## Fachbereich Elektrotechnik, Maschinenbau, Technikjournalismus

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The temperature of photovoltaic modules is modelled as a dynamic function of ambient temperature, shortwave and longwave irradiance and wind speed, in order to allow for a more accurate characterisation of their efficiency. A simple dynamic thermal model is developed by extending an existing parametric steady-state model using an exponential smoothing kernel to include the effect of the heat capacity of the system. The four parameters of the model are fitted to measured data from three photovoltaic systems in the Allgäu region in Germany using non-linear optimisation. The dynamic model reduces the root-mean-square error between measured and modelled module temperature to 1.58 K on average, compared to 3.03 K for the steady-state model, whereas the maximum instantaneous error is reduced from 20.02 to 6.58 K.

Long-term variability of solar irradiance and its implications for photovoltaic power in West Africa
(2020)

West Africa is one of the least developed regions in the world regarding the energy availability and energy security. Located close to the equator West Africa receives high amounts of global horizontal irradiance (GHI). Thus, solar power and especially photovoltaic (PV) systems seem to be a promising solution to provide electricity with low environmental impact. To plan and to dimension a PV power system climatological data for global horizontal irradiance (GHI) and its variability need to be taken into account. However, ground based measurements of irradiances are not available continuously and cover only a few discrete locations.

Incoming solar radiation is an important driver of our climate and weather. Several studies (see for instance Frank et al. 2018) have revealed discrepancies between ground-based irradiance measurements and the predictions of regional weather models. In the realm of electricity generation, accurate forecasts of solar photovoltaic (PV)energy yield are becoming indispensable for cost-effective grid operation: in Germany there are 1.6 million PVsystems installed, with a nominal power of 46 GW (Bundesverband Solarwirtschaft 2019). The proliferation of PV systems provides a unique opportunity to characterise global irradiance with unprecedented spatiotemporalresolution, which in turn will allow for highly resolved PV power forecasts.

Renewable energies play an increasingly important role for energy production in Europe. Unlike coal or gas powerplants, solar energy production is highly variable in space and time. This is due to the strong variability of cloudsand their influence on the surface solar irradiance. Especially in regions with large contribution from photovoltaicpower production, the intermittent energy feed-in to the power grid can be a risk for grid stability. Therefore goodforecasts of temporal and spatial variability of surface irradiance are necessary to be able to properly regulate thepower supply.

Due to the policy goals for sustainable energy production, renewable energy plants such as photovoltaics are increasingly in use. The energy production from solar radiation depends strongly on atmospheric conditions. As the weather mostly changes, electrical power generation fluctuates, making technical planning and control of power grids to a complex problem.

In recent years, a plethora of observations with high spectral resolution of sub-millimetre and far-infrared transitions of methylidene (CH), conducted with Herschel and SOFIA, have demonstrated this radical to be a valuable proxy for molecular hydrogen that can be used for characterising molecular gas within the interstellar medium on a Galactic scale, including the CO-dark component. We report the discovery of the 13CH isotopologue in the interstellar medium using the upGREAT receiver on board SOFIA. We have detected the three hyperfine structure components of the ≈2 THz frequency transition from its X2Π1∕2 ground-state towards the high-mass star-forming regions Sgr B2(M), G34.26+0.15, W49(N), and W51E and determined 13CH column densities. The ubiquity of molecules containing carbon in the interstellar medium has turned the determination of the ratio between the abundances of the two stable isotopes of carbon, 12C/13C, into a cornerstone for Galactic chemical evolution studies. Whilst displaying a rising gradient with galactocentric distance, this ratio, when measured using observations of different molecules (CO, H2CO, and others), shows systematic variations depending on the tracer used. These observed inconsistencies may arise from optical depth effects, chemical fractionation, or isotope-selective photo-dissociation. Formed from C+ either through UV-driven or turbulence-driven chemistry, CH reflects the fractionation of C+, and does not show any significant fractionation effects, unlike other molecules that were previously used to determine the 12C/13C isotopic ratio. This makes it an ideal tracer for the 12C/13C ratio throughout the Galaxy. By comparing the derived column densities of 13CH with previously obtained SOFIA data of the corresponding transitions of the main isotopologue 12CH, we therefore derive 12C/13C isotopic ratios toward Sgr B2(M), G34.26+0.15, W49(N) and W51E. Adding our values derived from 12∕13CH to previous calculations of the Galactic isotopic gradient, we derive a revised value of 12C/13C = 5.87(0.45)RGC + 13.25(2.94).

Technik wird in unserer Gesellschaft noch immer mit Männlichkeit assoziiert. Das Bild eines Mannes, der mit einer schweren Bohrmaschine arbeitet, erscheint uns vertrauter als das einer Frau, die dieselbe Tätigkeit ausführt. Derartige Repräsentationen von Technik und Geschlecht werden auch von den Medien verbreitet und könnten so bereits Mädchen und jungen Frauen den Zugang zu Technik erschweren. Digitalisierte Medienwelten bieten allerdings die Möglichkeit, neue Technik-Bilder zu entwerfen und dominante Vorstellungen dadurch zu verschieben. Hier könnten Öffentlichkeiten für Mädchen und Frauen entstehen, die eine Selbstverständigung über technische Interessen und damit einhergehend eine Erfahrung von Kompetenz vermitteln könnten. Anhand von fünf Gruppendiskussionen mit 12- bis 15-jährigen Gymnasiastinnen wurden deren Technikverständnis, deren Nutzung digitaler Medien zu Technikthemen, vor allem aber auch deren Ideen zu einer für sie attraktiven Vermittlung von Technikthemen erfragt. Dabei wurden insbesondere die Vorteile einer symmetrischen Kommunikation im Netz deutlich.

This paper addresses long-term changes in solar irradiance for West Africa (3° N to 20° N and 20° W to 16° E) and its implications for photovoltaic power systems. Here we use satellite irradiance (Surface Solar Radiation Data Set-Heliosat, Edition 2.1, SARAH-2.1) to derive photovoltaic yields. Based on 35 years of data (1983–2017) the temporal and regional variability as well as long-term trends of global and direct horizontal irradiance are analyzed. Furthermore, at four locations a detailed time series analysis is undertaken. The dry and the wet season are considered separately.
According to the high resolved SARAH-2.1 data record (0.05° x 0.05°), solar irradiance is largest (with up to 300 W/m² daily average) in the Sahara and the Sahel zone with a positive trend (up to 5 W/m²/decade) and a lower variability (< 75 W/m²). Whereas, the solar irradiance is lower in southern West Africa (between 200 W/m² and 250 W/m²) with a negative trend (up to −5 W/m²/decade) and a higher variability (up to 150 W/m²). The positive trend in the North is mostly connected to the dry season, while the negative trend in the South occurs during the wet season. PV yields show a strong meridional gradient with lowest values around 4 kWh/kWp in southern West Africa and reach more than 5.5 kWh/kWp in the Sahara and Sahel zone.

Solving diﬀerential-algebraic equations (DAEs) eﬃciently by means of appropriate numerical schemes for time-integration is an ongoing topic in applied mathematics. In this context, especially when considering large systems that occur with respect to many ﬁelds of practical application eﬀective computation becomes relevant. In particular, corresponding examples are given when having to simulate network structures that consider transport of ﬂuid and gas or electrical circuits. Due to the stiﬀness properties of DAEs, time-integration of such problems generally demands for implicit strategies. Among the schemes that prove to be an adequate choice are linearly implicit Rung-Kutta methods in the form of Rosenbrock-Wanner (ROW) schemes. Compared to fully implicit methods, they are easy to implement and avoid the solution of non-linear equations by including Jacobian information within their formulation. However, Jacobian calculations are a costly operation. Hence, necessity of having to compute the exact Jacobian with every successful time-step proves to be a considerable drawback. To overcome this drawback, a ROW-type method is introduced that allows for non-exact Jacobian entries when solving semi-explicit DAEs of index one. The resulting scheme thus enables to exploit several strategies for saving computational eﬀort. Examples include using partial explicit integration of non-stiﬀ components, utilizing more advantageous sparse Jacobian structures or making use of time-lagged Jacobian information. In fact, due to the property of allowing for non-exact Jacobian expressions, the given scheme can be interpreted as a generalized ROW-type method for DAEs. This is because it covers many diﬀerent ROW-type schemes known from literature. To derive the order conditions of the ROW-type method introduced, a theory is developed that allows to identify occurring diﬀerentials and coeﬃcients graphically by means of rooted trees. Rooted trees for describing numerical methods were originally introduced by J.C. Butcher. They signiﬁcantly simplify the determination and deﬁnition of relevant characteristics because they allow for applying straightforward procedures. In fact, the theory presented combines strategies used to represent ROW-type methods with exact Jacobian for DAEs and ROW-type methods with non-exact Jacobian for ODEs. For this purpose, new types of vertices are considered in order to describe occurring non-exact elementary diﬀerentials completely. The resulting theory thus automatically comprises relevant approaches known from literature. As a consequence, it allows to recognize order conditions of familiar methods covered and to identify new conditions. With the theory developed, new sets of coeﬃcients are derived that allow to realize the ROW-type method introduced up to orders two and three. Some of them are constructed based on methods known from literature that satisfy additional conditions for the purpose of avoiding eﬀects of order reduction. It is shown that these methods can be improved by means of the new order conditions derived without having to increase the number of internal stages. Convergence of the resulting methods is analyzed with respect to several academic test problems. Results verify the theory determined and the order conditions found as only schemes satisfying the order conditions predicted preserve their order when using non-exact Jacobian expressions.

The need for innovation around the control functions of inverters is great. PV inverters were initially expected to be passive followers of the grid and to disconnect as soon as abnormal conditions happened. Since future power systems will be dominated by generation and storage resources interfaced through inverters these converters must move from following to forming and sustaining the grid. As “digital natives” PV inverters can also play an important role in the digitalisation of distribution networks. In this short review we identified a large potential to make the PV inverter the smart local hub in a distributed energy system. At the micro level, costs and coordination can be improved with bidirectional inverters between the AC grid and PV production, stationary storage, car chargers and DC loads. At the macro level the distributed nature of PV generation means that the same devices will support both to the local distribution network and to the global stability of the grid. Much success has been obtained in the former. The later remains a challenge, in particular in terms of scaling. Yet there is some urgency in researching and demonstrating such solutions. And while digitalisation offers promise in all control aspects it also raises significant cybersecurity concerns.

In complex, expensive optimization domains we often narrowly focus on finding high performing solutions, instead of expanding our understanding of the domain itself. But what if we could quickly understand the complex behaviors that can emerge in said domains instead? We introduce surrogate-assisted phenotypic niching, a quality diversity algorithm which allows to discover a large, diverse set of behaviors by using computationally expensive phenotypic features. In this work we discover the types of air flow in a 2D fluid dynamics optimization problem. A fast GPU-based fluid dynamics solver is used in conjunction with surrogate models to accurately predict fluid characteristics from the shapes that produce the air flow. We show that these features can be modeled in a data-driven way while sampling to improve performance, rather than explicitly sampling to improve feature models. Our method can reduce the need to run an infeasibly large set of simulations while still being able to design a large diversity of air flows and the shapes that cause them. Discovering diversity of behaviors helps engineers to better understand expensive domains and their solutions.

Network aggregation
(2020)

Demand forecast
(2020)