Abstract：While promoting national economic growth, the rapid development of electrified railroads has increased the pressure of energy consumption, energy saving and emission reduction of the system. The construction of "network-source-storage-train" cooperative power supply system is conducive to the local consumption of new energy and the recycling of regenerative braking energy, which is of great significance to achieve the goal of "double carbon". However, the existing rules management strategy mainly focuses on the "network-storage-train" architecture and has limited management effect; the optimized management strategy often focuses on a single indicator such as economy and has low reliability. Therefore, this paper proposes a real-time energy management strategy based on "rules + optimization" for electrified railroad stations, which can improve the traction network voltage level and public grid power quality while achieving efficient utilization of new energy and regenerative braking energy. First of all, the "network-source-storage-train" cooperative power supply mechanism is determined with the low-carbon economic operation of the system as the guide, and the energy management instructions in each working mode are determined through logical analysis and judgment to improve the energy rule management strategy under the "network-source-storage-train" cooperative power supply architecture. Then, taking into account the traction transformer, railway power conditioner power transmission losses and new energy, train regenerative braking energy disposal costs, the system operation cost function is improved to enhance the system global optimization capability. Further, a multi-objective site energy management optimization model is constructed with the objectives of minimizing the site operation cost and minimizing the three-phase voltage imbalance on the high-voltage side of the traction transformer, and the model is simplified by using a logical front, and the site energy optimization management strategy is formulated based on the solution results. Finally, the cooperation mechanism of rule management and optimization management is designed, starting with the parallelism of the two procedures and ending with the real-time management time threshold, so as to realize the orderly switching of management instructions and the complementary advantages of management strategies. Through the simulation verification of the measured data, the following conclusions can be drawn: (1) The rule management can achieve ms-level output, which makes up for the defect that the optimization management cannot reliably output instructions within the real-time management requirements. (2) The multi-objective optimal management strategy designed in this paper can consume 0.77 MW more clean energy in a single day, reduce the operating cost by 0.55% more and the voltage imbalance does not exceed the national standard, which fills the shortage of rule management in the multi-objective optimal operation of the system. (3) Compared with the traditional traction power supply system without energy management, the single-day operating cost of the system under the energy management strategy based on "rules + optimization" in this paper can be reduced by 42.51%, the voltage fluctuation range of the low-voltage side of the traction transformer can be reduced by 93.44%, and the highest value of the three-phase voltage unbalance on the high-voltage side is only 1.81%. All test moments can meet the national standard requirements. (4) Under the real-time energy management strategy based on "rules + optimization", the estimated payback time of the "network-source-storage-train" cooperative power supply system is 2.1 years, and the final benefit is 2.55×104 million RMB, which provides strong support for the implementation of the actual project.
李俊豪, 涂春鸣, 王鑫, 郭祺, 肖凡. 基于“规则 + 优化”的电气化铁路站点实时能量管控策略[J]. 电工技术学报, 2024, 39(11): 3339-3352.
Li Junhao, Tu Chunming, Wang Xin, Guo Qi, Xiao Fan. Real-Time Energy Management Strategy for Electrified Railroad Stations Based on “Rules + Optimization”. Transactions of China Electrotechnical Society, 2024, 39(11): 3339-3352.
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2024, Vol. 39 
