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Optimal Control Of On-Board Energy Storage Systems And New Power Supply Networks For Dual-source Trolleybuses

Posted on:2018-08-24Degree:DoctorType:Dissertation
Country:ChinaCandidate:D ZhangFull Text:PDF
GTID:1312330512975548Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Dual-source trolleybuses powered by both on-board energy storage system and grid electricity offer unique advantages in zero tail gas emission,fuel economy,flexible driveability,cost reduction,and short construction period,which are especially appealing for public transportation in populated cities.With the large-scale popularization and application of new dual-source trolleybuses,their mobility,the complexity of running road conditions,and power supply network configurations introduce great challenges for safe,reliable,and efficient operation of new dual-source trolleybuses.In this thesis,the driving energy consumption characteristics of new dual-source trolleybuses are analyzed by using the actual parameters and operation data of Beijing dual-source trolleybuses and power supply network systems.The estimation model of segment capacity in ground power supply network is established,and the capacity of the segment and the ground power supply network are evaluated based on the electrical network analysis and software simulation.The conclusion is drawn that the existing power supply network and its operation and management technology can not meet the development demand of the dual-source trolleybuses.For the existing power supply network system,the optimal control model of on-board energy storage system output is established,and the optimal control algorithm is used to solve this issue under the system constraints.At the same time,the linear auto-regression model structure to represent the vehicle driving power demand profiles,and the prediction model parameters are estimated by a recursive least squares estimator with forgetting factor,and the prediction accuracy is improved by using a finite impulse response low-pass filter.The prediction-based distributed control strategy for on-board energy storage system is put forward by integrating the driving demand prediction algorithms and optimal control,to control the output of on-board energy storage system.The actual operational data of buses are used to demonstrate usages of the proposed optimal control methodologies,and the feeder current peak can be greatly reduced without affecting the operation of the vehicles,which implies that more dual-source trolleybuses can be supported and the power supply infrastructure resources can be the most fully utilized.A new distributed power supply network technology is proposed to solve the problem of segment feeder current unbalance in the existing power supply network system.The weighted-and-constrained consensus control method is introduced to manage the ground power supply network.Using only neighborhood information exchange among feeder lines in the network,the consensus control can achieve global current balancing with fast convergence to a balanced state.The convergence and stability of the proposed control algorithm are also theoretically discussed and proved,and the algorithms are further enhanced for improved convergence under large observation noise so that the feeder current distributions converge to the global consensus faster with much less fluctuation.Under non-uniform segment capacities,the current of each feeder can be distributed relatively to their capacities to realize the global weighted consensus.Robustness to sudden change of line load and scalability to reconfiguration with feeder addition and deletion are demonstrated,together with discussions on the feasibility,flexibility,and implementation issues of the methodology through the simulation case studies.Extending on the original single-objective power management method,a multi-objective optimal power management strategy for both distributed feeder current balancing and power loss reduction is introduced.The global optimization method and the local optimization method are given respectively.One critical finding is that the local optimization algorithm using only neighborhood information exchange among feeders actually achieves the global optimal solution asymptotically under uniform segment capacities.The distributed recursive optimization algorithm based on consensus control is given to solve this multi-objective power management optimization model.With different weighte coefficients,different tradeoffs can be achieved.For practical applications,the weight coefficient should be carefully considered based on different application scenarios and progressive development stages of dual-source trolleybus systems.
Keywords/Search Tags:dual-source trolleybus, on-board energy storage system, optimal control, driving power demand prediction, new power supply network, power management, consensus control
PDF Full Text Request
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