杭州供電公司整合多信息源的需求側(cè)管理信息平臺運維及應用的研究
發(fā)布時間：2018-10-30 20:48
【摘要】：近年來世界各國電力行業(yè)開展智能電網(wǎng)的建設,先進的通信技術、分布式發(fā)電技術、先進的測量技術、電動汽車等儲能技術為需求側(cè)管理提供新的技術支持,同時分時電價、實時電價也為需求側(cè)響應提供了更有效的經(jīng)濟激勵。浙江省電力公司經(jīng)過近幾年的努力,完成了多項國家電網(wǎng)公司智能電網(wǎng)試點項目,在“信息化、自動化、互動化”方面得到了很大提升,也為進一步開展智能用電、能效管理和需求側(cè)優(yōu)化決策創(chuàng)造了條件。本文以杭州供電公司為對象,從整合用電信息和氣象信息等實時多信息源,建立多信息源管理平臺出發(fā),建立負荷特性評估指標及相關性分析方法和預測方法,深入挖掘負荷響應的潛力,提出了自上而下的分層分區(qū)有序用電優(yōu)化決策方案和需求側(cè)改進措施。將分析過程加以整合,形成實時用電信息和氣象信息的需求側(cè)管理信息平臺、基于多信息源的負荷特性分析、建立系統(tǒng)一變電站—饋線—用戶的預測-校正集成模型以及分層分區(qū)用電優(yōu)化決策研究、需求側(cè)管理的潛力分析四項研究成果,這對于把握當前智能配電系統(tǒng)大規(guī)模建設的良好時機,充分發(fā)揮智能配電網(wǎng)的潛力,大力提升用電效率、發(fā)揮需求側(cè)管理潛能,為進一步科學用電、合理用電、節(jié)約用電、加強能效管理奠定基礎,對全力推進電力需求側(cè)管理信息平臺和長效機制的建設及促進營銷相關業(yè)務工作的開展具有重要的指導作用
[Abstract]:In recent years, the world's power industry has developed smart grid construction, advanced communication technology, distributed generation technology, advanced measurement technology, electric vehicles and other energy storage technologies to provide new technical support for demand-side management, and at the same time, time-sharing pricing. Real-time electricity price also provides a more effective economic incentive for demand-side response. Through its efforts in recent years, Zhejiang Electric Power Company has completed a number of smart grid pilot projects of the State Grid Corporation, which have been greatly upgraded in terms of "information technology, automation, and interaction," and also for the further development of intelligent electricity use. Energy efficiency management and demand-side optimization decisions create conditions. This paper takes Hangzhou Power supply Company as the object, from the integration of real-time multi-information sources such as power information and meteorological information, sets up the management platform of multi-information sources, and establishes the evaluation index of load characteristics, the methods of correlation analysis and prediction. In this paper, the potential of load response is deeply excavated, and a top-down hierarchical and sub-district optimal power consumption decision scheme and demand-side improvement measures are proposed. The analysis process is integrated to form a demand side management information platform for real-time power and meteorological information, which is based on the load characteristic analysis of multi-information sources. A system-substation feeder user predictive correction integrated model and hierarchical and zonal power optimization decision are established. The potential of demand-side management is analyzed. This will be helpful to grasp the good opportunity of large-scale construction of intelligent distribution system, to give full play to the potential of intelligent distribution network, to improve the efficiency of power consumption, to give full play to the potential of demand side management, and to further scientific, reasonable and economical use of electricity. Strengthening energy efficiency management lays the foundation for promoting the construction of power demand-side management information platform and long-effect mechanism and promoting the development of market-related business work, which plays an important guiding role in promoting the development of electric power demand-side management information platform and long-term mechanism.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM76;TP311.52
本文編號：2301142
[Abstract]:In recent years, the world's power industry has developed smart grid construction, advanced communication technology, distributed generation technology, advanced measurement technology, electric vehicles and other energy storage technologies to provide new technical support for demand-side management, and at the same time, time-sharing pricing. Real-time electricity price also provides a more effective economic incentive for demand-side response. Through its efforts in recent years, Zhejiang Electric Power Company has completed a number of smart grid pilot projects of the State Grid Corporation, which have been greatly upgraded in terms of "information technology, automation, and interaction," and also for the further development of intelligent electricity use. Energy efficiency management and demand-side optimization decisions create conditions. This paper takes Hangzhou Power supply Company as the object, from the integration of real-time multi-information sources such as power information and meteorological information, sets up the management platform of multi-information sources, and establishes the evaluation index of load characteristics, the methods of correlation analysis and prediction. In this paper, the potential of load response is deeply excavated, and a top-down hierarchical and sub-district optimal power consumption decision scheme and demand-side improvement measures are proposed. The analysis process is integrated to form a demand side management information platform for real-time power and meteorological information, which is based on the load characteristic analysis of multi-information sources. A system-substation feeder user predictive correction integrated model and hierarchical and zonal power optimization decision are established. The potential of demand-side management is analyzed. This will be helpful to grasp the good opportunity of large-scale construction of intelligent distribution system, to give full play to the potential of intelligent distribution network, to improve the efficiency of power consumption, to give full play to the potential of demand side management, and to further scientific, reasonable and economical use of electricity. Strengthening energy efficiency management lays the foundation for promoting the construction of power demand-side management information platform and long-effect mechanism and promoting the development of market-related business work, which plays an important guiding role in promoting the development of electric power demand-side management information platform and long-term mechanism.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM76;TP311.52
【參考文獻】
相關期刊論文 前1條
1 康重慶,夏清,張伯明;電力系統(tǒng)負荷預測研究綜述與發(fā)展方向的探討[J];電力系統(tǒng)自動化;2004年17期
，本文編號：2301142
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