METHODOLOGICAL PRINCIPLES OF MANAGEMENT OF SUSTAINABLE ENERGY DEVELOPMENT IN THE CONDITIONS OF GLOBAL RISKS AND BIFURCATION SHIFTS

Abstract

The problem of ensuring the sustainable energy development in the conditions of global risks, the growth of global uncertainty, unpredictability and bifurcation shifts associating with the Fourth Industrial Revolution and the green "energy" transition is analyzed. The necessity of consider modern energy as complex emergent system in conditions of multivariate and non-linear development vectors of the global economy, energy is proven. Based on the analysis of the methodological provisions of the theories of linear and non-linear (synergistic) paradigms, the expediency of synergistic-cybernetic approach using for sustainable energy development managing is substantiated, taking into account that the energy trajectories of functioning and development is inherent in the synthesis of evolutionary (linear, orderly) and chaotic (non-linear) processes. It is determined that the main direction of cybernetic management of the energy system is the search and implementation of such controlling influences that, in the presence of external and internal fluctuations, will ensure a stable, safe, homeostatic mode of functioning of the system, in which it reaches its maximum efficiency. It is noted that the problem of homeostasis (stability) in cybernetics is considered from a purely functional point of view, and therefore (unlike synergetic) it does not analyze specific mechanisms of self-organization. Synergetic investigates non-linear processes of self-complexity of systems, the emergence of "order from chaos" (and vice versa) and studies processes when bifurcation shifts, several states of equilibrium (attractor) can occur, and when controlling influences does not directly regulate the system behavior. It is proved that the synergistic-cybernetic approach for managing the sustainable energy development must be considered as interdisciplinary, based on the wide application of the apparatus of synergistic modeling (fuzzy logic, neural networks, evolutionary algorithms, fractals, elements of chaos theory, etc.), economic-mathematical, balance, socio-psychological and other models and methods.