The Newcomb-Benford law, also known as Benford's law, is the law of anomalous numbers stating that in many real-life numerical datasets, including physical and statistical ones, numbers have a small initial digit. Numbers irregularity observed in nature leads to the question, is the arithmetical-logical unit, responsible for performing calculations in computers, optimal? Are there other architectures, not as regular as commonly used Parallel Prefix Adders, that can perform better, especially when operating on the datasets that are not purely random, but irregular? In this article, structures of a propagate-generate tree are compared including regular and irregular configurations—various structures are examined: regular, irregular, with gray cells only, with both gray and black, and with higher valency cells. Performance is evaluated in terms of energy consumption. The evaluation was performed using the extended power model of static CMOS gates. The model is based on changes of vectors, naturally taking into account spatio-temporal correlations. The energy parameters of the designed cells were calculated on the basis of electrical (Spice) simulation. Designs and simulations were done in the Cadence environment and calculations of the power dissipation were performed in MATLAB. The results clearly show that there are PPA structures that perform much better for a specific type of numerical data. Negligent design can lead to an increase greater than two times of power consumption. The novel architectures of PPA described in this work might find practical applications in specialized adders dealing with numerical datasets, such as, for example, sine functions commonly used in digital signal processing.