Collaborative Optimization and Control of Integrated Microgrid with High Penetration of Distributed Energy

Yue Xiang; Jun Yong Liu; You Bo Liu

doi:10.4028/www.scientific.net/AMR.709.417

Paper Titles

Realization of the Optimization of Dijkstra Algorithm in Vehicle Navigation
p.399

Automatic PID Temperature Control of Thermoelectric Cooler Based on MSP430
p.404

Design and Implementation of Mid-Frequency Magnetron Sputtering Power Supply Based on TL494 and MCU
p.408

A Multi-Vehicle Tracking Algorithm Based on QPSO Clustering Algorithm and Particle Position Matching Template
p.413

Collaborative Optimization and Control of Integrated Microgrid with High Penetration of Distributed Energy
p.417

The Trust Relay QKD Network Communication Research
p.421

Simulation Research on Instantaneous Control in Battery Energy Storage System
p.427

The Design of a Rubik's Cube Robot
p.432

Research on the Key Technologies of Low-Altitude Airspace Surveillance and Navigation System
p.436

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 709Collaborative Optimization and Control of...

Collaborative Optimization and Control of Integrated Microgrid with High Penetration of Distributed Energy

Abstract:

Collaborative optimization and control of integrated distribution system/ microgrid with high penetration of distributed energy have been introduced in this paper. Along with the development of the smart grid, source-grid-load coordination framework, unit flexibility and load feasibility, muti-energy combination microgrid optimization, control strategies are introduced, and related methodologies and approaches are concluded, as well as the further research.

You might also be interested in these eBooks

Advances in Applied Science, Engineering and Technology

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 709)

Pages:

417-420

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.709.417

Citation:

Cite this paper

Online since:

June 2013

Authors:

Yue Xiang, Jun Yong Liu, You Bo Liu

Keywords:

Advanced Control Methodology, Demand Response, Distributed Generation (DG), Energy Optimization

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Zhaoyang Dong, Pei Zhang. Emerging Techniques in Power System Analysis. Higher Education Press, Beijing, 2009.

Google Scholar

[2] J. A. SHORT, D. G. INFELD, L. L. FRERIS: Stabilization of grid frequency through dynamic demand control．IEEE Transactions on Power Systems, Vol. 22 (2007), pp.1284-1293.

DOI: 10.1109/tpwrs.2007.901489

Google Scholar

[3] Xueping Liu, Tianqi Liu, Xingyuan Li. Power coordination strategies for hybrid isolated microgrid and its simulation. Power System Technology, Vol. 34 (2010), pp.202-205.

Google Scholar

[4] Jinyong Lei, Jun Xie, GAN Deqiang. Optimizaion of distributed energy system and benefit analysis of energy saving and emission reduction． Automation of Electric Power Systems, Vol. 33 (2009), pp.29-36．

Google Scholar

[5] Ping Ju, Changchun Cai, Xiangqin Cao. General microgrid model based on physical background．Electric Power Automation Equipment, Vol. 30 (2010), pp.7-14．

Google Scholar

[6] Li Guo, Chengshan Wang. Dynamical simulation on microgrid with different types of distributed generations．Automation of Electric Power Systems, Vol. 33 (2009), pp.82-86．

Google Scholar

[7] Mingjun Wang. Self-healing grid and distributed energy resource. Power System Technology, Vol. 31 (2007), pp.1-7．

Google Scholar

[8] Jiabin Wen, Mifu Liu. Improvement of maximum power point tracking for photovoltaic system. Electric Power Automation Equipment, Vol. 29 (2009), pp.81-84．

Google Scholar

[9] Youbo Liu, Junyong Liu, Lijun Yin. Summary of research on intelligent sales and marketing of smart grid (3) research vision of essential issues. Electric Power Automation Equipment, Vol. 30 (2010), pp.139-149.

Google Scholar