MPC-based power management in the shipboard power system

Paran, S.; Vu, Tuyen; Mezyani, T. El; Edrington, Chris S.

doi:10.1109/ests.2015.7157855

Cited by 29 publications

(17 citation statements)

References 24 publications

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“…Applying this method leads to a straightforward lookup table method which cannot necessarily lead to an optimal solution. Particle Swarm Optimization (PSO) algorithm is utilized in [13] for energy management of the shipboard loads. Hou et al [14] solve the optimal energy management of a hybrid energy storage system for tracking the energy fluctuations of the shipboard loads.…”

Section: Introductionmentioning

confidence: 99%

An Efficient and Cost-Effective Power Scheduling in Zero-Emission Ferry Ships

et al. 2020

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Today’s remarkable challenge of maritime transportation industry is the detrimental contamination generation from fossil fuels. To tackle such a challenge and reduce the contribution into air pollution, different power solutions have been considered; among others, hybrid energy-based solutions are powering many ferry boats. This paper introduces an energy management strategy (EMS) for a hybrid energy system (HES) of a ferry boat with the goal to optimize the performance and reduce the operation cost. HES considered for the ferry boat consists of different devices such as proton exchange membrane fuel cell (PEMFC), LI-ION battery bank, and cold ironing (CI). PEMFC systems are appropriate to employ as they are not polluting. The battery bank compensates for the abrupt variations of the load as the fuel cell has a slow dynamic against sudden changes of the load. Also, CI systems can improve the reduction of the expenses of energy management, during hours where the ferry boat is located at the harbor. To study the performance, cost and the pollution contribution CO2, NOX, SOX of the proposed hybrid energy management strategy (HEMS), we compare it against three various types of HEM from the state-of-the-art and also available rule-based methods in the literature. The analysis results show a high applicability of the proposed HES. All results in this paper have been obtained in the MATLAB software environment.

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Section: Introductionmentioning

confidence: 99%

An Efficient and Cost-Effective Power Scheduling in Zero-Emission Ferry Ships

et al. 2020

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“…To quantify this difference, this paper compares the unserved load with and without future knowledge. Power systems require some form of controller Paran et al (2015); Vu et al (2017), but rather than design a controller for every case an optimization process is used that mimics the behaviour of an ideal controller. Herein, two types of optimization methods are used to generate controller behavior.…”

Section: Introductionmentioning

confidence: 99%

The role of future information in control system design for shipboard power systems

Opila

Stevens

Cramer

2018

Proceedings of the International Ship Control Systems Symposium (iSCSS)

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Both naval and commercial ships are incorporating new power and energy system technologies to improve fuel economy and performance while servicing high power pulsed loads. These assets can be best utilized with load demand forecasting and/or prediction, especially when considering limits on generator ramp rates, distribution lines, and energy storage capacity. Obtaining future load demand data and designing a controller to accommodate it can be challenging, but with potentially large payoff. However, this information is not useful in all cases. This paper develops a method to quantify the potential value of future information depending on the specific power system characteristics. This quantitative approach aids designers in deciding how and when to deploy future forecasting in controller design, and provides insight into the potential benefits of these more complex controllers. To quantify this trade off, two optimization-based control methods are developed. One uses only current information, while the other has an exact forecast of the future. As examples, the method is applied to a notional naval ship and drill platform service vessel with representative power and energy system architectures under indicative operational load demands.

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“…Among those, the energy management problem for ship power systems has been addressed utilizing a predictive control strategy [12]- [18]. [12] presented an energy management scheme for a system that incorporates two generators. However, ES was not included and no high power ramp rate operations are discussed in the paper.…”

Section: Introductionmentioning

confidence: 99%

Predictive Control for Energy Management in Ship Power Systems Under High-Power Ramp Rate Loads

Gonsoulin

Diaz

et al. 2017

IEEE Trans. Energy Convers.

106

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Abstract--Electrical weapons and combat systems integrated into ships create challenges for their power systems. The main challenge is operation under high-power ramp rate loads, such as rail-guns and radar systems. When operated, these load devices may exceed the ships generators in terms of power ramp rate, which may drive the system to instability. Thus, electric ships require integration of energy storage devices in coordination with the power generators to maintain the power balance between distributed resources and load devices. In order to support the generators by using energy storage systems, an energy management scheme must be deployed to ensure load demand is met. This paper proposes and implements an energy management scheme based on model predictive control to optimize the coordination between the energy storage and the power generators under high-power ramp rate conditions. The simulation and experimental results validate the proposed technique in a reduced scale, notional electric ship power system. Index Terms-Ship power systems, DC microgrids, energy management, power control, and predictive control. NOMENCLATURE

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MPC-based power management in the shipboard power system

Cited by 29 publications

References 24 publications

An Efficient and Cost-Effective Power Scheduling in Zero-Emission Ferry Ships

An Efficient and Cost-Effective Power Scheduling in Zero-Emission Ferry Ships

The role of future information in control system design for shipboard power systems

Predictive Control for Energy Management in Ship Power Systems Under High-Power Ramp Rate Loads

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