Intelligent Energy Management of Electrical Power Systems

Abstract

Smart grid implementation is facilitated by multi-source energy systems development, i.e., microgrids, which are considered the key smart grid building blocks. Whether they are alternative current (AC) or direct current (DC), high voltage or low voltage, high power or small power, integrated into the distribution system or the transmission network, multi-source systems always require an intelligent energy management that is integrated into the power system. A comprehensive intelligent energy system aims at providing overall energy efficiency with regard to the following: increased power generation flexibility, increased renewable generation systems, improved energy consumption, reduced CO2 emission, improved stability, and minimized energy cost. This Special Issue presents recent key theoretical and practical developments that concern the models, technologies, and flexible solutions to facilitate the following optimal energy and power flow strategies: the techno-economic model for optimal sources dispatching (mono and multi-objective energy optimization), real-time optimal scheduling, and real time optimization with model predictive control.

Mixed Optimal Control Vector for a Boundary Value Problem of Couple Nonlinear Elliptic Equations

“…The subject of control theory has wide applications for many real life problems, in particular in science and engineering, for example, robotics [1], electric power [2], civil ISSN: 0067-2904 engineering [3], Aeronautics and Astronautics [4], medicine [5], economic [6], heat conduction [7] and biology [8]. In the field of mathematical sciences, optimal control problems are usually formulated in general either as ODEs [9] or as PDEs [10].…”

Sustainable Energy Systems: Optimization and Efficiency

“…This will maximize the benefits of exploiting the available clean and endogenous primary energy sources [5]. Thus, the technological advances and the new economic frameworks of the energy sector could guarantee full compliance with environmental constraints [6].…”