Abstract

This paper discusses a utility function-based control of a battery-ultracapacitor (UC) hybrid energy system. The example system employs the battery semiactive topology. In order to represent different performance and requirements of the battery and UC packs, the two packs are modeled as two independent but related agents using the NetLogo environment. Utility functions are designed to describe the respective preferences of battery and UC packs. Then, the control problem is converted to a multiobjective optimization problem solved by using the Karush-Kuhn-Tucker (KKT) conditions. The weights in the objective functions are chosen based on the location of the knee point in the Pareto set. Both the simulation and experimental results show the utility function-based control provides a comparable performance with the ideal average load demand (ALD)-based control, while the exact preknowledge of the future load demand is not required. The utility function-based control is fast enough to be directly implemented in real time. The discussion in this paper gives a starting point and initial results for dealing with more complex hybrid energy systems.

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