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This paper discusses the optimal control problem for increasing the energy efficiency of induction machines in dynamic operation including field weakening regime. In an offline procedure optimal current and flux trajectories are determined such that the copper losses are minimized during transient operations. These trajectories are useful for a subsequent online implementation.
Steady state efficiency optimization techniques for induction motors are state of the art and various methods have already been developed. This paper provides new insights in the efficiency optimized operation in dynamic regime. The paper proposes an anticipative flux modification in order to decrease losses during torque and speed transients. These trajectories are analyzed based on a numerical study for different motors. Measurement results for one motor are given as well.
Energy efficiency optimization techniques for steady state operation of induction machines are the state-of-the-art, and many methods have already been developed. However, many real-world industrial and electric vehicle applications cannot be considered to be in steady state operation. The focus of this contribution is on the efficiency optimization of induction machines in dynamic operation. Online dynamic operation is challenging due to the computational complexity and the required low sample times in an inverter. An offline optimization is therefore conducted to gain knowledge. Based on this offline optimal solution, a simple and easy to implement template based solution is developed. This approach aims at replicating the solution found by the offline optimization by resembling the shape and anticipative characteristics of the optimal flux trajectory. The energy efficiency improvement of the template based solution is verified by simulations and measurements on a test bench and using a real-world drive cycle scenario. For comparison, a model predictive numerical online optimization is investigated too.
Purpose. To improve the efficiency of the closed-cycle operation of the field-orientation induction machine in dynamic behavior when load conditions are changing, considering the nonlinearities of the main inductance.
Methodology. The optimal control problem is defined as the minimization of the time integral of the energy losses. The algorithm observed in this paper uses the Matlab/Simulink, dSPACE real-time interface, and C language. Handling real-time applications is made in ControlDesk experiment software for seamless ECU development.
Findings. Adiscrete-time model with an integrated predictive control scheme where the optimization is performed online at every sampling step has been developed. The optimal field-producing current trajectory is determined, so that the copper losses are minimized over a wide operational range. Additionally, the comparison of measurement results with conventional methods is provided, which validates the advantages and performance of the control scheme.
Originality. To solve the given problem, the information vector on the current state of the coordinates of the electromechanical system is used to form a controlling influence in the dynamic mode of operation. For the first time, the formation process of controls has considered the current state and the desired future state of the system in the real-time domain.
Practical value. Apredictive iterative approach for optimal flux level of an induction machine is important to generate the required electromagnetic torque and to reduce power losses simultaneously.
Energy efficient electric control of drives is more and more important for electric mobility and manufacturing industries. Online dynamic optimization of induction machines is challenging due to the computational complexity involved and the variable power losses during dynamic operation of induction machines. This paper proposes a simple technique for sub-optimal online loss optimization using rotor flux linkage templates for energy efficient dynamic operation of induction machines. Such a rotor flux linkage template is given by a rotor flux linkage trajectory which is optimal for a specific scenario. This template is calculated in an offline optimization process. For a specific scenario during real time operation the rotor flux linkage is calculated by appropriately scaling the given template.
Germany aims to achieve carbon-neutral electricity generation by 2045. As a part of this plan, solar and wind electricity generation is expected to increase significantly. Since renewable energy sources are highly volatile and intermittent, this leads to periods of energy surplus and deficit, resulting in need of energy storage solutions for efficient utilisation of renewable energy sources and grid stabilisation. The current paper proposes the utilisation of hydrogen as an energy storage system to balance the supply and demand dynamics in Germany for 2045 with an electrolyser sizing of 155 GW and a fuel cell sizing of 123 GW as a sustainable and profitable hydrogen system sizing for Germany in 2045. The paper illustrates that, fuel cell and electrolyser sizing can fully compensate for the future power deficit exacerbated by heating electricity and battery electric vehicles charging demand of Germany.
The production of green hydrogen is of paramount importance for the global transition to a carbon free energy supply. Electrolyzers that run on renewable energy are used to produce green hydrogen. The installed renewable power capacity is expected to vastly increase over the coming years. This greatly increased capacity in combination with the volatile nature of such power sources will require a short term energy dispatch. In this scenario an electrolyzer must be able to operate in dynamic conditions. This paper presents an optimal control solution to this future real world application considering the unique operational and economical characteristics of an electrolyzer as well as the dynamic mode of operation due to future short term energy dispatch. The necessity of such a control strategy is demonstrated by simulation results.
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.
Simulation eines dezentralen Regelungssystems zur netzdienlichen Erzeugung von grünem Wasserstoff
(2023)
Wasserstoff wird einen bedeutenden Beitrag zum Wandel von Industrie und Gesellschaft in eine klimaneutrale Zukunft leisten. Der Aufbau und die ökologisch und ökonomisch sinnvolle Nutzung einer Wasserstoffinfrastruktur sind hierbei die zentralen Herausforderungen. Ein notwendiger Baustein ist die effiziente Bereitstellung von grünem Strom und dem daraus produzierten grünen Wasserstoff. Der vorliegende Beitrag stellt ein dezentrales Regel- und Kommunikationssystem vor, mit dem Angebot und Nachfrage von grünem Strom und Wasserstoff in einem System aus dezentralen Akteuren in Einklang gebracht werden. In einer hierzu entwickelten Simulationsumgebung wird die Funktion und der Nutzen dieses dezentralen Ansatzes verdeutlicht.
