scholarly journals A Causal and Real-Time Capable Power Management Algorithm for Off-Highway Hybrid Propulsion Systems

Energies ◽  
2016 ◽  
Vol 10 (1) ◽  
pp. 10
Author(s):  
Johannes Schalk ◽  
Harald Aschemann
Keyword(s):  
Real Time ◽  
Power Management ◽  
Propulsion Systems ◽  
Hybrid Propulsion ◽  
Management Algorithm

Real-Time Modeling to Enable Hardware-in-the-Loop Simulation of Plug-In Electric Vehicle-Grid Interaction

2017 ◽  
Author(s):  
Chong Cao ◽  
Luting Wang ◽  
Bo Chen ◽  
Jason Harper ◽  
Theodore Bohn ◽  
...  
Keyword(s):  
Power System ◽  
Real Time ◽  
Electric Vehicle ◽  
Power Management ◽  
Hardware In The Loop ◽  
The Real ◽  
System Models ◽  
Management Algorithm ◽  
Time Modeling ◽  
Building Load

Real-Time simulation and Hardware-in-the-Loop (HIL) testing are increasingly adopted by industry for the development and validation of complex systems. This paper presents the real-time modeling and power management of a Vehicle-Grid Integration (VGI) system. The VGI system consists of six AC level 2 Plug-in Electric Vehicle (PEV) charging stations, a Photovoltaics (PV) farm, a commercial building load, and a switch connecting to 240V single phase power grid. PEV charging activities follow the SAE J1772 standard. An energy management algorithm is designed for the VGI system to coordinate the PEV charging with the building load and PV renewable generation. The coordination maintains the power consumption of the VGI system below utility’s demand charge pricing threshold. A real-time power system simulator, Opal-RT, is used in this study. The OPAL-RT system allows users to build detailed power system models using Matlab Simulink/SimPowerSystems and RT-LAB library, and run the models in real-time. The model-based approach enables the integration of power system models seamlessly with the power management algorithm and power electronics-level controllers. The simulation results show that the VGI model emulates the real system well and the coordinated PEV charging helps to balance the power generation and consumption of the VGI system to meet power management requirement.

Data-Driven Real-Time Decision Support and its Application to Hybrid Propulsion Systems

2017 ◽  
Author(s):  
Karl-Johan Reite ◽  
Jarle Ladstein ◽  
Joakim Haugen
Keyword(s):  
Mathematical Model ◽  
Decision Support ◽  
Real Time ◽  
Data Driven ◽  
Local Minima ◽  
Propulsion Systems ◽  
Hybrid Propulsion ◽  
Fishing Vessels ◽  
Main Engine ◽  
Fuel Consumption And Emissions

This paper describes a method for providing real time decision support based on measurements rather than optimizing a mathematical model. The proposed method is thus beneficial for systems for which the modelling would be inaccurate, the dynamics and complexity of the system would make it difficult to optimize in real time, or the risk of returning local minima is not acceptable. The proposed method is implemented on four fishing vessels. These vessels are complex and give the skipper many choices related to how the vessel is operated. The developed tool advises the crew on in real time on operational decisions, particularly on the use of various diesel electric and diesel mechanic propulsion modes, including decisions such as the use use of shaft generator, direct coupling between main engine and propeller or not, propeller pitch, etc. This will presumably reduce both fuel consumption and emissions of CO2 and NOX. Some examples of obtainable results from both onshore analyses and the onboard application are presented to demonstrate the methods applicability.

Naval Hybrid Power Take-Off and Power Take-In – Lessons Learnt and Future Advances

2018 ◽  
Author(s):  
M Benatmane ◽  
B Salter
Keyword(s):  
Electrical Power ◽  
Maritime Industry ◽  
Propulsion Systems ◽  
Systems Architecture ◽  
Hybrid Propulsion ◽  
Leading Role ◽  
Lessons Learnt ◽  
Marine Industry ◽  
Operational Systems ◽  
Great Pressure

With the ever tightening of budgets and legislation, new vessel builds are facing tough times.  The future maritime industry requires more efficient vessels to minimise ship operational costs with cleaner technologies that meet stringent environment regulations, reduce greenhouse gas emissions, specifically carbon emissions. Emissions reduction continues to be high on the agenda for the marine industry, it is responsible for about 2.5 percent of global greenhouse emissions1 and is under great pressure to reduce its environmental impact. With pressure comes the opportunity to incentivize innovation, developments and implementation of energy efficient measures, both design and operational. Naval propulsion systems are no different from other industries, and the industry is exploring ways to optimise propulsion and electrical power generation systems architecture for better performance and efficiency. Electric technology plays a leading role. The paper will: Provide a brief overview about the hybrid propulsion concept, with key electrical, mechanical qualities and issues. Describe different designs configurations and performances of hybrid propulsion systems from demonstrated and operational systems in the commercial and naval world. Cover the lessons learnt in technologies and controls used on such systems. Examine future architectures including energy storage and explore the benefits and the flexibility these can bringto the hybrid propulsion sphere.

scholarly journals MPC-informed ECMS based real-time power management strategy for hybrid electric ship

2021 ◽  
Vol 7 ◽  
pp. 126-133
Author(s):  
Peilin Xie ◽  
Sen Tan ◽  
Josep M. Guerrero ◽  
Juan C. Vasquez
Keyword(s):  
Real Time ◽  
Power Management ◽  
Management Strategy ◽  
Power Management Strategy ◽  
Electric Ship ◽  
Hybrid Electric

scholarly journals Efficient Prediction of Network Traffic for Real-Time Applications

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Muhammad Faisal Iqbal ◽  
Muhammad Zahid ◽  
Durdana Habib ◽  
Lizy Kurian John
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Power Management ◽  
Dynamic Resource Allocation ◽  
Computation Complexity ◽  
Real Time Traffic ◽  
Double Exponential ◽  
Efficient Prediction ◽  
Dynamic Resource ◽  
Double Exponential Smoothing

Accurate real-time traffic prediction is required in many networking applications like dynamic resource allocation and power management. This paper explores a number of predictors and searches for a predictor which has high accuracy and low computation complexity and power consumption. Many predictors from three different classes, including classic time series, artificial neural networks, and wavelet transform-based predictors, are compared. These predictors are evaluated using real network traces. Comparison of accuracy and cost, both in terms of computation complexity and power consumption, is presented. It is observed that a double exponential smoothing predictor provides a reasonable tradeoff between performance and cost overhead.

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