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 Energy Management for a Small Scale PV-Battery Microgrid: Modeling, Design, and Experimental Verification

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2712 ◽  
Author(s):  
Mahmoud Elkazaz ◽  
Mark Sumner ◽  
David Thomas
Keyword(s):  
Energy Storage ◽  
Real Time ◽  
Energy Management ◽  
Storage System ◽  
Reference Value ◽  
Energy Storage System ◽  
Small Scale ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy

A new energy management system (EMS) is presented for small scale microgrids (MGs). The proposed EMS focuses on minimizing the daily cost of the energy drawn by the MG from the main electrical grid and increasing the self-consumption of local renewable energy resources (RES). This is achieved by determining the appropriate reference value for the power drawn from the main grid and forcing the MG to accurately follow this value by controlling a battery energy storage system. A mixed integer linear programming algorithm determines this reference value considering a time-of-use tariff and short-term forecasting of generation and consumption. A real-time predictive controller is used to control the battery energy storage system to follow this reference value. The results obtained show the capability of the proposed EMS to lower the daily operating costs for the MG customers. Experimental studies on a laboratory-based MG have been implemented to demonstrate that the proposed EMS can be implemented in a realistic environment.

scholarly journals Energy Management of a Multi-Source Vehicle by λ-Control

2020 ◽  
Vol 10 (18) ◽  
pp. 6541
Author(s):  
Ali Castaings ◽  
Walter Lhomme ◽  
Rochdi Trigui ◽  
Alain Bouscayrol
Keyword(s):  
Energy Storage ◽  
Fuel Cell ◽  
Real Time ◽  
Energy Management ◽  
Management Strategy ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Management Strategy ◽  
The Real ◽  
Hydrogen Consumption

This paper deals with the real-time energy management of a fuel cell/battery/supercapacitors energy storage system for electric vehicles. The association of the battery and the supercapacitors with the fuel cell aims to reduce the hydrogen consumption while limiting the constraints on the fuel cell and the battery. In this paper, a real-time optimization-based energy management strategy by λ-control is proposed. Simulation results on a standard driving cycle show that the hydrogen consumption is reduced by 7% in comparison with a fuel-cell-based electric vehicle without any secondary energy storage source. Moreover, the energy management strategy ensures the system safety while preserving the fuel cell and the battery. Experimental results show that the developed energy management strategy is well-suited for the real-time requirements, applicability, and safety.

scholarly journals Fuzzy Decision-Based Optimal Energy Dispatch for Integrated Energy Systems With Energy Storage

2021 ◽  
Vol 9 ◽  
Author(s):  
Qiang Gao ◽  
Xiaodi Zhang ◽  
Mixia Yang ◽  
Xianqing Chen ◽  
Hongqing Zhou ◽  
...  
Keyword(s):  
Energy Storage ◽  
Real Time ◽  
Fuzzy Controller ◽  
Storage System ◽  
Minimum Cost ◽  
Energy System ◽  
Storage Device ◽  
Human Society ◽  
The Real ◽  
Integrated Energy System

The integrated energy system is an important strategic direction in the world’s future energy field, which will become the main carrier form of the energy future of human society in the next 30–50 years, directly affecting or even determining the future energy strategy pattern of the world. There are many types of integrated energy system. In the study of optimal dispatching of energy storage, the integrated energy system is modeled according to the energy transmission characteristics of the integrated energy system, which mainly includes the combined cooling, heating and power system and the multi-type energy storage system containing electricity and heat storage. Then, a two-tier optimal scheduling model for an integrated energy system with multiple types of energy storage as the core is established, divided into the day-head scheduling layer and the real-time dispatch layer. At the day-head scheduling layer, an optimization model has been proposed with the minimum cost of the optimization goal and the power network, heating network, cooling network, energy storage operation constraints and carbon constraints as constraints. Then at the real-time dispatch layer, utilize the fuzzy controller to dispatch and control the electric storage system and the thermal storage system. Finally, the verification simulation experiment is carried out in an industrial park. Besides, the energy efficiency, economy and environmental performance before and after the integrated energy system connected to the multi-energy storage device are compared and analyzed, and different scheduling methods are used to compare and prove the advantages of the scheduling method.

Single Depth View Based Real-Time Reconstruction of Hand-Object Interactions

2021 ◽  
Vol 40 (3) ◽  
pp. 1-12
Author(s):  
Hao Zhang ◽  
Yuxiao Zhou ◽  
Yifei Tian ◽  
Jun-Hai Yong ◽  
Feng Xu
Keyword(s):  
Real Time ◽  
Synthetic Data ◽  
Real Data ◽  
Depth Image ◽  
Real Time System ◽  
The Real ◽  
Time Performance ◽  
Contact Constraint ◽  
Object Shapes ◽  
Object Interactions

Reconstructing hand-object interactions is a challenging task due to strong occlusions and complex motions. This article proposes a real-time system that uses a single depth stream to simultaneously reconstruct hand poses, object shape, and rigid/non-rigid motions. To achieve this, we first train a joint learning network to segment the hand and object in a depth image, and to predict the 3D keypoints of the hand. With most layers shared by the two tasks, computation cost is saved for the real-time performance. A hybrid dataset is constructed here to train the network with real data (to learn real-world distributions) and synthetic data (to cover variations of objects, motions, and viewpoints). Next, the depth of the two targets and the keypoints are used in a uniform optimization to reconstruct the interacting motions. Benefitting from a novel tangential contact constraint, the system not only solves the remaining ambiguities but also keeps the real-time performance. Experiments show that our system handles different hand and object shapes, various interactive motions, and moving cameras.

scholarly journals Power Hardware-in-the-Loop: Response of Power Components in Real-Time Grid Simulation Environment

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 593
Author(s):  
Moiz Muhammad ◽  
Holger Behrends ◽  
Stefan Geißendörfer ◽  
Karsten von Maydell ◽  
Carsten Agert
Keyword(s):  
Real Time ◽  
Power Distribution ◽  
Control Strategies ◽  
Power Grid ◽  
Energy System ◽  
Hardware In The Loop ◽  
Distribution Grid ◽  
Compensation Strategy ◽  
Software Environment ◽  
The Real

With increasing changes in the contemporary energy system, it becomes essential to test the autonomous control strategies for distributed energy resources in a controlled environment to investigate power grid stability. Power hardware-in-the-loop (PHIL) concept is an efficient approach for such evaluations in which a virtually simulated power grid is interfaced to a real hardware device. This strongly coupled software-hardware system introduces obstacles that need attention for smooth operation of the laboratory setup to validate robust control algorithms for decentralized grids. This paper presents a novel methodology and its implementation to develop a test-bench for a real-time PHIL simulation of a typical power distribution grid to study the dynamic behavior of the real power components in connection with the simulated grid. The application of hybrid simulation in a single software environment is realized to model the power grid which obviates the need to simulate the complete grid with a lower discretized sample-time. As an outcome, an environment is established interconnecting the virtual model to the real-world devices. The inaccuracies linked to the power components are examined at length and consequently a suitable compensation strategy is devised to improve the performance of the hardware under test (HUT). Finally, the compensation strategy is also validated through a simulation scenario.

scholarly journals Home Energy Management for Community Microgrids Using Optimal Power Sharing Algorithm

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1060
Author(s):  
Md Mamun Ur Rashid ◽  
Majed A. Alotaibi ◽  
Abdul Hasib Chowdhury ◽  
Muaz Rahman ◽  
Md. Shafiul Alam ◽  
...  
Keyword(s):  
Energy Storage ◽  
Real Time ◽  
Energy Management ◽  
Cost Minimization ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Power Sharing ◽  
Optimal Power ◽  
Time Operation ◽  
Home Energy Management

From a residential point of view, home energy management (HEM) is an essential requirement in order to diminish peak demand and utility tariffs. The integration of renewable energy sources (RESs) together with battery energy storage systems (BESSs) and central battery storage system (CBSS) may promote energy and cost minimization. However, proper home appliance scheduling along with energy storage options is essential to significantly decrease the energy consumption profile and overall expenditure in real-time operation. This paper proposes a cost-effective HEM scheme in the microgrid framework to promote curtailing of energy usage and relevant utility tariff considering both energy storage and renewable sources integration. Usually, the household appliances have different runtime preferences and duration of operation based on user demand. This work considers a simulator designed in the C++ platform to address the domestic customer’s HEM issue based on usages priorities. The positive aspects of merging RESs, BESSs, and CBSSs with the proposed optimal power sharing algorithm (OPSA) are evaluated by considering three distinct case scenarios. Comprehensive analysis of each scenario considering the real-time scheduling of home appliances is conducted to substantiate the efficacy of the outlined energy and cost mitigation schemes. The results obtained demonstrate the effectiveness of the proposed algorithm to enable energy and cost savings up to 37.5% and 45% in comparison to the prevailing methodology.

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.

Sign in / Sign up

Export Citation Format

Share Document