REACTIVE POWER AS AN INFORMATION FACTOR IN ELECTRIC CIRCUITS

This article examines information processes in electrical circuits using the introduced concept of electrical entropy, which is analogous to thermodynamic entropy. Electrical entropy is understood as the time density of circulating reactive power. Because electrical energy is higher than thermal energy, the magnitude of entropy, unlike thermodynamics, takes on a different direction. Indeed, active power supplied to the network is transmitted to the load with high efficiency, and reactive elements are not associated with active power consumption or heating temperatures. Electrical entropy characterizes neither the degradation of energy nor the tendency of processes toward the most probable state of the system. On the contrary, this entropyindicates the degree of its approach to a less probable state, thus being a negative entropy—negentropy. This leads to the elimination of certain uncertainties, i.e., the generation of information processes in the electrical system. It has been shown that electrical entropy is a function of the system's state, characterizing the transformation of electrical energy from one form to another and the corresponding change in the parameters of the electric current. Zero electrical entropy means the absence of such transformations. This article examines various types of nonlinear electrical systems, using four basic power converters—rectifiers, standalone inverters, and buck and boost converters—as examples, where these phenomena are most evident. Circuits—models of transport networks, and general-purpose electrical networks—are also considered. It is shown that information processes are driven by reactive power and nonlinear elements, primarily power valves, which constitute the mechanism for influencing electrical systems. This article expands our understanding of the processes in such systems, as well as our view of reactive power, current, and voltage pulsations as harmful and counteractable—and counteractable only by understanding their role. The analysis is supported by modeling various systems in Matlab.