Research and Application for Power-Grid Comprehensive Distribution Decision System
- DOI
- 10.2991/ammsa-18.2018.80How to use a DOI?
- Keywords
- power-grid planning; statistical data model; decision-making requirements; robust reregulation; universal adaptation
- Abstract
High-efficiency power-grid planning is used to ensure the benefits and smooth operation of power-grid companies and industries. In order to solve the planning management business, such as the enterprise overall planning, power-grid planning and early planning, and its decision analysis issues, such as comprehensive planning, investment planning, production planning, etc. This paper proposes some statistical data models for power-grid planning decision and its applications. With some quantitative and data information analysis, the different decisions are designed for different plans and mathematical analysis methods are provided to decision makers. Taking the common decision analysis model as the carrier, a specific and applicable logic model is proposed with power-grid companies' business characteristics and decision-making requirements. The experimental results show that this power-grid planning method has the features of robust reregulation and universal adaptation with same types, which implied that the optimization constraints of this model are matching with the actual conditions and further ensuring the credibility and practicality of the power-grid planning.
- Copyright
- © 2018, 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 - Qian Gao AU - Shangyuan Wu AU - Junyi Yang AU - Kai Zhang AU - Chao Xu PY - 2018/05 DA - 2018/05 TI - Research and Application for Power-Grid Comprehensive Distribution Decision System BT - Proceedings of the 2018 2nd International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2018) PB - Atlantis Press SP - 382 EP - 384 SN - 1951-6851 UR - https://doi.org/10.2991/ammsa-18.2018.80 DO - 10.2991/ammsa-18.2018.80 ID - Gao2018/05 ER -