In order to coordinate multiple power sources appropriately, and avoid the transients and rapid changes of power demand, a power management strategy based on an adaptive droop control, which is combined with a multimode strategy and an equivalent consumption minimization strategy, is proposed for a large-scale and high-power hybrid tramway. According to the hybrid system model of tramway developed with commercially available devices, the proposed power management strategy is evaluated with a real driving cycle of tramway. The results obtained from RT-LAB platform testify that the proposed strategy is able to manage and coordinate multiple power sources based on their natural characteristics, maintain dc bus voltage stabilization, improve the efficiency of overall tramway, and alleviate the stress on the hybrid power system.

This paper introduces a state machine control based on equivalent consumption method for fuel cell/supercapacitor hybrid tramcar is proposed. By the effective combination with state machine, the coordinate control of multiple power sources enhances the performance of equivalent consumption minimization strategy, increases the fuel cell operating time in a range of high efficiency and reduces the fluctuation of fuel cell. Moreover, the proposed approach can effectively reduce the hydrogen consumption and keep the SOC of supercapacitor at a reasonable level. By constructing the RT-LAB semi-physical hardware platform, this method is compared with state machine strategy and equivalent consumption minimization strategy. The hydrogen consumption of the proposed method is reduced by 4.18% compared with the state machine strategy, and reduced by 0.56% compared with the equivalent consumption minimization strategy. Then, the result demonstrates the proposed method has better performance. Hence, this new method will have a good application prospect in high-power hybrid tramway.

Efficient and stable operation (ESO) of the proton exchange membrane fuel cell (PEMFC) system is challenging because the nonlinearity of system not only aggravates the difficulty of performance analysis but also puts forward higher requirements for controller design. In this article, a hierarchical performance enhancement control strategy (HPECS) is proposed, which can deal with optimal trajectory seeking under multiobjective constraints and nonlinear problem of system separately. In upper optimization level, the multiobjective optimization based on dynamic adjustment of weighting factor is proposed to seek optimal trajectory for ESO of PEMFC system considering the harm of oxygen starvation, oxygen saturation to system, and contradiction characteristic between net power and efficiency; in lower control level, a data-driven constraint adaptive predictive control is proposed for optimal trajectory tracking with the nonlinearity of system. The proposed HPECS is implemented and validated on the experimental PEMFC system. The comparative studies show that the proposed HPECS is superior in performance enhancement, disturbance rejection, and tracking ability. The normalized multiobjective optimization function can be basically guaranteed to above 0.9, and a nearly 7.2% enhancement in average can be also observed, which shows that ESO of PEMFC system can be achieved in changeable working conditions under proposed HPECS.

For the sake of coordinating multiple energy sources appropriately from power demand and guarantee stage of charge (SOC) consensus of the energy storage systems in different operation conditions, a multisource coordination energy management strategy based on self-convergence droop control is proposed for a large-scale and high-power hybrid tramway. A hybrid powertrain configuration that includes multiple proton exchange membrane fuel cell systems, batteries, and supercapacitors is designed for a 100% low-floor light rail vehicle (LF-LRV) tramway. According to the hybrid system model of LF-LRV tramway developed with commercial equipment, this proposed multisource coordination energy management strategy is assessed with a real driving cycle of tramway. The results obtained from RT-LAB platform testify that the proposed strategy is capable of coordinating multiple energy sources, guaranteeing the SOC consensus and improving the efficiency of overall tramway.

For low energy consumption and operational stability, Multimode Equivalent Energy Consumption, an optimal energy management and control method, is proposed in this paper. This method effectively solves the problem of energy distribution between the primary power — a high-power fuel cell and an auxiliary power — a supercapacitor, in complex operating conditions. In all four states of the hybrid electric tram: traction, coasting, braking and station parking, the optimal energy distribution method, with the highest energy efficiency of the tram, is obtained through the whole system modeling and the equivalent energy consumption calculation. In order to verify the responding speed, this method gets the analytical solution and is tested on the RT-LAB hardware-in-the-loop simulation platform. The results show that compared to the Power Following Method, the new method can reduce the overall tram energy consumption by 2.5% in complex operating conditions. What's more, when this method is successfully applied to the world's first commercial fuel cell/supercapacitor LF-LRV hybrid tram, its energy consumption and fuel cell system (FCS) output fluctuation rate are effectively reduced according to the operational data, which indicates a good chance of extending the life of the fuel cell system as well.

A coordinated scheduling model based on two-stage distributionally robust optimization (TSDRO) is proposed for integrated energy systems (IESs) with electricity-hydrogen hybrid energy storage. The scheduling problem of the IES is divided into two stages in the TSDRO-based coordinated scheduling model. The first stage addresses the day-ahead optimal scheduling problem of the IES under deterministic forecasting information, while the second stage uses a distributionally robust optimization method to determine the intraday rescheduling problem under high-order uncertainties, building upon the results of the first stage. The scheduling model also considers collaboration among the electricity, thermal, and gas networks, focusing on economic operation and carbon emissions. The flexibility of these networks and the energy gradient utilization of hydrogen units during operation are also incorporated into the model. To improve computational efficiency, the nonlinear formulations in the TSDRO-based coordinated scheduling model are properly linearized to obtain a Mixed-Integer Linear Programming model. The Column-Constraint Generation (C&CG) algorithm is then employed to decompose the scheduling model into a master problem and subproblems. Through the iterative solution of the master problem and subproblems, an efficient analysis of the coordinated scheduling model is achieved. Finally, the effectiveness of the proposed TSDRO-based coordinated scheduling model is verified through case studies. The simulation results demonstrate that the proposed TSDRO-based coordinated scheduling model can effectively accomplish the optimal scheduling task while considering the uncertainty and flexibility of the system. Compared with traditional methods, the proposed TSDRO-based coordinated scheduling model can better balance conservativeness and robustness.