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Objectives Aiming at the distributed hybrid energy storage system (HESS) in the shipboard integrated power system（IPS）, a multi-HESSs collaborative control method based on the state of charge (SOC) of the energy storage device (ESD) was proposed to achieve the relative consistency among multi-HESSs and the reasonable power distribution between supercapacitor and battery within a single HESS.Methods The droop control method will be adopted in the outer control loop of a single HESS to realize the initial power distribution, while the master-slave control mode will be adopted in the inner control loop to reduce the communication demand among multi-HESS's. Given the characteristics of a fast dynamic response but the small capacity of supercapacitor and large capacity of battery, the SOC value of the supercapacitor is calculated to obtain the output power of the battery within a single HESS. Between multi-HESSs, the total charging/discharging power of each HESS unit is calculated based on the SOC value of the internal battery.Results Through the simulation of PSCAD/EMTDC, the discharge response characteristics of multi-HESSs under high energy load switching and random fluctuation conditions are verified. Under the charge-discharge mode transformation condition, the bus voltage fluctuation is within the allowable range of 2.5%. The SOC of a supercapacitor is controlled between the upper and lower limits, and the SOC consistency of two supercapacitor units is maintained. In both charging and discharging modes, lithium batteries operate only when the supercapacitor is limited.Conclusions On the premise of not depending on the high-low pass filter unit, the multi-HESS's collaborative control method has better bus voltage stability and strong robustness.

Objectives With the wide application of energy management system (EMS) networks in shipboard power systems, their non-ideal characteristics have a growing effect on the system performance. To analyze the close-coupling feature of the two systems, a cyber-physical co-simulation method that combines information network and power system simulation is proposed.Methods Using OPNET and Matlab/Simulink as an information network and power system simulator respectively, the software data exchange interfaces and co-simulation synchronization method are proposed based on a uniform co-simulation framework. A co-simulation model of two synchronous generators running in parallel with load is built, and the effect of EMS information network characteristics including link latency and background traffic on secondary power distribution is studied.Results Simulation results indicate that after adding link latency (2 and 5 ms), the total latency of the control process is around 12 and 30 ms. The fixed latency on network links significantly affects the response of the power system. When network links are overloaded by background traffic, the packet latency and system closed loop control latency will increase, the system will diverge after a certain period.Conclusions The proposed method provides an effective simulative method for future research on shipboard close-coupling EMS information network and power system.

Objectives In order to accumulate a ship's comprehensive power big data resources, especially in the case of relatively limited ship computing resources, and realize the effective compression of large-scale historical data, an improved revolving door data compression algorithm is proposed in this paper.Methods According to the real-time data characteristics of a ship's Integrated Power System (IPS), the data compression accuracy index is introduced, and the deviation between the expected error and actual decompression error is used for negative feedback in order to dynamically adjust the compression deviation ?E and reduce the setting difficulty of the compression deviation ?E. Data series with different characteristics are tested in this paper.Results The results show that the proposed algorithm can meet the data compression accuracy of the typical integrated power service of a ship, and maintain a high compression ratio on the premise of ensuring accuracy. The compression rate of the algorithm can reach 1/10-1/5 of the initial data.Conclusions The data compression algorithm in this paper has better compression precision and compression ratio, and can effectively improve the storage efficiency of a ship's historical comprehensive power data.

This paper investigates the small-signal stability of a DC shipboard power system (SPS) with the integration of a supercapacitor. As an efficient energy storage solution, supercapacitors can not only provide rapid energy response to sudden power demand spikes, effectively mitigating load fluctuations, but also enhance the system's resilience to disturbances. In the context of the parallel operation of two Permanent Magnet Synchronous Generators (PMSGs), the inclusion of supercapacitors may alter the system's dynamic behaviors, thereby affecting its small-signal stability. This paper develops the small-signal model of SPS and explores the small-signal model under various power distribution strategies in the parallel operation of diesel generator sets. Through the calculation of eigenvalues and influence factors, the system's oscillation modes are analyzed, and key parameters affecting the stability of the DC distribution system are identified. Furthermore, this paper meticulously examines the specific impacts of electrical and control parameter variations on the system's small-signal stability. Simulation experiments validate the accuracy of the small-signal stability analysis after supercapacitor integration into SPS. [ABSTRACT FROM AUTHOR]

In instances where vessels encounter impacts or other factors leading to communication impairments, the status of electrical equipment becomes inaccessible through standard communication lines for the controllers. Consequently, the shipboard power system enters the partial observable state. Failure to timely ascertain and respond to the current state of the shipboard power system with appropriate restorative controls can result in irreversible damages to the electrical infrastructure and potentially precipitate a complete systemic failure. In this paper, an innovative fault-tolerant control and state estimation approach is proposed to address the partial observability problem of shipboard power systems, based on distributed control architecture and hybrid automata modeling, where controllers are unable to fully acquire equipment status due to device failures like sensor malfunctions. This approach infers the overall state of subsystems using data from intact equipment and discrete events from circuit breakers. Through fault-tolerant control techniques, it ensures that the subsystem state avoids invalid regions, effectively preventing the system from entering unhealthy operational states and significantly reducing the risk of performance degradation or systemic collapse due to faults. Simulation results confirm that this approach can quickly and accurately estimate the system's current state under partial observation, enabling subsequent fault recovery strategies to accurately pinpoint fault locations and identify optimal recovery solutions. [ABSTRACT FROM AUTHOR]