The massive load from the surge of the 5G base station construction affects the operational economics of the distribution network. However, base station backup energy storage can participate in peak reduction and valley filling under the guarantee of reliability and dynamic power backup. How to use distribution network reconfiguration and energy storage regulation to improve the operational economy of both sides needs to be studied.
Firstly, considering that the 5G base station backup energy storage needs to ensure the uninterrupted operation of the base station, this paper analyses the regulation potential of 5G base station backup energy storage and establishes a model for the regulable capacity of base station energy storage. Secondly, considering that the topology of the distribution network is changed after reconfiguration and the power supply paths of some nodes are changed, which leads to changes in node reliability and changes in the 5G base station backup demand, this paper use the Sequential Monte Carlo method to evaluates the node reliability of the distribution network with different topologies and proposes a method to determine the backup duration of base station energy storage considering the node reliability. Thirdly, this paper constructs a two-layer optimization model for distribution network reconfiguration considering optimal regulation of 5G base station backup energy storage. The upper-layer model is reconfigured with the objective of minimum comprehensive operating cost of the distribution network, and the lower-layer model determines the base station energy storage regulation strategy with the objectives of minimum the base station operating cost and load curve variance. Finally, the Cplex commercial solver in Yalmip toolbox of MATLAB platform is used to solve the model. The upper-layer model transmits the reconfiguration results to the lower-layer, and the lower-layer model determines the backup duration of 5G base station energy storage under this topology structure and solves the base station energy storage regulation strategy, and then transmits the updated load data to the upper-layer for the next round of reconfiguration solving. The upper-layer and lower-layer models iterate with each other to obtain the upper-layer reconfiguration strategy of distribution network and the lower-layer regulation strategy of 5G base station energy storage.
The results show that the distribution network reconfiguration considering base station backup energy storage in peak reduction and valley filling reduces the daily comprehensive operation cost by 12.22 yuan compared to that without consideration, while improving the quality of the node voltage level. The 5G base station storage regulation considering the distribution network reconfiguration improves the node reliability, so that the base station energy storage has more regulation space, and reduces the daily base station operation cost by 101.6 yuan.
The following conclusions can be drawn from the analysis of the example:(1) The distribution network reconfiguration considering the role of 5G base station backup energy storage in peak reduction and valley filling improves the operation of the distribution network in terms of economy and safety. (2) The 5G base station backup energy storage regulation strategy under the optimized distribution network topology reduces the operation cost of 5G base stations while reducing the comprehensive operation cost of the distribution network, and realizes the mutual benefits for both the base station and the power grid. (3) The base station energy storage backup considering the reliability of distribution network nodes can distinguish the energy storage backup duration of 5G base stations connected to different nodes, and refine the energy storage regulation potential of each base station.
麻秀范, 张乐萱, 于琨澎, 杨璐. 考虑5G基站备用储能优化调控的配电网重构双层优化方法[J]. 电工技术学报, 2024, 0(0): 2-.
Ma Xiufan, Zhang Lexuan, Yu Kunpeng, Yang Lu. A Two-Layer Optimization Approach for Distribution Network Reconfiguration Considering Optimal Regulation of 5G Base Station Backup Energy Storage. Transactions of China Electrotechnical Society, 2024, 0(0): 2-.
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