Two-Stage Reactive Power Optimization for Distribution Network Considering Reactive Power Margin

doi:10.12204/j.issn.1000-7229.2021.09.014

Abstract

Abstract:

To solve the coordinated dispatch and spatiotemporal coupling of various adjustable resources after high-proportion renewable distributed generation (RDG) is connected to the distribution network, a two-stage reactive power optimization for distribution network considering reactive power margin is proposed. The Copula theory is used to establish a prediction model which considers the uncertainty and correlation of wind power and photovoltaic output. In the first stage, a day-ahead multi-objective optimization model is established by considering voltage deviation, operation cost and dynamic reactive power margin. In the second stage, the continuous regulating device is used to respond the fluctuations of photovoltaic and wind power, which realizes the differentiated management of reactive power regulating devices with different fast and slow time constants while fully coordinating the adjustable resources in the distribution network in a short time scale. Finally, the simulation example carried out on the improved IEEE 33-node system shows that the collaborative optimization strategy can improve the safety and economic benefits of the system, and verify the influence of the wind-photovoltaic correlativity on the system.

Key words: optimization of active power, optimization of reactive power, renewable distributed generation (RDG), multi-objective optimization, Copula correlativity, reactive power margin

CLC Number:

TM73

HU Rong, QIU Xiaoyan, ZHANG Zhirong. Two-Stage Reactive Power Optimization for Distribution Network Considering Reactive Power Margin[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(9): 129-139.

Figures/Tables 14

Fig.1 Solution method of optimal active-reactive power dispatch model in the first stage

Fig.B1 Modified IEEE 33-node distribution system

Fig.B2 Historic data

Fig.2 Scene generation results considering correlation

Table B1 Electricity purchase price

Fig.B3 Load forecast output of the first stage

Table 1 Comparison of compromise solutions

Fig.3 Comparison of node voltages

Fig.4 Comparison of optimization results

Fig.5 Comparison of continuous reactive power outputs of compensation devices

Fig.B4 Photovoltaic, wind power and load output in the second stage

Fig.6 Voltages at typical nodes

Fig.7 Charging and discharging of energy storages

Table 2 Comparison of CvaR

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