scholarly journals Real-Time Implementation of the Predictive-Based Control with Bacterial Foraging Optimization Technique for Power Management in Standalone Microgrid Application

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1723
Author(s):  
Félix Dubuisson ◽  
Miloud Rezkallah ◽  
Hussein Ibrahim ◽  
Ambrish Chandra
Keyword(s):  
Real Time ◽  
Power Management ◽  
Renewable Energy Sources ◽  
Optimization Technique ◽  
Euler Method ◽  
Small Scale ◽  
Diesel Generator ◽  
Bacterial Foraging Optimization ◽  
Time Model ◽  
Bacterial Foraging

In this paper, the predictive-based control with bacterial foraging optimization technique for power management in a standalone microgrid is studied and implemented. The heuristic optimization method based on the social foraging behavior of Escherichia coli bacteria is employed to determine the power references from the non-renewable energy sources and loads of the proposed configuration, which consists of a fixed speed diesel generator and battery storage system (BES). The two-stage configuration is controlled to maintain the DC-link voltage constant, regulate the AC voltage and frequency, and improve the power quality, simultaneously. For these tasks, on the AC side, the obtained power references are used as input signals to the predictive-based control. With the help of the system parameters, the predictive-based control computes all possible states of the system on the next sampling time and compares them with the estimated power references obtained using the bacterial foraging optimization (BFO) technique to get the inverter current reference. For the DC side, the same concept based on the predictive approach is employed to control the DC-DC buck-boost converter by regulating the DC-link voltage using the forward Euler method to generate the discrete-time model to predict in real-time the BES current. The proposed control strategies are evaluated using simulation results obtained with Matlab/Simulink in presence of different types of loads, as well as experimental results obtained with a small-scale microgrid.

Real-Time Model Predictive Control for Shipboard Power Management Using the IPA-SQP Approach

2015 ◽  
Vol 23 (6) ◽  
pp. 2129-2143 ◽  
Author(s):  
Hyeongjun Park ◽  
Jing Sun ◽  
Steven Pekarek ◽  
Philip Stone ◽  
Daniel Opila ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Real Time ◽  
Power Management ◽  
Predictive Control ◽  
Time Model ◽  
Shipboard Power

scholarly journals Design and Embedded Implementation of a Power Management Controller for Wind-PV-Diesel Microgrid System

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
M. Boussetta ◽  
S. Motahhir ◽  
R. El Bachtiri ◽  
A. Allouhi ◽  
M. Khanfara ◽  
...  
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Time Management ◽  
Storage System ◽  
Real Data ◽  
Energy System ◽  
Small Scale ◽  
Diesel Generator ◽  
The Real ◽  
Labview Software

This paper presents an implementation of real-time energy management systems (EMS) to maximize the efficiency of the electricity distribution in an isolated hybrid microgrid system (HMGS) containing photovoltaic modules, wind turbine, battery energy storage system, and diesel generator (DG) which is used as a backup source. These systems are making progress worldwide thanks to their respect for the environment. However, hybridization of several sources requires power flow control (PFC). For this reason, in this work, a proper energy management system is developed using LabVIEW software and embedded in a suitable platform for the real-time management of the hybrid energy system. The developed EMS is tested and validated through a small-scale application which accurately represents the case study of an isolated mosque located in a remote area of Morocco. The aim of this paper is to (i) propose a novel modelling method and real-time monitoring interface under the LabVIEW software based on the real data obtained by an optimal sizing previously made using Homer-pro software and (ii) implement the power control system on a low-consumption embedded platform that is the Raspberry-pi3.

scholarly journals Bacterial Foraging-Based Algorithm for Optimizing the Power Generation of an Isolated Microgrid

2019 ◽  
Vol 9 (6) ◽  
pp. 1261 ◽  
Author(s):  
Betania Hernández-Ocaña ◽  
José Hernández-Torruco ◽  
Oscar Chávez-Bosquez ◽  
Maria Calva-Yáñez ◽  
Edgar Portilla-Flores
Keyword(s):  
Information Technologies ◽  
Numerical Solutions ◽  
Renewable Energy Sources ◽  
Parameter Tuning ◽  
Point Of View ◽  
Bacterial Foraging Optimization ◽  
Bacterial Foraging ◽  
Reducing Costs ◽  
Best Parameter ◽  
Electrical Distribution Network

An Isolated Microgrid (IMG) is an electrical distribution network combined with modern information technologies aiming at reducing costs and pollution to the environment. In this article, we implement the Bacterial Foraging Optimization Algorithm (BFOA) to optimize an IMG model, which includes renewable energy sources, such as wind and solar, as well as a conventional generation unit based on diesel fuel. Two novel versions of the BFOA were implemented and tested: Two-Swim Modified BFOA (TS-MBFOA), and Normalized TS-MBFOA (NTS-MBFOA). In a first experiment, the TS-MBFOA parameters were calibrated through a set of 87 independent runs. In a second experiment, 30 independent runs of both TS-MBFOA and NTS-MBFOA were conducted to compare their performance on minimizing the IMG using the best parameter tuning. Results showed that TS-MBFOA obtained better numerical solutions compared to NTS-MBFOA and LSHADE-CV, an Evolutionary Algorithm, found in the literature. However, the best solution found by NTS-MBFOA is better from a mechatronic point of view because it favors the lifetime of the IMG, resulting in economic savings in the long term.

scholarly journals Grid-Following Mode Operation of Small-Scale Distributed Battery Energy Storages for Fast Frequency Regulation in a Mixed-Source Microgrid

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7710
Author(s):  
Amir Hussain ◽  
Wajiha Shireen
Keyword(s):  
Real Time ◽  
Renewable Energy Sources ◽  
Synchronous Generator ◽  
Frequency Instability ◽  
Power Converter ◽  
Rate Of Change ◽  
Frequency Regulation ◽  
Small Scale ◽  
Power Imbalance ◽  
Battery Energy

As the share of power converter-based renewable energy sources (RESs) is high, a microgrid, in islanded mode, is more vulnerable to frequency instability due to (1) sudden power imbalance and (2) low inertia. One of the most common approaches to address this issue is to provide virtual inertia to the system by appropriately controlling the grid-side converter of the RESs. However, the primary frequency controller (PFC) presented in this paper focuses on the fast compensation of power imbalance without adding inertia to the system. The proposed method is based on estimating the real-time power imbalance caused by a disturbance and compensating it using multiple small-scale distributed battery energy storage systems (BESSs). The power imbalance is estimated by observing the initial rate of change of frequency (RoCoF) following a disturbance. Based on the estimated power imbalance and the rating of the BESSs, the reference power for the BESSs is determined. The BESSs are controlled in grid-following mode to compensate for the power imbalance. The performance of the proposed PFC is verified using a Typhoon real-time simulator for various scenarios and is compared with the conventional virtual synchronous generator (VSG) controller.

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