Multi-Stage Optimal Placement of Branch PMU in Active Distribution Network

Author(s):  
Wang Shu ◽  
Kong Xiangrui ◽  
Yan Zheng ◽  
Xu Xiaoyuan ◽  
Wang Han

Abstract The penetration of distributed generation and electric vehicles requires advanced monitoring and control strategies to maintain the reliable operation of active distribution network (ADN). Phasor measurement unit (PMU), as an advanced measuring device, has been applied in the operation of transmission systems for decades. Recently, it is anticipated that PMUs can be adopted in the distribution network. In this paper, the optimal branch PMU (BPMU) placement is studied. First, an optimization model for the multi-stage BPMU placement is established considering the observability of ADN. Moreover, the weights of buses are designed to consider the influence of uncertain renewable energy generation and loads. Then, probabilistic load flow (PLF) is used to solve power flow with uncertainties, and weights of buses are obtained based on probability distributions of voltage magnitude. Finally, binary integer programming (BIP) is adopted to obtain the locations of BPMUs. The proposed method is tested on customized IEEE 33-bus and PG&E 69-bus distribution network, and the results are compared with those considering other methods.

energyo ◽  
2019 ◽  
Author(s):  
Wang Shu ◽  
Kong Xiangrui ◽  
Yan Zheng ◽  
Xu Xiaoyuan ◽  
Wang Han

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2830 ◽  
Author(s):  
Chang Ye ◽  
Shihong Miao ◽  
Yaowang Li ◽  
Chao Li ◽  
Lixing Li

This paper presents a hierarchical multi-stage scheduling scheme for the AC/DC hybrid active distribution network (ADN). The load regulation center (LRC) is considered in the developed scheduling strategy, as well as the AC and DC sub-network operators. They are taken to be different stakeholders. To coordinate the interests of all stakeholders, a two-level optimization model is established. The flexible loads are dispatched by LRC in the upper-level optimization model, the objective of which is minimizing the loss of the entire distribution network. The lower-level optimization is divided into two sub-optimal models, and they are carried out to minimize the operating costs of the AC/DC sub-network operators respectively. This two-level model avoids the difficulty of solving multi-objective optimization and can clarify the role of various stakeholders in the system scheduling. To solve the model effectively, a discrete wind-driven optimization (DWDO) algorithm is proposed. Then, considering the combination of the proposed DWDO algorithm and the YALMIP toolbox, a hierarchical optimization algorithm (HOA) is developed. The HOA can obtain the overall optimization result of the system through the iterative optimization of the upper and lower levels. Finally, the simulation results verify the effectiveness of the proposed scheduling scheme.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 68124-68134 ◽  
Author(s):  
Muhammad Zulqarnain Zeb ◽  
Kashif Imran ◽  
Abraiz Khattak ◽  
Abdul Kashif Janjua ◽  
Anamitra Pal ◽  
...  

2020 ◽  
Vol 10 (11) ◽  
pp. 3812
Author(s):  
Xiaohui Wang ◽  
Peng Wang ◽  
Yunbo Wang ◽  
Fang Shi

The potential short-circuit current in active distribution network features time-variance with the increasing distributed generations. This feature makes the online estimation of fault level necessary. In this paper, a novel online estimation method is proposed to be implemented by either phasor measurement unit (PMU) or the measurements from protection relays. The equivalent circuit of the radial distribution network with distributed generators (DGs), e.g., wind turbines and photovoltaic cells, is derived with necessary simplifications. The natural disturbances downstream are used to evaluate the parameters of the equivalent circuit so that the potential fault level can be estimated in advance of the actual fault occurrence. A fuzzy logic identifier is presented to rank the confidence of the measurements incurred by the disturbance and to distinguish the qualified disturbance to launch the estimation. The mechanism based on multi-measurements and confidence indices was applied, to improve the accuracy. A typical distribution network in the United Kingdom (UK) with DGs was taken, as an example, to validate the proposed method under various load fluctuation. The results confirm the effectiveness of the proposed method, which is suitable for online estimation of short-circuit fault level in active distribution networks.


Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4297
Author(s):  
Kong ◽  
Yuan ◽  
Wang ◽  
Xu ◽  
Yu

With the continuous development of smart distribution networks, their observable problems have become more serious. Research on the optimal placement of the distribution phasor measurement unit (D-PMU) is an important way to improve the measurability, observability and controllability of a smart distribution network. In this paper, the optimal D-PMU placement methods and implementation technology were studied to determine the optimal D-PMU placement scheme. Considering the bus vulnerability index and the different operating states of the system, the more practical one-time optimal placement methods to ensure complete system observability was proposed. On this basis, the system's measurement redundancy and unobservable depth were considered to realize the multistage optimal D-PMU placement. The corresponding mathematical model and solution flow were given. Then the implementation technology of the methods was studied and the optimal D-PMU placement assistant decision-making software for smart distribution network was developed. Thereby, the structure and requirements of different distribution networks can be satisfied. The application analysis, functional architecture and the overall design process were given. Finally, the methods and software were analyzed by using the IEEE 33 bus system and an actual project, the Guangzhou Nansha Yuan'an Substation. The verification results showed that the method and software mentioned in this paper can provide convenient and quick operation for optimal D-PMU placement, improve the efficiency of smart distribution network planning work, and promote the theoretical application level of smart distribution network planning results.


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