Optimization Research of AC/DC Power Grid Considering Complementary Characteristics of Multiple Power Source

DOI

10.2991/aiea-16.2016.44How to use a DOI?

Keywords

AC/DC system; Wind power generation; Photovoltaic power generation; Energy storage system; Quantum optimizing.

Abstract

With the rapid development of wind power generation and photovoltaic power generation. The power grid stability influence by randomness and intermittence of wind and solar energy more and more serious. Although the hybrid wind/photovoltaic power generation system with energy storage (HPWS) utilize the complementary characteristics of wind and solar energy, it can improve the power generation system output power stability at some level. However, in the long term the development trend of the large HPWS is realizing the HPWS controllable operation and making the HPWS included in the AC/DC power grid scheduling system. Thence the active power control become a key problem of unite power generation system. In this paper, firstly emphatically introduces the quantum optimizing algorithm, analyze principle and advantages of the algorithm. And build HPWS active power optimization model. The aim for power generation most stability using the quantum optimizing algorithm obtain the model optimal solution. It illustrates the important of the optimal scheduling in the HPWS.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Tao Liu
AU  - Fengmei Cao
AU  - Weihuang Huang
AU  - Zhichao Liu
AU  - Yan Li
AU  - Qiujuan Shi
PY  - 2016/11
DA  - 2016/11
TI  - Optimization Research of AC/DC Power Grid Considering Complementary Characteristics of Multiple Power Source
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 236
EP  - 247
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.44
DO  - 10.2991/aiea-16.2016.44
ID  - Liu2016/11
ER  -