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The efficient production and utilization of green hydrogen is vital to succeed in the global strive for a sustainable future. To provide the necessary amount of green hydrogen a high number of electrolyzers will be connected as decentralized power consumers to the grid. A large amount of decentralized renewable power sources will provide the energy. In such a system a control method is necessary to dispatch the available power most efficiently. In particular, the shutdown of renewable energy sources due to temporary overproduction must be avoided. This paper presents a decentralized tertiary control algorithm that provides a new decentralized control approach, thus creating a flexible, robust and easily scalable system. The operation of each grid participant within this grid connected microgrid is optimized for maximum financial profit, while minimizing the exchange of power with the mains grid and reducing the shutdown of renewable power sources.
The increase in distributed energy generation, such as photovoltaic systems (PV) or combined heat and power plants (CHP), poses new challenges to almost every distribution network operator (DNO). In the low-voltage (LV) grids, where installed PV capacity approaches the magnitude of household load, reverse power flow occurs at the secondary substa-tions. High PV penetration leads to voltage rise, flicker and loading problems. These problems have been addressed by the application of various techniques amongst which is the deployment of step voltage regulators (SVR). SVR can solve the voltage problem, but do not prevent or reduce reverse power flows. Therefore, the application of SVR in low voltage grids can result in significant power losses upstream. In this paper we present part of a research project investi-gating the application of remote-controlled cable cabinets (CC) with metering units in a low-voltage network as a possible alternative for SVR. A new generation of custom-made remote-control cable cabinets has been deployed and dynamic network reconfigurations (NR) have been realized with the following objectives: (i) reduction of reverse power flow through the secondary substation to the upstream network and therefore a reduction of upstream losses, (ii) reduction of the voltage rise caused by distributed energy resources and (iii) load balancing in the low-voltage grid. Secondary objec-tives are to improve the DNO's insight into the state of the network and to provide further information on future smart grid integration.
Class Phi2 amplifier using GaN HEMTs at 13.56MHz with tuned transformer for wireless power transfer
(2022)
This paper discusses a design procedure of a wireless power transfer system at a RF switching frequency of 13.56MHz. The wireless power transfer amplifier uses GaN HEMTs in aClass phi2 topology and is designed in order to achieve high efficiency and high power density. A design method for the load over a certain bandwidth is presented for a transformer with its tuning network.
Switched reluctance motors are particularly attractive due to their simple structure. The control of this machine type requires the instants, to switch the currents in the motor phases in an appropriate sequence. These switching instants are determined either based on a position sensor, or on signals generated by a sensorless method. A very simple sensorless method uses the switching frequency of the hysteresis controllers used for phase current control. This paper first presents an automatic commissioning method for this sensorless method and second a startup procedure, thus enhancing this approach towards an application in industry.
The current paper proposes a design method for an active damping approach for LC output filters in a power stage for motor control with continuous output voltage. The power stage uses GaN-HEMTs and operates at switching frequencies in a range between 500 kHz and 1MHz. The active damping of the output filter is achieved here by a feedback of the filter inductor current using a high-pass structure. The paper discusses the impact of this feedback on the system behavior and proposes a design method.
Eine Organisation hin zur Klimaneutralität zu transformieren, ist nicht nur Neuland für praktisch jeden, der loslegt: Es geht los mit dem „Wollen“, also dem Ziel, dann wird der Weg skizziert, und schließlich muss es auch noch jemand umsetzen. Aus ihren Projekten der Begleitung von Organisationen auf dem Weg zur Klimaneutralität erscheint den Autoren folgende Erfahrung des Geschäftsführers Philipp Tiefenbach der Dorfbäckerei Tiefenbach, St. Johann-Würtingen, besonders treffend: „Machen ist wie Wollen, nur krasser.“ Für eine Kommune gerät dieser Prozess zu einem „wicked problem“. Sechs Lösungswege für Kommunen erscheinen attraktiv.
Electronic design automation approaches can roughly be divided into optimizers and procedures. While the former have enabled highly automated synthesis flows for digital integrated circuits, the latter play a vital (but mostly underestimated role) in the analog domain. This paper describes both automation strategies in comparison, identifying two fundamentally different automation paradigms that reflect the two basic design practices known as “top-down” and “bottom-up”. Then, with a focus on the latter, the history of procedural approaches is traced from their
early beginnings until today’s evolvements and future prospects to underline their practical importance and to accentuate their scientific value, both in itself and in the overall context of EDA.
This paper presents an improvement in usability and integrity of simulation-based analog circuit sizing. Instead of using geometrical sizing parameters (width, length), a transformed design-space, consisting exclusively of electrical parameters (branch currents, efficiencies and speed) is utilized. This design-space is explored more efficiently by optimizers. Moreover, this design-space can be reduced without affecting the quality of the result. The method is illustrated on two application examples, a symmetrical and a miller operational amplifier. Sizing the circuits using the transformed design-space showed significant reduction in required circuit simulations (up to 11x faster), better convergence, without loss in quality.
The integration of renewable energy sources in single family homes is challenging. Advance knowledge of the demand of electrical energy, heat, and domestic hot water (DHW) is useful to schedule projectable devices like heat pumps. In this work, we consider demand time series for heat and DHW from 2018 for a single family home in Germany. We compare different forecasting methods to predict such demands for the next day. While the 1-day-back forecast method led to the prediction of heat demand, the N-day-average performed best for DHW demand when Unbiased Exponentially Moving Average (UEMA) is used with a memory of 2.5 days. This is surprising as these forecasting methods are very simple and do not leverage additional information sources such as weather forecasts.
This paper presents a machine learning powered, procedural sizing methodology based on pre-computed look-up tables containing operating point characteristics of primitive devices. Several Neural Networks are trained for 90nm and 45nm technologies, mapping different electrical parameters to the corresponding dimensions of a primitive device. This transforms the geometric sizing problem into the domain of circuit design experts, where the desired electrical characteristics are now inputs to the model. Analog building blocks or entire circuits are expressed as a sequence of model evaluations, capturing the sizing strategy and intention of the designer in a procedure, which is reusable across different technology nodes. The methodology is employed for the sizing of two operational amplifiers, and evaluated for two technology nodes, showing the versatility and efficiency of this approach.