scholarly journals On Energy Management Control of a PV-Diesel-ESS Based Microgrid in a Stand-Alone Context

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2164 ◽  
Author(s):  
Ahmed Belila ◽  
Mohamed Benbouzid ◽  
El-Madjid Berkouk ◽  
Yassine Amirat
Keyword(s):  
Energy Management ◽  
Power Flow ◽  
Control Strategies ◽  
Real Data ◽  
Management Control ◽  
Diesel Generator ◽  
Mode Control ◽  
Parallel Mode ◽  
Scale Test ◽  
Reduced Scale

This paper deals with the energy management control of a PV-Diesel-ESS-based microgrid in a stand-alone context. In terms of control, an Isolated Mode Control (IMC) strategy based on a resonant regulator is proposed. In Parallel Mode Control (PMC) conditions, the diesel generator (DG) is controlled to operate at its nominal power. In this context, a supervisory algorithm optimizing the power flow between the microgrid’s various components ensures switching between the two modes for different possible scenarios. To prove the effectiveness of the proposed control strategies, the energy management control (EMC) is tested first using a standard state of charge (SOC) profile emulating the microgrid different states. Then real data are used to simulate the load and solar radiations. An experimental validation on a reduced scale test bench is carried out to prove the feasibility and the effectiveness of the proposed energy management control strategies.

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 Real-Time Implementation of Robust Control Strategies Based on Sliding Mode Control for Standalone Microgrids Supplying Non-Linear Loads

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2590 ◽  
Author(s):  
Seghir Benhalima ◽  
Rezkallah Miloud ◽  
Ambrish Chandra
Keyword(s):  
Sliding Mode Control ◽  
Real Time ◽  
Sliding Mode ◽  
Control Strategies ◽  
Storage System ◽  
Voltage Source ◽  
Voltage Source Converter ◽  
Sliding Mode Controller ◽  
Diesel Generator ◽  
Mode Control

In this paper enhanced control strategies for standalone microgrids based on solar photovoltaic systems (SVPAs) and diesel engine driven fixed speed synchronous generators, are presented. Single-phase d-q theory-based sliding mode controller for voltage source converter voltage source converter (VSC) is employed to mitigate harmonics, balance diesel generator (DG) current, and to inject the generated power by SVPA into local grid. To achieve fast dynamic response with zero steady-state error during transition, sliding mode controller for inner control loop is employed. To achieve maximum power point tracking (MPPT) from SVPA without using any MPPT method, a DC-DC buck boost converter supported by battery storage system is controlled using a new control strategy based on sliding mode control with boundary layer. In addition, modeling and detailed stability analysis are performed. The performance of the developed control strategies, are validate by simulation using MATLAB/Simulink and in real-time using hardware prototype.

scholarly journals Development and Real-Time Performance Evaluation of Energy Management Strategy for a Dynamic Positioning Hybrid Electric Marine Vessel

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1280
Author(s):  
Truong M. N. Bui ◽  
Truong Q. Dinh ◽  
James Marco ◽  
Chris Watts
Keyword(s):  
Performance Evaluation ◽  
Real Time ◽  
Energy Management ◽  
Power Flow ◽  
Control Strategies ◽  
Storage System ◽  
Dynamic Positioning ◽  
Energy Management Strategy ◽  
Time Performance ◽  
Hybrid Electric

Hybridisation of energy sources in marine vessels has been recognized as one of the feasible solutions to improve fuel economy and achieve global emission reduction targets in the maritime sector. However, the overall performance of a hybrid vessel system is strongly dependent on the efficiency of the energy management system (EMS) that regulates the power-flow amongst the propulsion sources and the energy storage system (ESS). This study develops a simple but production-feasible and efficient EMS for a dynamic positioning (DP) hybrid electric marine vessel (HEMV) and real-time experimental evaluation within a hardware-in-the-loop (HIL) simulation environment. To support the development and evaluation, map-based performance models of HEMVs’ key components are developed. Control logics that underpin the EMS are then designed and verified. Real-time performance evaluation to assess the performance and applicability of the proposed EMS is conducted, showing the improvement over those of the conventional control strategies. The comparison using key performance indicators (KPIs) demonstrates that the proposed EMS could achieve up to 4.8% fuel saving per voyage, while the overall system performance remains unchanged as compared to that of the conventional vessel.

Real Time Energy Management Control Strategies for an Electrically Supercharged Gasoline Hybrid Vehicle

2020 ◽  
Author(s):  
Francesco Accurso ◽  
Alessandro Zanelli ◽  
Luciano Rolando ◽  
Federico Millo
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Control Strategies ◽  
Hybrid Vehicle ◽  
Management Control

scholarly journals Towards a Smarter Energy Management System for Hybrid Vehicles: A Comprehensive Review of Control Strategies

2019 ◽  
Vol 9 (10) ◽  
pp. 2026 ◽  
Author(s):  
Nan Xu ◽  
Yan Kong ◽  
Liang Chu ◽  
Hao Ju ◽  
Zhihua Yang ◽  
...  
Keyword(s):  
Energy Management ◽  
Control Strategies ◽  
Large Data ◽  
Management Control ◽  
Mode Switching ◽  
Rule Based ◽  
Comprehensive Review ◽  
Main Research ◽  
Deterministic Dynamic ◽  
Management Optimization

This paper presents a comprehensive review of energy management control strategies utilized in hybrid electric vehicles (HEVs). These can be categorized as rule-based strategies and optimization-based strategies. Rule-based strategies, as the most basic strategy, are widely used due to their simplicity and practical application. The focus of rule-based strategies is to determine and optimize the optimal threshold for mode switching; however, they fall into a local optimal solutions. To have better performance in energy management, optimization-based strategies were developed. The categories of the existing optimization-based strategies are identified from the latest literature, and a brief study of each strategy is discussed, which consists of the main research ideas, the research focus, advantages, disadvantages and improvements to ameliorate optimality and real-time performance. Deterministic dynamic programming strategy is regarded as a benchmark. Based on neural network and the large data processing technology, data-driven strategies are put forward due to their approximate optimality and high computational efficiency. Finally, the comprehensive performance of each control strategy is analyzed with respect to five aspects. This paper not only provides a comprehensive analysis of energy management control strategies for HEVs, but also presents the emphasis in the future.

scholarly journals Neural Network- and Fuzzy Control-Based Energy Optimization for the Switching in Parallel Hybrid Two-Wheeler

2021 ◽  
Vol 12 (1) ◽  
pp. 35
Author(s):  
Supriya Kalyankar-Narwade ◽  
Ramesh Kumar Chidambaram ◽  
Sanjay Patil
Keyword(s):  
Neural Network ◽  
Energy Management ◽  
Hybrid Electric Vehicle ◽  
Control Strategies ◽  
Energy Optimization ◽  
Switching Control ◽  
Management Control ◽  
Energy Utilization ◽  
Power Sources ◽  
Two Wheeler

Optimization of a two-wheeler hybrid electric vehicle (HEV) is a typical challenge compared to that for four-wheeler HEVs. Some of the challenges which are particular to two-wheeler HEVs are throttle integration, smooth switching between power sources, add-on weight compensation, efficiency improvisation in traffic, and energy optimization. Two power sources need to be synchronized skillfully for optimum energy utilization. A prominent variant of HEV is that it easily converts conventional scooters into parallel hybrids by “Through-the-Road (TTR)” architecture. This paper focuses on three switching control strategies of HEVs based on the state of charge, fuzzy logic, and neural network. Further, to optimize energy usage, all these control strategies are compared. Energy management control for the TTR model is developed with vehicle parameters in the Simulink environment and simulated using the “World Harmonized Motorcycle Test Cycle” (WMTC) drive cycle. The multivariable input model is presented with a fuzzy rule-based hybrid switching control. A similar system is also modeled with a neural network-based decision control and the observations are tabulated for the fuel economy and energy management. Simulation results show that the neural network-based optimization results in minimal energy consumption among all three hybrid operations.

scholarly journals Energy Management Control Strategies in The Egyptian Power System.(Dept.E)

2021 ◽  
Vol 18 (3) ◽  
pp. 61-78
Author(s):  
Hassan Younes ◽  
Kamel Yassin ◽  
El-Hussieny Abd-Raboh
Keyword(s):  
Power System ◽  
Energy Management ◽  
Control Strategies ◽  
Management Control
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