Research on Multi-Energy Integrated Ship Energy Management System Based on Hierarchical Control Collaborative Optimization Strategy
Abstract
:1. Introduction
2. Typical System Structure and Mathematical Modeling of Hybrid Electric Ship
2.1. Typical System Structure
2.2. Distributed Power Mathematical Model
2.2.1. Diesel Engine and Speed-Governing System Model
2.2.2. Synchronous Generator and Excitation System Model
2.2.3. Photovoltaic Power Generation System Model
2.2.4. Doubly-Fed Wind Power Generation System Model
2.3. Mathematical Model of Energy Storage System
3. Hierarchical Control Scheme and Optimization Algorithm Design for Hybrid Ships
3.1. Hierarchical Control Scheme
3.2. Maximum Power Point Tracking Control Strategy for Ship Propulsion Systems
3.3. Design of Two-Layer Coordinated Control Strategy Based on Dynamic Droop Controller
3.4. Research on Day-Ahead Optimal Dispatching Strategy of Ship Power System
3.4.1. Mathematical Model of Day-Ahead Optimal Scheduling Problem in Power System
3.4.2. Research on Day-Ahead Optimization Scheduling Method Based on Improved PSO
4. Simulation Verification and Analysis
4.1. Simulation and Verification of MPPT Control Strategy Based on Improved Disturbance Observation Method
- Simulation of photovoltaic power generation system:
- 2.
- Wind Power System Simulation
4.2. Simulation Verification of Control Strategy Based on the Dynamic Droop Controller
4.3. Simulation Verification of Day-Ahead Optimal Scheduling Control Strategy
5. Conclusion and Discussion
- The overall scheme of the layered control system of the ship propulsion system is designed, and a detailed and complete mathematical model is established. An overall simulation model of the ship propulsion system is built, which meets the needs of subsequent related research and simulation tests.
- A P&O algorithm based on dynamic perturbation step size is designed, including oscillation detection mechanism, dynamic perturbation step adjustment strategy, and voltage boundary setting. Through the comparison example simulation test with the traditional algorithm, the results show that the power loss of the MPPT control strategy using the P&O algorithm with a dynamic disturbance step size is reduced by 39.3%, and the overall tracking time is prolonged by 15.4%.
- A three-layer coordinated control strategy of the propulsion system based on the dynamic droop coefficient is designed, which dynamically adjusts the fixed droop coefficient. Realizing the adaptive change of the droop coefficient solves the problem of voltage and frequency deviation. In order to improve the system performance, the power sensitivity factor is designed simultaneously; moreover, a voltage and current double closed-loop controller are further designed to improve the inverter noise immunity and power quality. The simulation results show that the proposed control strategy can effectively suppress the voltage and frequency fluctuations and improve the system-connected security and power quality of the system-connected side.
- A PSO algorithm based on mutation particles is designed, and the collection information of some top-ranked vectors is mixed in the generated mutation vector; furthermore, the method of the segmental improvement speed formula is adopted in order to improve the accuracy and search speed. Through the standard function performance test with other intelligent optimization algorithms, the results show that the improved algorithm has a faster convergence speed and higher accuracy in solving the load optimization problem. The total running cost of the algorithm is reduced 8.4%, and the total cost was reduced by 8.2%.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
Nomenclature
Category | Symbol | Implication |
abbreviations | PSO | Particle Swarm Optimization |
IPSO | Improved Particle Swarm Optimization | |
PV | Photovoltaic | |
MPPT | Maximum Power Point Tracking | |
P&O | Perturbation Observation Algorithm | |
GA | Genetic Algorithm | |
DE | Differential Evolution | |
PWM | Pulse Width Modulation | |
parameter | the damping coefficient | |
the angular velocity of the diesel engine | ||
the number of pole pairs of the synchronous generator | ||
the output torque of the diesel engine | ||
resistance torque of the diesel engine | ||
the constant current source | ||
the current passing through the diode | ||
the temperature coefficient | ||
the pitch angle of the blade | ||
the maximum power output of the current | ||
the maximum power output of the voltage | ||
the voltage to the photovoltaic array | ||
the open circuit voltage | ||
the temperature of the photovoltaic array | ||
the ambient temperature | ||
the actual solar irradiance | ||
the tip speed ratio | ||
the rotational speed | ||
the wind speed | ||
the speed of wind turbines | ||
the lithium battery voltage | ||
the constant voltage source voltage | ||
the lithium battery charge/discharge capacity | ||
the filtered current | ||
the state of charge of the lithium battery | ||
the three-phase current output by the inverter | ||
the three-phase voltage output by the inverter | ||
the reference active power | ||
the reference reactive power | ||
the SPWM modulation signal | ||
the given reference frequency | ||
the given reference voltage | ||
the dynamic droop coefficient | ||
the dynamic droop factor | ||
the sensitivity factor | ||
the operating cost coefficients | ||
the numbers of wind power generation units | ||
the output power of wind power generation systems | ||
the maximum number of iterations | ||
the test vector function | ||
the target vector function | ||
an indicator used to monitor |
Appendix A
SO2 | CO2 | CO | NOX |
---|---|---|---|
4.34 | 2.32 | 0.47 | 232.04 |
Appendix B
SO2 | CO2 | CO | NOX |
---|---|---|---|
0.75 | 0.0028 | 0.125 | 1.00 |
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Symbol | Symbol | Slope Value |
---|---|---|
+ | + | +1 |
+ | − | −1 |
− | + | −1 |
− | − | +1 |
Algorithm | Track Time (s) | Maximum Power Loss (kW) |
---|---|---|
traditional P&O | 341.1 | 15.46 |
improved P&O | 393.7 | 4.74 |
Day-Ahead Planned Cost | Improvement Strategy | Fixed Strategy * |
---|---|---|
Diesel generator fuel cost | 7663.2 | 8371.2 |
Environmental cost of diesel generator | 751.51 | 820.93 |
Operating cost of diesel generator | 28.74 | 28.74 |
Cost of energy storage system | 280 | 400 |
Renewable energy cost | 99.19 | 99.19 |
Load profit | 1215 | 1215 |
Total cost | 10,037.64 | 10,935.06 |
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Ren, Y.; Zhang, L.; Shi, P.; Zhang, Z. Research on Multi-Energy Integrated Ship Energy Management System Based on Hierarchical Control Collaborative Optimization Strategy. J. Mar. Sci. Eng. 2022, 10, 1556. https://doi.org/10.3390/jmse10101556
Ren Y, Zhang L, Shi P, Zhang Z. Research on Multi-Energy Integrated Ship Energy Management System Based on Hierarchical Control Collaborative Optimization Strategy. Journal of Marine Science and Engineering. 2022; 10(10):1556. https://doi.org/10.3390/jmse10101556
Chicago/Turabian StyleRen, Yuanjie, Lanyong Zhang, Peng Shi, and Ziqi Zhang. 2022. "Research on Multi-Energy Integrated Ship Energy Management System Based on Hierarchical Control Collaborative Optimization Strategy" Journal of Marine Science and Engineering 10, no. 10: 1556. https://doi.org/10.3390/jmse10101556
APA StyleRen, Y., Zhang, L., Shi, P., & Zhang, Z. (2022). Research on Multi-Energy Integrated Ship Energy Management System Based on Hierarchical Control Collaborative Optimization Strategy. Journal of Marine Science and Engineering, 10(10), 1556. https://doi.org/10.3390/jmse10101556