Optimal power management for electric tugboats with unknown load demand

Vu, Thanh Long; Dhupia, Jaspreet Singh; Ayu, Aaron Alexander; Kennedy, Louis; Adnanes, A.K.

doi:10.1109/acc.2014.6859004

Cited by 18 publications

(11 citation statements)

References 9 publications

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“…The integrating element of a rechargeable energy storage with capacity limits brings a time aspect to the problem. Vu et al (2014aVu et al ( ,2014bVu et al ( ,2015 presented variations of a power management optimisation method using a series hybrid tugboat. The penalty function included elements for fuel consumption, load demand tracking and changes in battery energy.…”

Section: Power Management Optimisation Makes the Best Use Of Existingmentioning

confidence: 99%

Optimising design and power management in energy-efficient marine vessel power systems: a literature review

Jaurola

Hedin

Tikkanen

et al. 2018

Journal of Marine Engineering & Technology

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The conventional marine vessel power systems typically have the potential to improve their fuel consumption and their emissions. This can be done by redesigning the system configuration, the machinery and the power management strategy. The addition of options in power management allows for the running of individual power sources closer to their optimal operating point. However, this immediately raises questions about how to redesign the system and how to operate it to maximise the benefits. The information needed to answer these questions is often scattered around separate sectors of the marine industry. The system integrator needs to be able to combine the complex dependencies of these individual sectors to formulate the big picture that describes the whole power system. Numerical optimisation algorithms provide solutions to develop methodologies to solve multi-variable and potentially multi-objective problems. This literature review presents the authors' findings of design and power management optimisation cases in marine vessel power systems. ARTICLE HISTORY

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Section: Power Management Optimisation Makes the Best Use Of Existingmentioning

confidence: 99%

Optimising design and power management in energy-efficient marine vessel power systems: a literature review

Jaurola

Hedin

Tikkanen

et al. 2018

Journal of Marine Engineering & Technology

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“…We neglect the intermediate dynamic process, and establish the real-time fuel consumption model relating the fuel consumption rate to the output power. Assuming that there are X diesel engines in the hybrid ship, the fuel consumption in the diesel engines in time interval [0, T] can be expressed as [13,14]:…”

Section: Fuel Consumption Modelmentioning

confidence: 99%

An Energy Optimization Strategy for Hybrid Power Ships under Load Uncertainty Based on Load Power Prediction and Improved NSGA-II Algorithm

Gao

Wang

et al. 2018

Energies

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In this paper, a hybrid ship powered by diesel generator sets and power batteries in series is considered. By analyzing the characteristics of hybrid ship cycle operating conditions, the load power of the hybrid ship under load uncertainty is firstly predicted. Then, considering the economy, emissions and continuous navigation time (endurance) of the hybrid ship, an energy optimization strategy based on the predicted load power is proposed to achieve the goal of minimum fuel consumption, minimum emissions and maximum endurance of ship operation. The experimental results show that, compared with the fuzzy logic rules based strategy, the fuel economy of the ship is increased by 9.6% and the ship's endurance is increased by 24% for the proposed strategy.

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“…A novel prediction scheme, which requires only the information regarding the general characteristics of tugboat operation, is proposed to forecast the load demand, and then combined with the optimization formulation presented in Section II to determine the engine and battery power outputs and the engine operation schedule. The preliminary work done on prediction scheme was presented in [13]. Improvements have been made in prediction algorithm and its combination with the optimization formulation.…”

Section: Unknown Load Demandmentioning

confidence: 99%

Power Management for Electric Tugboats Through Operating Load Estimation

Ayu

Dhupia

et al. 2015

IEEE Trans. Contr. Syst. Technol.

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This brief presents an optimal power management scheme for an electromechanical marine vessel's powertrain. An optimization problem is formulated to optimally split the power supply from engines and battery in response to a load demand, while minimizing the engine fuel consumption and maintaining the battery life, wherein the cost function associates penalties corresponding to the engine fuel consumption, the change in battery's state of charge (SOC), and the excess power that cannot be regenerated. Utilizing the nonlinear optimization approach, an optimal scheduling for the power output of the engines and optimal charging/discharging rate of the battery is determined while accounting for the constraints due to the rated power limits of engine/battery and battery's SOC limits. The proposed optimization algorithm can schedule the operation, i.e., starting time and stopping time for a multiengine configuration optimally, which is a key difference from the previously developed optimal power management algorithms for land-based hybrid electric vehicles. Afterward, a novel load prediction scheme that requires only the information regarding the general operational characteristics of the marine vessel that anticipates the load demand at a given time instant from the historical load demand data during that operation is introduced. This prediction scheme schedules the engine and battery operation by solving prediction-based optimizations over consecutive horizons. Numerical illustration is presented on an industry-consulted harbor tugboat model, along with a comparison of the performance of the proposed algorithm with a baseline conventional rule-based controller to demonstrate its feasibility and effectiveness. The simulation results demonstrate that the optimal cost for electric tugboat operation is 9.31% lower than the baseline rule-based controller. In the case of load uncertainty, the prediction-based algorithm yields a cost 8.90% lower than the baseline rule-based controller.Index Terms-Hybrid electric vehicle (HEV), load estimation, marine powertrain, marine vessel, optimization, power management.

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Optimal power management for electric tugboats with unknown load demand

Cited by 18 publications

References 9 publications

Optimising design and power management in energy-efficient marine vessel power systems: a literature review

Optimising design and power management in energy-efficient marine vessel power systems: a literature review

An Energy Optimization Strategy for Hybrid Power Ships under Load Uncertainty Based on Load Power Prediction and Improved NSGA-II Algorithm

Power Management for Electric Tugboats Through Operating Load Estimation

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