Optimization Research of AC/DC Power Grid Considering Complementary Characteristics of Multiple Power Source
- https://doi.org/10.2991/aiea-16.2016.44How to use a DOI?
- AC/DC system; Wind power generation; Photovoltaic power generation; Energy storage system; Quantum optimizing.
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/aiea-16.2016.44 ID - Liu2016/11 ER -