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Multi-Objective Coordinated Planning of Distributed Generation and AC/DC Hybrid Distribution Networks Based on a Multi-Scenario Technique Considering Timing Characteristics

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  • Yongchun Yang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Xiaodan Wang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Jingjing Luo

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Jie Duan

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Yajing Gao

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Hong Li

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Xiangning Xiao

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

Abstract

With increased direct current (DC) load density and the penetration of a large number of distributed generation (DG) units in alternating current (AC) distribution networks (DNs); a planning approach that considers transforming some of the AC lines into DC lines and building the DC network is proposed. Considering the DG output uncertainty and the load fluctuation, a planning model for an AC/DC hybrid distribution network (DN) with the DG based on the construction of multi-scenario technology with timing characteristics is built. In the DG configuration planning model, the lines to be transformed into DC form the access location and the decision regarding the DC or AC form of the newly built lines are considered optimizing variables. The DG investment, the network and converters of the DG and load, the active power loss and the voltage stability are considered in the objective functions. An improved adaptive niche genetic algorithm based on the fuzzy degree of membership and variance weighting is used to solve the nested model. Finally, considering the improved electrical and electronic engineers 33 (IEEE33) node system as an example, the correctness and effectiveness of the proposed planning method are verified. Compared to the plan without transforming some of the AC lines into DC lines and building a DC network, more DG can be admitted, and the economic cost of the AC/DC hybrid DN is notably decreased when planning to transform some of the AC lines into DC lines and build a DC network. The active power network loss and the voltage stability index are similarly further optimized.

Suggested Citation

  • Yongchun Yang & Xiaodan Wang & Jingjing Luo & Jie Duan & Yajing Gao & Hong Li & Xiangning Xiao, 2017. "Multi-Objective Coordinated Planning of Distributed Generation and AC/DC Hybrid Distribution Networks Based on a Multi-Scenario Technique Considering Timing Characteristics," Energies, MDPI, vol. 10(12), pages 1-29, December.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:2137-:d:123068
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    References listed on IDEAS

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    Cited by:

    1. Hao Pan & Ming Ding & Anwei Chen & Rui Bi & Lei Sun & Shengliang Shi, 2018. "Research on Distributed Power Capacity and Site Optimization Planning of AC/DC Hybrid Micrograms Considering Line Factors," Energies, MDPI, vol. 11(8), pages 1-18, July.
    2. Fei Wang & Kangping Li & Xinkang Wang & Lihui Jiang & Jianguo Ren & Zengqiang Mi & Miadreza Shafie-khah & João P. S. Catalão, 2018. "A Distributed PV System Capacity Estimation Approach Based on Support Vector Machine with Customer Net Load Curve Features," Energies, MDPI, vol. 11(7), pages 1-19, July.
    3. Hao Pan & Ming Ding & Rui Bi & Lei Sun, 2019. "Research on Cooperative Planning of Distributed Generation Access to AC/DC Distribution (Micro) Grids Based on Analytical Target Cascading," Energies, MDPI, vol. 12(10), pages 1-20, May.
    4. Hamza M. Bakr & Mostafa F. Shaaban & Ahmed H. Osman & Hatem F. Sindi, 2020. "Optimal Allocation of Distributed Generation Considering Protection," Energies, MDPI, vol. 13(9), pages 1-18, May.
    5. Hong Li & Xiaodan Wang & Jie Duan & Feifan Chen & Yajing Gao, 2018. "Locating Optimization of an Integrated Energy Supply Centre in a Typical New District Based on the Load Density," Energies, MDPI, vol. 11(4), pages 1-22, April.
    6. Guo, Li & Hou, Ruosong & Liu, Yixin & Wang, Chengshan & Lu, Hai, 2020. "A novel typical day selection method for the robust planning of stand-alone wind-photovoltaic-diesel-battery microgrid," Applied Energy, Elsevier, vol. 263(C).

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