基于线性化方法的交直流混合配电系统网架规划

doi:10.19595/j.cnki.1000-6753.tces.222363

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Abstract In order to adapt the network structure of a distribution network to the access of new energy technologies such as distributed generation (DG), energy storage and DC loads, a new network planning method for AC/DC hybrid distribution networks is proposed. The method considered all possibilities of the AC/DC configuration to improve the economic benefits of the network construction, and constructed a linearized single-layer network planning model to improve the global optimization capability in view of the difficulty of obtaining global optimal solutions for the network planning model.
Firstly, considering that AC/DC types of buses and the connection states between buses determine the investment cost of converters and lines, which determines the economic benefits of distribution network planning, a binary bus type matrix is used to represent AC/DC types of buses, a binary network association matrix is developed to represent the connection states between buses, and binary line type variables are adopoted to represent line type selection to construct network structure decision variables, achieving a description of the overall network structure. Secondly, with an objective of converter installation cost, line construction cost and system operation and maintenance cost, a single-layer network planning model is established considering elaborated and practical constraints, such as the number of node-connected lines, line selection constraint, power flow, voltage source converter (VSC) reactive power compensation capacity, system safety operation, energy storage operation, network connectivity and so on. In this proposed model, the AC and DC current models is unified by introducing branch type variables, thus linking the planning layer and operation layer, so that network planning variables and operation optimization variables consisting of power purchased from the distribution network to the grid, DG output, energy storage charging and discharging power and VSC power were optimized simultaneously to enhance the possibility of obtaining a global optimal solution. Finally, to achieve better sulution, power flow equations and line transmission capacity constraints are linearized by a series of linearization methods, such that the mixed integer nonlinear programming (MINLP) problem was transformed into a mixed integer linear programming (MILP) problem, and the GUROBI solver is invoked in Matlab to solve it.
The validity of the planning method was verified in a 13-node distribution system. The simulation results show that: (1) The AC/DC hybrid distribution network planning scheme can save 5.05% of the total investment and operation cost compared with the pure AC distribution network planning, and the network structure of the planned AC/DC hybrid distribution network also has greater network supply capacity, which illustrates that the AC/DC hybrid distribution network is more advantageous in the case of mixed AC/DC sources and loads. (2) The proposed planning method saves 13.54% of the total investment and operation cost and 91.32% of the computation time compared with the traditional bi-layer planning model solved by genetic algorithm, which indicates that the single-layer network planning method has prominent global optimization performance and faster computational efficiency. (3) As the method does not require relaxation of constraints, compared to second-order cone planning techniques, there are no limitations in terms of grid topology, etc, and it is suitable for the planning of both radial and meshed distribution networks.

Key words： AC/DC Hybrid distribution system network planning single-layer programming linearization optimization

Received: 16 December 2022

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	Jiang Yuewen
	Luo Zeyu
	Cheng Nuo

Cite this article:

Jiang Yuewen,Luo Zeyu,Cheng Nuo. Network Planning of AC/DC Hybrid Distribution System Based on Linearization Method[J]. Transactions of China Electrotechnical Society, 2024, 39(5): 1404-1418.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.222363 OR https://dgjsxb.ces-transaction.com/EN/Y2024/V39/I5/1404

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