In this paper, we identify the current status and outlook of the renewable energy source in Morocco. We provide also the challenges and the barriers to the development of renewable energy (RE) in Morocco and the national strategy for energy security and meeting these challenges. Then, using a time series method, we estimate the capacity of the wind and solar power in Morocco plans in the long-term towards 2030, that can be injected without creating the constraints of transit on the grid utility and on the whole electrical system.
The smart grid concept is predicated upon the pervasive use of advanced digital communication, information techniques, and artificial intelligence for the current power system to be more characteristics on the real-time monitoring and controlling of the supply/demand. Therefore, in recent years, researchers increasingly couple distinct simulators to form novel “co-simulations.” In this article, we will present a survey of different electrical power and communication simulators, a literature survey of 20 smart grid co-simulations frameworks, and the characteristics of each platform applicable in the intelligent electrical network. Finally, we proposed multi-agent systems for controlling the microgrid that consists of wind power and storage system using MACSimJX co-simulation that combines Simulink simulator and JADE (Java Agent Development Environment).
Summary
Standalone Power Systems (SPS), formerly known as Micro Power Systems, is an off‐grid electricity system for locations that are not fitted with an electricity generation. Typical SPS include one or more renewable electricity sources, energy storage, and regulation. In this paper, supervision of hybrid Photovoltaic system and battery storage is presented. The power balance of the hybrid system is made on an intelligent supervisor based on Artificial Neural Network Controller (ANNC). The main purpose of this paper is the control of DC/DC Bidirectional Converter (DBC), which connect the Li‐ion battery with the DC_Bus of Stand‐alone Power Systems (SPS). Based on the use of artificial neural network controller, which are effective tools for highly nonlinear system. The proposed technique does not require a pre‐defined model of power DBC only depend on power and voltage system data. Simulation for stand‐alone systems performed at Matlab Simulink. The comparison with PID controller for the result obtained of DC_Bus voltage, and power demanded, demonstrate the robustness, and satisfactory performance of the proposed control strategy.
<span>In this paper, an intelligent control strategy for a microgrid system consisting of Photovoltaic panels, grid-connected, and li-ion battery energy storage systems proposed. The energy management based on the managing of battery charging and discharging by integration of a smart controller for DC/DC bidirectional converter. The main novelty of this solution are the integration of artificial neural network (ANN) for the estimation of the battery state of charge (SOC) and for the control of bidirectional converter. The simulation results obtained in the MATLAB/Simulink environment explain the performance and the robust of the proposed control technique.</span>
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