2. Ship Power System Electric Transient Simulation
Shipping navigation conditions are complex, the environment is harsh and changeable, and a new energy ship power system is vulnerable to uncertain power fluctuation, which reduces the ship’s power transient stability. Transient simulation technology that uses the transient characteristics of electrical equipment to construct a time-domain high-order differential model is a low-cost, flexible, and convenient operation and is essential for ship power design, stability analysis, and protection. Transient simulation technology is also the basis of DT for ship performance in the ship power system. Current ship power system simulation software is not exclusive.
2.1. Electromechanical Transient Simulation
The electromechanical transient simulation calculates the time domain solution for the transient process quantities of power systems by solving a system of differential equations and algebraic equations. Electromechanical transient simulation software is widely used for land grids or equipment-level power simulations, so there are few applications for ship power system simulation. Power system electromechanical transient simulation programs, such as the Power System Simulator/Engineering (PSS/E) software from PTI (USA), the power system synthesis programs Power System Analysis Software Package (PSASP), and Bonneville Power Administration (BPA) power system analysis programs from China, the ABB (Sweden) SIMPOW program, the NETOMAC platform from Siemens, Germany and the DIG-SILENT software from POWERFACTORY
[118,119][5][6] are used.
PSS/E is widely used for the steady-state and dynamic process analysis of transmission and distribution networks or large generating units. It simulates thousands of power lines or generators simultaneously. PSS/E has calculation capability and is compatible with subroutines. Decurrent
By using PSS/E. In 2021, Michael Abdelmalak
[120][7] converted the New York State Large Grid PSS/E model to an RSCAD model for a semi-physical real-time simulation in the RTDS simulator. The results demonstrate that the average simulation error for the bus voltage magnitude between PSS/E and RTDS simulations is 0.271%, the standard deviation is 0.621%, and the maximum deviation is 4%. These results demonstrate the simulation accuracy and robustness of PSS/E.
PSASP software has a primary grid database, a fixed model base, and a user-defined model base to simulate various power systems. PSASP allows users to build self-defined models without complex program codes and simulates various new electrical components and automatic control devices. In 2020, Wang
[121][8] used PSASP to simulate the black start process for a thermal generator in Vida Bay Industrial Park, Indonesia. The parameters for a diesel governor and an automatic regulator were debugged to determine the effect of the parameters on the power system’s transient stability. The results of the experiments show that the PSASP simulation approaches actual operating conditions.
Power System Department-Bonneville Power Administration (PSD-BPA) is a power system analysis software that was developed by the BPA in the 1960s
[122][9]. BPA terminated the development and maintenance of the PSD-BPA transient stability program in 1996, and now PSD-BPA is only serviced by the China Electric Power Research Institute.
2.2. Electromagnetic Transient Simulation
The electromagnetic transient simulation uses numerical calculation methods to simulate electromagnetic transient processes for power systems from a few microseconds to several seconds. Electromagnetic transient simulation software is widely used for ship power systems. Electromagnetic transient programs (EMTP) have been developed by many countries. The China Electric Power Research Institute proposed an EMTPE that uses EMTP
[123][10]. Similarly, EMTDC/PSCAD (Electromagnetic Transients including DC/Power Systems Computer Aided Design) was developed by the Manitoba DC Research Centre in Canada
[124][11]. Microtran was developed by Columbia University in Canada, and NETOMAC was developed by Siemens
[125,126][12][13].
PSCAD/EMTDC/PSCAD was completed in Canada in 1976 and is used worldwide with PSCAD as the user interface. The successful development of PSCAD allows EMTDC to be used for power system analysis. EMTDC simulates any size of AC/DC systems and over-voltage faults, short circuits, and open circuits
[127][14].
In 2020, Wu
[128][15] constructed a ship cyber-physical co-simulation platform that uses a High-Level Architecture (HLA) framework. The co-simulation of shipboard power systems and information networks is accomplished using OPNET HLA using custom modules for simulation. The transmission delay when a fault occurs is 200–1000 µs. In 2020, Lin developed a mathematical model of a ship DC bus and propulsion motor load using a PSCAD hybrid simulation and hardware-in-the-loop testing. The study defined flexible energy scheduling and the virtual inertia of IPS
[129][16]. A flexible energy scheduling algorithm was used to control the propulsion motor load and the pulse load to mitigate the effect of the pulse load on the IPS system. In the simulation experiment, the PSCAD simulation step was 20 μs. The maximum fluctuation in the propulsion motor power is 1.5 MW and the effective value for the bus voltage is 4950 V~5050 V. PSCAD simulation models simulate the operating conditions of a ship power system.
In 2018, Feng
[130][17] proposed a Multi-intelligent Agent System (MAS) that uses decentralized collaborative controllers. The PSCAD simulation results for a dual-zone all-electric ship power system demonstrate that the system frequency decreases to 59.4 Hz when a 10% load (0.4 MW) is disconnected. A UFLS algorithm was developed to adjust the load to restore the frequency of the ship power system. In 2015, Sun
[131][18] developed a simulation model for a PV ship power system (PSPS) that uses a PSCAD/EMTDC platform.
The transient characteristic of PSPS, such as the fault transient process, when a shipboard PV system is connected to the primary grid was studied. A PQ control strategy was used for the PSCAD model to control a shipboard PV generation system and synchronous generators. The transient simulation results show that the PV generation system has little effect on a single-phase fault.
An Electro-Magnetic Transient Program/The Alternative Transients Program (EMTP/ATP) was developed by Prof. H.W. Dommel in Canada, and featured multiple analysis functions, complete component models, and accurate calculation results. ATP is a free, stand-alone version of EMTP and is one of the most widely used EM transient analysis programs to simulate complex networks and control systems.
In 2021, J.J. Deroualle
[132][19] presented a dual-circuit modeling of an EMTP-ATP time-domain simulation to determine the ability to protect a marine power system with a DC bus. The advantages and limitations of two DC fault methods, fuel cells and battery power for DC structures, are discussed. Their use for feeder protection with high-speed fuses in DC was also studied. The EMTP-ATP time-domain fault comparison results were used to derive time-current curves for 400 A-rated fuses. Two EMTP-ATP circuit models eliminated the fault in less than 10 ms, which demonstrates the effectiveness of the protection components.
Simulink is a visual simulation tool that was developed by Mathworks y. It is a multi-domain model-based simulation software that supports the functions of system design, simulation, automatic code generation, and continuous testing and verification of embedded systems. Simulink has graphical editors, customizable module libraries, and model solvers. Simulink is used in the automotive, aerospace, and industrial automation industries and for large-scale modeling, complex logic, physical logic, and signal processing.
In 2020, Yan
[133][20] developed a ship energy efficiency model for a 53,000 GT Chinese coastal bulk carrier that uses Monte Carlo simulation methods and Simulink software. The designed model has sufficiently high accuracy to simulate ship energy efficiency considering the consideration of stochastic effects of cargo loading, ship speed, and various natural environments. The energy efficiency operating index for a ship has increased by about 6.44%.
In 2019, Samy Faddel
[134][21] simulated an intelligent power coordination algorithm using Simulink that mitigates the effect of pulse loading and ensures power sharing between different storage units. The proposed decentralized coordination strategy for the shipboard hybrid energy storage system does not require a link with other system components, unlike a conventional strategy. To ensure power sharing in the ship power system, the initial SOCs for the batteries are 70% and 25%, and the supercapacitor is 50%.
In 2022, Hyun-Keun Ku
[135][22]. presented a medium voltage DC power system Simulink model for the analysis of an all-electric ship (AES). The proposed model has mechanical and power systems. The effectiveness of the developed individual AES model and the integrated AES model was verified for different ship operating conditions. In 2019, Tien Anh Tran
[136][23] used the Energy Efficiency Operational Indicator as a monitoring tool to establish an improved numerical model of the energy-efficient operation condition of a large ship’s main engine using different navigational environments in Simulink. The simulation value for wave resistance varies from 180 kN to 0 for different ship speeds, and the theoretical calculation value varies from 250 kN to 30 kN. In 2017, Kyunghwa Kim
[137][24] simulated a hybrid power system for a medium-sized container ship using Simulink software to determine the optimal allocation of shipboard ESS. The CO
2 emissions for the proposed planning scheme are reduced by 8.6% to 20.7% compared to a traditional ship power system.
3. Ship Power System DT
DT technology
[138][25] involves multi-disciplinary knowledge, coupled simulation of multiple physical fields, and multi-time scale data interchange. DT uses historical data, and real-time data that are measured by sensors to map physical entities to virtual entities
[139][26]. It allows real-time operation and is very accurate. Simulation technology and deep learning algorithms are used for DT. Ship DT technology uses operational data and environmental data to mine hidden information from data and to determine an optimum O&M strategy. DT also allows better fault detection and increases the operating efficiency of new energy ships.
A new energy ship power system DT requires electrical parameters for equipment, operating data for the power system, ship attitude data, and meteorological data for the route. Ship DT considers the effect of the navigation environment on the power system of new energy ships. In 2019, Andrea Coraddu
[140][27] proposed a ship DT model that uses sensor data to determine the effect of ship speed on polluting emissions. Tests on two Handymax tankers showed the effectiveness of the proposed model. Ícaro Aragão
[145][28] Fonseca used ship DT to simulate a scale model ship with a dynamic positioning system in an artificial pool in 2022. An advanced version of ship DT software uses experimental results to increase the capacity for motion responses for a ship.
New energy ships have a more complicated power system than traditional ships and additional electrical equipment, so ship power system faults are more complex and difficult to solve. DT analyzes complex faults to decrease the failure rate for new energy ships. In 2021, Wu
[141][29] determined the effect of DT on the intelligent manufacturing of ships. The study assumes that a ship DT framework consists of a physical layer, a modeling layer, a data layer, a system layer, and an application layer. In 2021, Andrew Wunderlich
[142][30] verified that DT must be used for power and energy management in all-electric warships. The study demonstrates various simulation technologies for DT modeling and proposes a DT model of a boost converter that uses a mixed modeling method for a shipboard microgrid. Wang
[143][31] studied the drive process for ship DT for marine engine systems and marine containers in 2022. The study constructed a ship DT model using Maya modeling technology and Unity 3D scene rendering. A Bayesian neural network was used to fuse multi-source heterogeneous data in a virtual simulation layer and a data layer. The Ship DT model was used to forecast cabin temperature with only a 5.22% MPD error. Li
[144][32] proposed a DT-based quality prediction and control method to eliminate the lag in ship assembly welding and increase the prediction accuracy in 2022. The proposed method predicts and controls the performance of Ship Group Products (SGP). The method uses physical assembly and welding equipment, virtual assembly and a welding model, a prediction and control system, and digital data. In 2022, Eric VanDerHorn
[145][28] used global vessel position data and metocean hindcast data instead of missing fatigue measurement data and used ship DT to simulate the 7-year operation of a container ship to calculate ship fatigue time.
The capital cost of new energy ships is greater than that of traditional ships, but the operating cost is less. New energy ships with DT technology have long-term economic benefits. Ship DT reduces the cost of ship design, manufacture, and O&M. DT also processes the ship and environment information in real-time for the entire life cycle of new energy ships to self-tune the model. In 2021, Jan-Erik Giering
[146][33] studied ship DT from the perspective of the ship life cycle and defined Maritime DT Architecture (MDTA). In 2022, Xiao
[147][34] defined the whole life cycle of a ship to include design, manufacture, operation, maintenance, and scrapping. Information islands are caused by the “One Stage Analysis” of a ship. Xiao proposed a ship design framework that uses DT with historical experience and real-time data. A ship DT model can evolve and be used to predict each stage of the ship’s life cycle. In 2021, Lan developed DT software for a ship power system. The software allowed online monitoring and transmission, ship power system health management, and intelligent dispatching functions and was applied to a 25-m all-electric propulsion research vessel. In 2022, Zhang
[148][35] discussed the development of the shipping industry. Ship DT simulates various operating conditions and generates twin data to generate optimum strategies for ship controlling and scheduling. The study performed full-scale ship docking experiments using ‘Gunnerus,’ which is a Norwegian research vessel, to verify the effectiveness of the ship DT system.
DT technology has been widely applied in new energy ships. Ship DT is an important component in the technology system of new energy ships, but it is still in the exploratory stage. Ship DT urgently requires an efficient open-source software platform to quickly unite different simulation systems. A reasonable technical framework for ship DT is also necessary to be proposed to achieve reliable, low-carbon, and intelligent operation and maintenance.
4. Summary
Ship electric transient simulation technology needs a lot of manpower and material resources to establish models and tune parameters. Ship electric transient simulation technology is always realized on commercial closed-loop software, which means that it is difficult to establish a real-time data interaction channel among multiple electric transient models. The development from ship electric transient simulation technology to ship DT technology has increased the efficiency of marine electrical research. DT allows the monitoring and detection of ship electric systems to optimize control and prediction. DT is used for all phases of the entire life cycle of new energy ships to increase the accuracy of the model and reduce the experimental cost and the length of the research cycle. A ship DT model contains multi-physical field and multi-source data and prediction technology and accurately predicts the new-energy power output on a ship and generates the optimal strategy for ship power scheduling. Ship DT technology allows better and faster transformation and development of new energy ships. DT technology has developed from real-time to predictive operation. Increased real-time data interaction, fast prediction, and high simulation accuracy are development goals.