Global environmental changes, nuclear power risks, losses in the electricity grid, and rising energy costs are increasing the desire to rely on more renewable energy for electricity generation. Recently, most people prefer to live and work in smart places like smart cities and smart universities which integrating smart grid systems. The large part of these smart grid systems is based on hybrid energy sources which make the energy management a challenging task. Thus, the design of an intelligent energy management controller is required. The present paper proposes an intelligent energy management controller based on combined fuzzy logic and fractional-order proportional-integral-derivative (FO-PID) controller methods for a smart DC-microgrid. The hybrid energy sources integrated into the DC-microgrid are constituted by a battery bank, wind energy, and photovoltaic (PV) energy source. The source-side converters (SSCs) are controller by the new intelligent fractional order PID strategy to extract the maximum power from the renewable energy sources (wind and PV) and improve the power quality supplied to the DC-microgrid. To make the microgrid as cost-effective, the (wind and PV) energy sources are prioritized. The proposed controller ensures smooth output power and service continuity. Simulation results of the proposed control schema under Matlab/Simulink are presented and compared with the super twisting fractional-order controller.

This paper is mainly dedicated to an extension of the Slepian-Bangs formula to non-circular complex elliptical symmetric (NC-CES) distributions, which is derived from a new stochastic representation theorem. This formula includes the non-circular complex Gaussian and the circular CES (CCES) distributions. Some general relations between the Cramer Rao bound (CRB) under CES and Gaussian distributionsare deduced. It is proved in particular that the Gaussian distribution does not always lead to the largest stochastic CRB (SCRB) as many authors tend to believe it. Finally a particular attention is paid to the noisy mixture where closed form expressions for the SCRBs of the parameters of interest are derived.

This paper designs an intelligent energy management control for a stand alone smart DC- micro-grid using super twisting fractional order method. Based on mathematical model of the micro-grid, controllers are derived for the source side converters such as photovoltaic (PV),wind, AC grid and battery management system, and load side converters. Based on the available measured input and consumed output power, an intelligent energy management algorithm decides the appropriate mode of operation for the source and load side converters controller. All DC loads connected to the micro-grid are treated as essential loads and no load shedding can be allowed by the energy management unit. The energy management unit prioritizes the renewable energy sources (PV and wind) in order to make the micro-grid as cost effective. The performance of the proposed control scheme is compared with the integer order controller and the system is simulated in MATLAB/SIMULINK environment for different test cases.