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Jianguo Li
College of Electrical Engineering, Shanghai Dianji University, Shanghai 20136, China

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Journal article
Published: 11 October 2019 in Applied Sciences
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In recent years, distributed generation (DG) technology has developed rapidly. Renewable energy, represented by wind energy and solar energy, has been widely studied and utilized. In order to give full play to the advantages of distributed generation and to meet the challenges of DG access to the power grid, the multi-scenario analysis method commonly used in DG optimal allocation method is studied in this paper. In order to solve the problems that may arise from using large-scale scenes in the planning of DG considering uncertainties by using multi-scene analysis method, the cluster analysis method suitable for large-scale scene reduction in scene reduction method is introduced firstly, and then an improved clustering algorithm is proposed. The validity of the scene reduction method is tested, and the feasibility of the reduction method is verified. Finally, the method mentioned in this paper is compared with other commonly used methods through IEEE-33 node system.

ACS Style

Sitong Lv; Jianguo Li; Yongxin Guo; Zhong Shi. A Typical Distributed Generation Scenario Reduction Method Based on an Improved Clustering Algorithm. Applied Sciences 2019, 9, 4262 .

AMA Style

Sitong Lv, Jianguo Li, Yongxin Guo, Zhong Shi. A Typical Distributed Generation Scenario Reduction Method Based on an Improved Clustering Algorithm. Applied Sciences. 2019; 9 (20):4262.

Chicago/Turabian Style

Sitong Lv; Jianguo Li; Yongxin Guo; Zhong Shi. 2019. "A Typical Distributed Generation Scenario Reduction Method Based on an Improved Clustering Algorithm." Applied Sciences 9, no. 20: 4262.

Preprint
Published: 08 September 2019
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In recent years, distributed generation technology has developed rapidly. Renewable energy, represented by wind energy and solar energy, has been widely studied and utilized. In order to give full play to the advantages of Distributed Generation (DG) and meet the challenges after power grid access, Active Distribution Network (ADN) is considered as the future development direction of traditional distribution network because of its ability of active management. Nowadays, multi-scenario analysis is widely used in the research of optimal allocation of distributed power supply in active distribution network. Aiming at the problems that may arise when using multi-scenario analysis to plan DG with uncertainties in large-scale scenarios, a scenario reduction method based on improved clustering algorithm is proposed. The validity of the scene reduction method is tested, and the feasibility of the method is verified. At present, there are few studies on the optimal allocation of DG in ADN under fault state. In this paper, comprehensive safety indicators are introduced. Considering the timing characteristics of DG and the influence of active management mode, a bi-level programming model is established, which aims at minimizing the investment of annual life cycle and the removal of active power. The bi-level model is a complex mixed integer non-linear programming model. A hybrid algorithm combining cuckoo search algorithm and primal dual interior point method is used to solve the model. Finally, through the simulation of the IEEE-33 node system, the superiority of the scenario reduction method and the comprehensive security index used in this paper to optimize the configuration of DG in ADN is verified.

ACS Style

Sitong Lv; Jianguo Li; Yongxin Guo; Zhong Shi. Distributed Generation Planning in Active Distribution Networks Based on Multi-Scene Analysis. 2019, 1 .

AMA Style

Sitong Lv, Jianguo Li, Yongxin Guo, Zhong Shi. Distributed Generation Planning in Active Distribution Networks Based on Multi-Scene Analysis. . 2019; ():1.

Chicago/Turabian Style

Sitong Lv; Jianguo Li; Yongxin Guo; Zhong Shi. 2019. "Distributed Generation Planning in Active Distribution Networks Based on Multi-Scene Analysis." , no. : 1.

Article
Published: 29 October 2015 in Journal of Shanghai Jiaotong University (Science)
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A stability problem of the linear networked control systems (NCSs) with multisensor having different data missing rates is investigated in this paper. Each sensor of the multiple sensor-controller communication channels is assumed to have an individual stochastic data missing rate. The stochastic data missing is described by a Bernoulli binary distribution. Sufficient conditions are given for the closed-loop linear NCS which is exponentially stable in the mean square sense as the existence of random multiple data missing. The stability problem could be disposed by the MATLAB linear matrix inequality (LMI) tool easily. A simulation case is provided to illustrate the validity of the presented LMI approach.

ACS Style

Jian-Guo Li; Li Lu; Ying Jiang; San-Bo Pan. Stability analysis of networked linear systems for multiple sensors with different packet loss probabilities. Journal of Shanghai Jiaotong University (Science) 2015, 20, 528 -534.

AMA Style

Jian-Guo Li, Li Lu, Ying Jiang, San-Bo Pan. Stability analysis of networked linear systems for multiple sensors with different packet loss probabilities. Journal of Shanghai Jiaotong University (Science). 2015; 20 (5):528-534.

Chicago/Turabian Style

Jian-Guo Li; Li Lu; Ying Jiang; San-Bo Pan. 2015. "Stability analysis of networked linear systems for multiple sensors with different packet loss probabilities." Journal of Shanghai Jiaotong University (Science) 20, no. 5: 528-534.