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The hybridization of power systems offers the low-emission and energy-efficient marine vessels. However, it increases the complexity of the power system. Design, analysis, control, and optimization of such a sophisticated system require reliable and efficient modeling tools to cover a wide range of applications. In this work, a typical DC hybrid power system model is developed using a bond graph modeling approach. Necessary component models of varying degrees of fidelity are developed and integrated to build a system model with reasonable accuracy. The developed system model, along with the rule-based energy management system, is used to simulate the entire system and to investigate the load-sharing strategies as well as the system stability in various operating scenarios. Moreover, the simulation results are validated with experimental results conducted on a full-scale laboratory setup of the DC hybrid power system and with a ship load profile. The results show that the system model is capable of capturing the fundamental dynamics of the real system. The hybrid power system model is further used to analyze the bus voltage deviation from its nominal value. The computational efficiency presented by the system is fairly good as it can simulate faster than real-time. The developed system model can be used to build up a comprehensive simulation platform for different system analysis and control designs. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

The electrical power system in ships can be traced to the 1880s, when lightbulbs were installed on SS Columbia. Since then, electricity has been a crucial part of marine vessels. Research and development initiatives resulted in innovations including the ac motor and transformer, turboelectric power, submarines, dieselelectric propulsion, modern solidstate power electronics, the use of liquified natural gas (LNG) as fuel, and pure electric and hybrid ferries with pluggedin and wireless charging from shore.

With the increasing in frequency, intensity, and side effects of grid outages caused by weather based events, the importance of resiliency is also increased. This study presents a novel multi-objective optimization problem for improving the resilience of smart grid against natural disasters in the presence of a considerable amount of line outages occurring due to the weather conditions. The proposed model considers the management of distributed energy resources (DERs), energy storages (ESs), and dynamic topology reconfiguration of the distribution network. The main goal is based on a dynamic resilient operational planning using prediction of weather condition. The objectives in the proposed approach are defined as: to minimise operational cost of distribution network from the system operator's viewpoint, to minimise the penalty costs for energy not supplied and side effects of outages, and to maximise benefits of DER-ES owners by using flexible reconfiguration and dynamic operational planning considering weather conditions. A hybrid optimization algorithm based on genetic algorithm and -constraint method using fuzzy decision maker is employed to choose the best solution from a provided Pareto optimal set. The outcome of the Pareto solution specifies the best scheduling for DERs, ESs and switching of lines during the scheduling horizon.

The electrification of a ship power-train is growing at a fast pace to improve efficiency and reduce emissions. The implementation of new technologies requires test and validation using various modeling approaches. However, many of the existing models of the ship hybrid power system are too complicated and demand high computational requirements, which make them inappropriate for the real-time applications. The real-time simulation model offers the benefits of testing different control algorithms along with hardware-in-the-loop testing. The bond graph-based dynamic modeling of a ship hybrid power system with a DC grid is presented as applicable to real-time simulation. The overall system model is established using different component models with varying fidelity, so-called mixed-modeling approach. In this approach, the components and control functions are modeled with different complexity such that it can capture the necessary system dynamics while minimizing the computational time. Results show that the modeled system is capable of simulating different operating strategies of the hybrid power system. Moreover, the mixed-modeling approach has enabled the system to simulate in nearly 2.5 times faster than the real-time. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

International shipping contributes to a major portion of global emissions. This is expected to grow at a faster pace due to economic and population growth. According to the Third Greenhouse Gas (GHG) Study 2014 of the International Maritime Organization (IMO), the total shipping emissions during 2007-2012 were 3.1% of global CO2 emissions, 2.8% of global CO2-equivalent (CO2e) emissions, 13% of global sulfur oxide (SOX) emissions, and 15% of global nitrogen oxide (NOX) emissions. Further details are given in Table 1.

The conventional $RC$ -lumped thermal networks are widely used to estimate the temperature of power devices, but they lack of accuracy in addressing detailed thermal behaviors/couplings in different locations and layers of the high-power insulated gate bipolar transistor (IGBT) modules. On the other hand, a finite-element (FE)-based simulation is the other method, which is often used to analyze the steady-state thermal distribution of IGBT modules, but it is not possible to be used for a long-term analysis of load profiles of power converter, which is needed for reliability assessments and better thermal design. This paper proposes a novel 3-D $RC$ -lumped thermal network for the high-power IGBT modules. The thermal coupling effects among the chips and among the critical layers are modeled, and boundary conditions, including the cooling conditions, are also considered. It is demonstrated that the proposed thermal model enables both accurate and fast temperature estimation of high-power IGBT modules in the real loading conditions of the converter while maintaining the critical details of the thermal dynamics and thermal distribution. The proposed thermal model is verified by both the FE-based simulation and the experimental results.

A basic challenge in the insulated gate bipolar transistor (IGBT) transient simulation study is to obtain the realistic junction temperature, which demands not only accurate electrical simulations but also precise thermal impedance. This paper proposed a transient thermal model for IGBT junction temperature simulations during short circuits or overloads. The updated Cauer thermal model with varying thermal parameters is obtained by means of finite-element method (FEM) thermal simulations with temperature-dependent physical parameters. The proposed method is applied to a case study of a 1700 V/1000 A IGBT module. Furthermore, a testing setup is built up to validate the simulation results, which is composed of a IGBT baseplate temperature control unit, an infrared camera with a maximum of 3 kHz sampling frequency, and a black-painted open IGBT module.

In this paper the degradation evolution and distribution in high power IGBT module interconnects are investigated. Modules are subjected to advanced active thermal cycling by applying a sinusoidal current load switched by the device. A series of samples subjected to an increasing number of power cycles under conditions resembling real life operation are considered. Under the given load conditions the dominating failure mechanisms are bond wire lift-off and metallization reconstruction. Both failure processes are investigated using micro-sectioning approach and scanning electron microscopy combined with focused ion beam milling. The degradation evolution and distribution are analysed and discussed in relation to load conditions. It is clear that both bond wire lift-off and metallization reconstruction are complicated micro-structural processes affected by numerous stressors. Especially, the fractures causing bond wire lift-off are observed to consist of several sub-phases—delamination, intergranular, and transgranular crack propagations.

Power semiconductor devices are the most fragile components limiting reliability of power converters, where major stresses are temperature dependent parameters. Typically, the operating virtual maximum junction temperature is specified by a manufacturer for each individual device. The thermal system and operating load are designed based on this number. Online monitoring of an on-state collector–emitter voltage (υce,on) and a junction temperature is necessary to ensure the design performance within a safe limit and also to make this method applicable for derating/uprating power. This paper presents the real time measurement of υce,on and thereby the junction temperature estimation in high power converters. Knowing these parameters online, the maximum power capability can be detected. The operating maximum junction temperature is selected and thereby based on the operating condition the derating of power is shown for a megawatt (MW) converter. An experimental setup including online monitoring is described and the measurement of power derating is presented at the specified conditions.