Capacity configuration optimization is one of the primary tasks in the construction of the integrated energy system (IES). the uncertainties of renewable energy sources and loads deepen the coupling relationship between the capacity configuration and energy dispatching of IES, which makes optimizing the capacity difficult. This paper proposes a two stage GA-MILP-based capacity sizing allocation method for off- grid IES. Firstly, a double-layer capacity configuration framework based on Leader-Follower is constructed. Secondly, the genetic algorithm (GA) is used to randomly generate the initial configuration in the Leader layer and use it as the input of the Follower layer. In the Follower layer, the system investment cost, operation cost, and maintenance cost are comprehensively considered, the mixed integer linear programming (MILP) method is used to obtain the minimum operating cost and energy dispatching scheme and then return to the Leader layer. The optimal capacity configuration scheme is obtained through multiple iterative optimizations. Finally, the proposed method is applied to an Off-grid island to confirm the rationality and effectiveness of the optimization results.

As the main device of aircraft electric propulsion system, the voltage stabilization control of dc-dc converter is crucial to ensure flight safety and energy efficiency. Passivity-Based Control (PBC) relies on exact models. Physics-Informed Neural Network (PINN) lacks stability guarantees. To address these issues, this paper proposed a PINN-PBC algorithm. The algorithm takes the closed-loop dynamics equation of PBC as the explicit constraint term of PINN to construct an end-to-end control architecture. It is able to improve the dynamic response performance while ensuring the large-signal stability of the system. The results show that the output voltage fluctuation is ±1.7% when a large disturbance occurs in the CPL.

For the fuel cell/battery UAV hybrid power system, an energy management strategy(EMS) based on fuzzy logic control(FLC) is proposed in this paper, which is optimized to reduce the system's hydrogen consumption, maintain the state of charge(SOC) of lithium battery, and stabilize the bus voltage. In order to verify the effectiveness of the EMS, a fuel cell UAV hardware experimental platform is built and a finite state machine(FSM) strategy is designed for comparison. Experimental comparison results verify the effectiveness of the proposed fuzzy logic control strategy in stabilizing the bus voltage, maintaining the SOC of the lithium battery, and improving the system fuel economy.

In this paper, a real-time Energy Management Strategy (EMS) based on Particle Swarm Optimization (PSO) and virtual inductor is proposed for hybrid electric Unmanned Aerial Vehicle (UAV) powered by fuel cells and lithium batteries. For comparative analysis, EMS-based Finite-State Machine (FSM) and Dynamic Programming (DP) are also designed in this paper. Though simulating on MATLAB, the results demonstrate that the proposed EMS can effectively reduce the hydrogen consumption of the system, thereby improving fuel economy. Additionally, the EMS smooths the output power of the fuel cell with the aid of the virtual inductor.

Nowadays distribution power systems are used in different applications such as aircraft, ships, submarines and hybrid electric vehicles. However, the interaction between individually designed power subsystems may cause instability. Moreover, in these applications, the constant power load (CPL) also poses challenges for system dynamic response and stability. Thus, the main objective is to stabilize the cascaded system supplying the CPL. An interconnection and damping assignment (IDA) passivity-based control (PBC) scheme for LC filter cascaded with buck converter supplying CPL is proposed. The plant is described by port-controlled Hamiltonian (PCH) form. Particularly, an adaptive interconnection matrix is developed to achieve internal links in PCH system. A modified IDA-PBC and its proof are presented to perfect the implementation for the CPL application. Simulation results are given to illustrate the effectiveness of the proposed approach.

It is well know that the interaction between poorly damped LC input filter with dc-dc converter lead to degradation of dynamic performance and fault scenario of the system. This problem also often occurs in fuel cell systems. Due to the relatively low and unregulated output voltage, the high gain boost converter is need in such application. A floating interleaved boost converter (FIBC) is selected as a good candidate to achieve this desired effect. In order to ensure the system stability, this paper addresses a method which permits to design a fault-tolerant stabilizing system for the proposed converter and the filter. It consists in implementing an active stabilizer for each switch. Afterward, a method to design fault-tolerant stabilizing system is developed. The simulation results are reported to verify the effectiveness of the proposed method.

In the DC distributed power system of the more electric aircraft (MEA), it is necessary to have a LC filter in the input of boost converter due to electromagnetic interference (EMI) and sharp input impulse voltage. Whereas, the interaction between boost converter and poorly damping filter may cause instability throughout the system., The problem may be solved by adding resistor or increasing capacitance, but it also increases the power consumption, volume and weight. However, the volume and weight are important performance indexes in the MEA. In this paper, we will introduce a virtual capacitor to solve the above problem without extra volume and weight. Firstly, the closed-loop control parameters of boost converter are designed by SISOTOOL of MATLAB. Then, the model, which is used to analyze the stability of cascade system with LC filter, is derived based on the Takagi-Sugeno (TS) fuzzy theory, and then a public Lyapunov function is found by (linear matrix inequation) LMI tool of MATLAB to estimate the stability of the system. Finally, the simulation results confirm the validity of the proposed stability analysis and control method.

The electric vehicle technology has been adopting PEM fuel cells for hybrid applications over the past decades. Fuel cell systems are often low voltage systems. The key requirements of a boost converter for such application are need of high-voltage. The second-order low-pass filter is often used to filter the high frequency current ripple. It is known that the interaction between the poorly damped filter with the converter leads to degradation of dynamic performance and instability of the system. This paper addresses a novel wide stability control strategy to solve this problem without increasing the weight and size. In this paper, the mathematical model of the system is built. The dynamic stability of the system is investigated based on root locus and Lyapunov first method. The simulation results are reported to verify the effectiveness of the proposed method.