (RECOG-EQ). RECOG-LR is computed from forward-modelling surface water volume estimates derived from satellite altimetry and (optical) remote sensing and allows both a removal of these signals from GRACE and a relocation of the mass change to its origin within the outline of the lakes/reservoirs. The earthquake correction, RECOG-EQ, includes both the co-seismic and post-seismic signals of two major earthquakes with magnitudes above Mw9.
We discuss that applying the correction dataset (1) reduces the GRACE signal variability by up to 75 % around major lakes and explains a large part of GRACE seasonal variations and trends, (2) avoids the introduction of spurious trends caused by leakage signals of nearby lakes when calibrating/assimilating hydrological models with GRACE, and (3) enables a clearer detection of hydrological droughts in areas affected by earthquakes. A first validation of the corrected GRACE time series using GPS-derived vertical station displacements shows a consistent improvement of the fit between GRACE and GNSS after applying the correction. Data are made available on an open-access basis via the Pangaea database (RECOG-LR: Deggim et al., 2020a, https://doi.org/10.1594/PANGAEA.921851; RECOG-EQ: Gerdener et al., 2020b, https://doi.org/10.1594/PANGAEA.921923)
Virtual Reality Application of the Fortress Al Zubarah in Qatar Including Performance Analysis of Real-Time Visualisation
Get PDFTechnological advancements in the area of Virtual Reality (VR) in the past years have the potential to fundamentally impact our everyday lives. VR makes it possible to explore a digital world with a Head-Mounted Display (HMD) in an immersive, embodied way. In combination with current tools for 3D documentation, modelling and software for creating interactive virtual worlds, VR has the means to play an important role in the conservation and visualisation of cultural heritage (CH) for museums, educational institutions and other cultural areas. Corresponding game engines offer tools for interactive 3D visualisation of CH objects, which makes a new form of knowledge transfer possible with the direct participation of users in the virtual world. However, to ensure smooth and optimal real-time visualisation of the data in the HMD, VR applications should run at 90 frames per second. This frame rate is dependent on several criteria including the amount of data or number of dynamic objects. In this contribution, the performance of a VR application has been investigated using different digital 3D models of the fortress Al Zubarah in Qatar with various resolutions. We demonstrate the influence on real-time performance by the amount of data and the hardware equipment and that developers of VR applications should find a compromise between the amount of data and the available computer hardware, to guarantee a smooth real-time visualisation with approx. 90 fps (frames per second). Therefore, CAD models offer a better performance for real-time VR visualisation than meshed models due to the significant reduced data volume
Defining Parameters for Urban-Environmental Quality Assessment
Get PDFMeasuring the quality of the urban environment has been a matter of research rooted in different fields of knowledge. Several methods and indicators have been deployed through the years, as have horizontal approaches from mixed perspectives. However, currently established indexes to measure urban performance depend on the actual definition of quality and on the weighted relevance of the different features influencing it. This contribution compares the level of emphasis paired by established indexes to measure urban quality, in contrast to what people mention the most when asked about what they like or dislike about the urban environment. The underlying idea is to obtain firsthand information about the way people make decisions about their movements in urban space. As a result, the authors observe a lack of correlation between the two groups of indicators and between the key urban elements driving positive and negative emotions. In conclusion, the authors observe a tendency of people to perceive and report individual physical elements rather than intangible concepts like safety or comfort
Consideration of Uncertainty Information in Accessibility Analyses for an Effective Use of Urban Infrastructures
Get PDFAccessibility analyses are an essential step in the evaluation and planning of urban infrastructures such as transport or pipeline networks. However, these studies generally produce sharply defined lines (called isovarones) or areas (called isovarone areas) that represent the same or similar accessibility. Uncertainties in the input data are usually not taken into account. The aim of this contribution is, therefore, to set up a structured framework that describes the integration of uncertainty information for accessibility analyses. This framework takes uncertainties in the input data, in the processing step, in the target variables, and in the final visualization into account. Particular attention is paid, on the one hand, to the impact of the uncertainties in the target values, as these are key factors for reasoning and decision making. On the other hand, the visualization component is emphasized by applying a dichotomous classification of uncertainty visualization methods. This framework leads to a large set of possible combinations of uncertainty categories. Five selected examples that have been generated with a new software tool and that cover important combinations are presented and discussed
CityScope Platform for Real-Time Analysis and Decision-Support in Urban Design Competitions
Get PDFThis paper presents a digital online tool and interaction process that supplies algorithmic analysis and predictive simulation for early-stage urban design proposals within the framework of public competitions. Specifically, the system supports the decision-making of two user groups: 1) planners in the process of developing urban designs proposals and 2) competition juries in evaluating those proposals. The system provides instant assessment of the design solutions' environmental and spatial impact regarding selected target criteria such as noise propagation or pedestrian accessibility. Enabling the easy testing of functional programs and the identification of feasible trade-offs between multiple design targets, the system supports rapid design iterations as well as the objective evaluation of proposals. Applied for the first time within an innovative tender format for a new residential and business district in Hamburg, Germany, the new toolset paves the way towards a more holistic and interactive form of sustainable urban design