Cost-Optimized Control of DC Microgrids based on Characteristic Diagrams

Abstract

This paper presents a novel approach for an energy control of a DC microgrid. It combines decentralized grid management and energy management. For this purpose, the conventional voltage droop curves are extended to a characteristic diagram with electricity costs as a further dimension. The support points of these characteristic diagrams are then optimized with a particle swarm optimizer. The target criterion of this optimization is a monetary cost function, that takes several effects, such as depth of discharge, on the operating costs into account. The optimized characteristic diagrams are designed more robust by a sensitivity analysis. The proposed method has been tested successfully in simulations and experiment and was always more cost-efficient than the initial characteristics diagram. Index Terms-energy control, DC microgrid, characteristic diagrams, voltage droop control This is the author's version of an article that has been published in the ICIT 2019 proceedings.

Decentralized Cost-Optimized Fuzzy Control of DC Microgrids

“…The modeling of the DC Grid was done as proposed in [1] and will be explained here only briefly. Since the model of the DC network is invoked often in the optimization, a short runtime is mandatory.…”

“…The model was validated in [1] with the test setup described in [11]. The error between simulated and measured rectifier power for a 15 minute measurement is less than 4.5 %.…”

“…In addition, the characteristic diagrams should be a monotonic (growing) function. In [1] a great effort was made to prevent this. Due to the predesigning of the fuzzy rules this post processing is not necessary, but by optimizing the fuzzy rules this advantage would be lost again.…”

“…Another option without communication is to extend the dimension of the characteristic curves so that the current provided also depends on the electricity costs. This characteristic, as proposed in our previous work, diagrams were optimized offline based on the load cycle and then loaded onto the controller [1]. With this method, the advantages of the adaptation can be used without the need for additional communication and computing power.…”

“…The optimization was performed in terms of minimizing the operative costs of the DC microgrid. This method and its results were in the end compared with the optimized characteristic diagrams presented in [1]. These diagrams were an extension of the voltage droop curves and the optimization was also based on the operating costs of the grid.…”