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| A Flexible Scheduling Method of AC/DC Hybrid Distribution Network Considering the Multi-Dimensional Value Tags of Flexible Resources |
| Li Zongsheng, Zhang Lu, Zhang Zhigang, Lou Chengwei, Tang Wei |
| College of Information and Electrical Engineering China Agricultural University Beijing 100083 China |
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Abstract The high permeability of renewable energy makes the AC/DC hybrid distribution network face serious randomness. Fully tapping the regulation potential of flexible resources can effectively reduce the operation risk of distribution network caused by renewable energy. At present, many studies have explored the regulation potential of distribution network from multiple levels of ''source-network-load-storage'' of AC/DC hybrid distribution network, which has improved the economy and safety of system operation to a certain extent. However, there are some problems, such as single evaluation index of flexible resource, insufficient research on collaborative control of voltage source converter (VSC) and flexible resources, and difficulty in suppressing the uncertainty of renewable energy. A flexible scheduling method of AC/DC hybrid distribution network considering multi-dimensional value tags of flexible resources is proposed.
Firstly, considering the influence factors of the regulation potential for flexible resources such as temperature-controlled load, electric vehicle and VSC, a multi-dimensional value tag evaluation system is proposed, including response period, regulation capability, regulation cost and response willingness. The regulation potential of temperature-controlled load, electric vehicle and VSC is evaluated respectively, and the comprehensive regulation potential range of flexible resources in each response period is further accurately calculated. Secondly, a two-stage robust day-ahead optimal scheduling model of AC/DC hybrid distribution network is established, in which the objective function is minimizing the operation cost, and the constraints include the operation constraints of various types of equipment, the operation safety constraints of AC/DC hybrid distribution network, the renewable energy output interval and the total control potential range of flexible resources.
The simulation results of the improved IEEE 33 node AC/DC hybrid distribution network show that the multi-dimensional value tags of flexible resources can accurately evaluate the comprehensive regulation potential of each response period, according to the historical electricity consumption habits, travel habits and response willingness of different users, thereby improving the solution efficiency and accuracy of the proposed scheduling model of AC/DC hybrid distribution network. The power demand can be reduced by power reduction and power transfer of flexible resources such as temperature-controlled load and electric vehicle on the temporal scale, which can also be reduced by transferring load power between AC and DC systems using VSC on the spatial scale. The coordinated scheduling of flexible resources and VSC can effectively reduce the operation cost of AC/DC hybrid distribution network and improve the accommodation capacity of renewable energy.
The following conclusions can be drawn from the simulation analysis: (1) Aiming at the difference of regulation characteristics between flexible resources such as temperature-controlled load, electric vehicle and VSC, a multi-dimensional value tag system including response period, regulation capability, regulation cost and response willingness is constructed, which can accurately evaluate the comprehensive regulation potential range of flexible resources. (2) A two-stage robust day-ahead optimal scheduling model of AC/DC hybrid distribution network is established, which takes the minimum operating cost as the objective function and the multi-dimensional value tags of flexible resources as the constraint. It not only avoids the infeasible solutions beyond the power regulation potential of flexible resources, but also reduces the solution space of optimization variables, thus improving the computational efficiency. The nested C&CG algorithm can effectively improve the solution accuracy and cope with the uncertainty of renewable energy.
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Received: 08 January 2024
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2024, Vol. 39 
