Intelligent Decision-Making System Design and Implementation for Distribution Area Construction and Retrofit

被引：0
|
作者：
Duan X. [1 ]
Wang J. [1 ]
Feng D. [1 ]
Li Y. [1 ]
Kou L. [1 ]
Wang L. [1 ]
Zhao X. [1 ]
机构：
[1] SGCC Key Laboratory of Advanced Distribution Automation and Distribution Network Optimization Control (China Electric Power Research Institute), Haidian District, Beijing
来源：
Dianwang Jishu/Power System Technology | 2017年 / 41卷 / 08期
关键词：
Decision system; Distribution area; Online intelligent drawing; Simulation analysis; Supply capability evaluation;
D O I：
10.13335/j.1000-3673.pst.2016.2962
中图分类号：
学科分类号：
摘要：
In order to improve rural distribution area power supply quality and service level, aiming at problems such as low information level, low efficiency, lack of decision-making support and other issues in distribution area planning, construction and retrofit, intelligent decision-making system architecture design for distribution area construction and retrofit is put forward to realize real-time simulation decision-making and online intelligent drawing of distribution area. With application of HTML5 high-speed expansion caching technology, some innovations on integrated design idea are put forward, including data, graphics, account material and model, giving implementation plan of four functions, i.e. power supply capability evaluation, scheme decision-making support, real-time online drawing and basic information management. Combined with actual demand, security design and two kinds of data interface are put forward according to current situation of distribution area data. It can assess actual power supply capacity of distribution area in multiple dimensions, accurately identify main weakness in distribution area power supply, assist distribution area with scientific planning and resource allocation optimization, effectively avoid short- and medium-term reconstruction and improve efficiency and effectiveness of construction and retrofit. Verified in application, the result can effectively enhance distribution area management level, improve decision-making ability of distribution area power supply quality and promote social image of power enterprises. © 2017, Power System Technology Press. All right reserved.
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页码：2709 / 2715
页数：6
相关论文
共 14 条
  • [1] Huang L., Wei Z., Wei Y., Et al., A survey on interactive system and operation patterns of intelligent power utilization, Power System Technology, 37, 8, pp. 2230-2237, (2013)
  • [2] Yan H., Chen S., Zhong M., Et al., Research and design of demand side energy efficiency management and demand response system, Power System Technology, 39, 1, pp. 42-47, (2015)
  • [3] Shi C., Zhang B., Sheng W., Et al., A discussion on technical architecture for flexible intelligent interactive power utilization, Power System Technology, 37, 10, pp. 2868-2874, (2013)
  • [4] Zhang D., Miao X., Liu L., Et al., Research on development strategy for smart grid big data, Proceedings of the CSEE, 35, 1, pp. 2-12, (2015)
  • [5] Fang H., Sheng W., Wang J., Et al., Research on the method for real-time online control of three-phase unbalanced load in distribution area, Proceedings of the CSEE, 35, 9, pp. 817-821, (2015)
  • [6] Deng C., Hou J., Yan J., Et al., Functional design and implementation of online dynamic security assessment and early warning system, Power System Technology, 34, 3, pp. 55-60, (2010)
  • [7] Leite J.B., Mantovani J.R.S., Development of a smart grid simulation environment, Part II:implementation of the advanced distribution management system, Journal of Control Automation and Electrical Systems, 261, 1, pp. 96-104, (2015)
  • [8] Wang Y., Pan Z., Hao H., Et al., Study on multi-objective effect evaluation system of smart grid construction, Journal of Power and Energy Engineering, 3, 4, pp. 85-91, (2015)
  • [9] Liu T., Wang S., Zhang Z., Et al., Newton-Raphson method for theoretical line loss calculation of low-voltage distribution transformer district by using the load electrical energy, Power System Protection and Control, 43, 19, pp. 143-148, (2015)
  • [10] Li H., Sheng W., Zhang X., Et al., Application of improved niche genetic algorithm inreactive power optimization, Power System Technology, 32, 17, pp. 29-34, (2008)
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