Lithium-Ion batteries modeling and state of charge estimation using Artificial Neural Network

In This paper, we propose an effective and online technique for modeling nd State of Charge (SoC) estimation of Lithium-Ion (Li-Ion) batteries using Feed Forward Neural Networks(FFNN) and Nonlinear Auto Regressive model with eXogenous input(NARX). The both Artificial Neural Network (ANN) are rained using the data collected from the batterycharging and discharging pro ess. The NARX network finds the needed battery model, where the input ariables are the battery terminal voltage, SoC at the previous sample, and the urrent, temperature at the present sample. The proposed method is imple mented on a Li-Ion battery cell to estimate online SoC. Simulation results show good estimation of theSoC

Intelligent control of battery energy storage for microgrid energy management using ANN

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

LVRT and HVRT control strategies of doubly- fed induction generator

The Doubly Fed Induction Generator (DFIG) has a high sensitivity to the Grid Faults (GFs), which can cause many problems on the power quality and the production continuity. Actually, the grid connection requirements impose strict laws to respect to Low Voltage Ride Through (LVRT), High Voltage Ride Through (HVRT), and grid support capacities following the Grid Codes (GCs). In fact, when detecting voltage fault, Wind Turbines (WTs) should stay in connection with the grid in order to hold a safe and stable operation. The main objective of this work is to propose LVRT and HVRT strategies able to retain WTs connected to the grid during severe grid voltage faults. The proposed approach is a hybrid method combining two methods (active and passive methods): The first aim is to develop the control of DFIG, while the second is applied for severe voltage faults using hardware protection circuits

A comparison between series dynamic resistors and CROWBAR circuit protection for LVRT capability of doubly-fed induction generator

In this paper, we will focus on a comparison between two strategies (the Series Dynamic Resistors (SDR) and CROWBAR circuit for Low Voltage Ride Through (LVRT) capability of Doubly-Fed Induction Generator (DFIG), in order to determine different responses of reactive power and active power during the grid faults in line with the requirements determined by the grid codes (GCs). The two strategies are simulated by using MATLAB/Simulink environment

A deterministic method of distributed generation hosting capacity calculation: case study of underground distribution grid in Morocco

Global warming has become a significant concern over the past decades. As a result, governments have shifted their policies toward renewable energy sources and environmentally friendly industries. This approach requires a renewal of the electrical networks to accommodate this new intermittent generation (from solar and wind sources) while remaining stable and reliable. In this vision, the notion of hosting capacity has been introduced to define the amount of new distributed generation that an electrical network can host without affecting its stability and reliability. This study proposes a deterministic method based on the π model of cables to estimate the underground feeder's hosting capacity. This method considers reverse power flow, overvoltage, reconfiguration, overloading, and the physical characteristics of lines. It is applied to the Moroccan medium voltage underground radial feeder. Through DIgSILENT power factory software, the power flow analysis is carried out to validate its effectiveness in overcoming overvoltage and cable overload problems. The results validate the relevance of our method, its reliability, its fluidity of application, and its ability to maintain performance indices within the acceptable range

Fuzzy logic-based controller of the bidirectional direct current to direct current converter in microgrid

Microgrids are small-scale power networks that include renewable energy sources, load, energy storage systems, and energy management systems (EMS). Lithium-ion batteries are the most used battery for energy storage in microgrids due to their advantages over other types of batteries. However, to protect the battery from the explosion and to manage to charge and discharge based on state-of-charge (SoC) value, this type of battery requires the use of an energy management system. The main objective of this paper is to propose an intelligent control strategy for energy management in the microgrid to control the charge and discharge of Li-ion batteries to stabilize the system and reduce the cost of electricity due to the high cost of grid electricity. The proposed technique is based on a fuzzy logic controller (FLC) for voltage control. The FLC is based on the measured voltage of the direct current (DC) bus and the fixed reference voltage to generate buck/boost converter signal control. The proposed technique has been simulated and tested using MATLAB/Simulink software which illustrates the tracking of desired power and DC bus voltage regulation. The simulation results confirm that the proposed systems can diminish the deviations of the system's voltage

Intelligent energy management system of a smart microgrid using multiagent systems

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 of the real-time monitoring and controlling of the supply/demand. Microgrids are modern types of power systems used for distributed energy resource (DER) integration. However, the microgrid energy management, the control, and protection of microgrid components (energy sources, loads, and local storage units) is an important challenge. In this paper, the distributed energy management algorithm and control strategy of a smart microgrid is proposed using an intelligent multi-agent system (MAS) approach to achieve multiple objectives in real-time. The MAS proposed is developed with co-simulation tools, which the microgrid model, simulated using MATLAB/Simulink, and the MAS algorithm implemented in JADE through a middleware MACSimJX. The main study is to develop a new approach, able to communicate a multi-task environment such as MAS inside the S-function block of Simulink, to achieve the optimal energy management objectives

Harmonic pollution filtering: case study of a university campus

This paper provides a study of the benefits and improvements in electrical power quality obtained by filtering harmonic pollution. A continuous 7-day measurement by a network analyzer at the secondary level of a higher education institution's transformer proved the existence of important harmonic pollution. We proposed to attenuate these harmonics by installing passive filters at the general circuit breaker. The simulations were carried out with Matlab/Simulink software, based on a set of data measured by the network analyzer. This harmonic pollution-filtering project will improve the quality of power and make significant energy savings

Frequency Control and Energy Management of Microgrid with Distributed Energy Storage

The purpose of the Energy Management System (EMS) is to ensure a high degree of efficiency, stability, and dependability. And the electrical system should have the ability to adjust to the majority of changes such as renewable energy integration. In some situations, the power generated by distributed power sources is greater than the local demand. This has an effect on the microgrid's stability and frequency. Smart energy management in a microgrid is proposed in this research., consisting of a wind power generator, photovoltaic and storage energy system for frequency regulation, and system balance. The above paper's main contribution is a system for managing energy. based on a clever strategy using MATLAB/Simulink. The results of the simulation and analyses demonstrate that the suggested microgrid energy management system is efficient at balancing energy