Pareto Front Analysis Method for Optimization of PV Inverter Based Volt/Var Control Considering Inverter Lifetime

Qingmian Chai; Cuo Zhang; Yan Xu; Zhao Yang Dong; Rui Zhang

doi:10.17775/CSEEJPES.2022.00840

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

Pareto Front Analysis Method for Optimization of PV Inverter Based Volt/Var Control Considering Inverter Lifetime

Regular Papers | 更新时间：2026-10-15

- Pareto Front Analysis Method for Optimization of PV Inverter Based Volt/Var Control Considering Inverter Lifetime
- CSEE Journal of Power and Energy Systems Vol. 9, Issue 1, Pages: 111-121(2023)
- 作者机构：
  
  1. School of Electrical Engineering and Telecommunications, The University of New South Wales,Sydney,Australia
  2. School of Electrical and Information Engineering, The University of Sydney,Australia
  3. School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore,639798
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2022.00840
  CLC：
- Published：01 January 2023
- 稿件说明：
移动端阅览
Qingmian Chai, Cuo Zhang, Yan Xu, et al. Pareto Front Analysis Method for Optimization of PV Inverter Based Volt/Var Control Considering Inverter Lifetime[J]. CSEE Journal of Power and Energy Systems, 2023, 9(1): 111-121.
DOI：

Qingmian Chai, Cuo Zhang, Yan Xu, et al. Pareto Front Analysis Method for Optimization of PV Inverter Based Volt/Var Control Considering Inverter Lifetime[J]. CSEE Journal of Power and Energy Systems, 2023, 9(1): 111-121. DOI： 10.17775/CSEEJPES.2022.00840.

摘要

Abstract

Photovoltaic (PV) inverter-based volt/var control (VVC) is highly promising to tackle the emerging voltage regulation challenges brought by increasing PV penetration. However

PV inverter operational reliability has arisen as a critical concern for practical VVC implementation. This paper proposes a new PV inverter based VVC optimization model and a Pareto front analysis method for maintaining a satisfactory inverter lifetime. First

reliability of the vulnerable DC-link capacitor inside a PV inverter is analyzed

and long-term VVC impact on inverter operational reliability is identified. Second

a multi-objective PV inverter based VVC optimization model is proposed for minimizing both inverter apparent power output and network power loss with a weighting factor. Third

a Pareto front analysis method is developed to visualize the impact of the weighting factor on VVC performance and inverter reliability

thus determining the effective weighting factor to reduce network power loss with expected inverter lifetime. Effectiveness of the proposed VVC optimization model and Pareto front analysis method are verified in a case study.

关键词

Keywords

references

1. Department of Industry, Science, Energy and Resources, Australian Government . [Online ] . Available: https://www.energy.gov.au.

4. ( 2019, Jan. ). IEEE 1547 standard for interconnecting distributed resources with electric power systems . [Online ] . Available: http://grouper.ieee.org/groups/scc21/1547/1547_index.html.

5. ( 2020, Dec. ). AS/NZS 4777.2:2020, Australian standard. [Online]. Available: https://www.standards.org.au/standards-catalogue/sa-snz/other/el-042/as-slash-nzs-4777-dot-2-colon-2020.

22. Application guide, aluminum electrolytic capacitors, Cornell Dubilier, Liberty, SC, USA . [ Online ] . Available: http://www.cde.com/catalogs/AEappGUIDE.pdf.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Robust $N-k$ Security-constrained Optimal Power Flow Incorporating Preventive and Corrective Generation Dispatch to Improve Power System Reliability

Reliability evaluation of UHVDC transmission systems with a hierarchical connection mode

Dynamic Temperature Model of AA-CAES for Reliability Evaluation of IES

Unreliability Tracing of Power Systems with High Penetration of Wind Power Based on Temporal Decomposition Model

State-Space and Impedance Modeling Methods for Stability Analysis of Interconnected Power Electronic Systems

Related Author

Liping Huang

Chun Sing Lai

Zhuoli Zhao

Guangya Yang

Bang Zhong

Loi Lei Lai

Shenghu Li

Zhengyang Wu

Related Institution

School of Automation, Guangdong University of Technology

Department of Electronic and Electrical Engineering, Brunel University London

Department of Electrical Engineering, Center for Electric Power System and Energy, Technical University of Denmark, Kongens Lyngby, Demark

Zhaoqing Power Supply Bureau, Guangdong Power Grid Company, China Southern Power Grid

Hefei University of Technology,,, CN

AI问答

⁰