摘要
电能质量经济性评估对提高电能质量治理经济效益、降低公用电网和电力用户经济损失具有重要意义,合理的经济性评估涉及电能质量监测数据、电气设备参数、用户生产过程和用户财务数据等多方面数据信息,分散在电能质量监测系统、电力设备管理系统和生产管理系统等,难以实现数据的集成和共享。本文基于IEC 61970/IEC 61968标准的公共信息模型提出了适用于电能质量经济性评估的公共信息模型扩展方法。分析了电能质量经济成本组成,从4方面总结提炼了电能质量经济性评估所需的基础数据。以连续型和事件型电能质量问题为出发点,在电能质量经济损失、电能质量量测和电力设备信息3方面建立了电能质量经济性评估公共信息模型,并给出了相关扩展类的重要固有属性,为电能质量经济性评估的数据集成和信息共享奠定基础。
The economic evaluation for power quality mic efficiency of power quality control and reduction is of great significance in the improvement of econo- of economic loss utility and consumers. Reasonable economic involves in the data information in such multiple aspects as the monitoring data of power quality,parameters of electrical equipment,production process and financial data of the customers and those information is spread in the monitoring system of power quality, the management system of electrical equipment and production management system and is difficult to achieve integration and share. In this paper,the expansion method of common information model for the economic evaluation of power quality is based on the common information model in IEC 61970/IEC 61968. The economic cost compos- ition of the power quality is analyzed and basic data for the economic evaluation improvement of power quality is summarized from four aspects. The common information model for the economic evaluation of pow- er quality is established from such three aspects as economic loss of power quality ,power quality meas- urement and information of electrical equipment with the problem of the continuous and event power quality as the starting point ,the important inherent property of related expansion type is given,which lay the foundation data integration and information share of economic evaluation of power quality.
出处
《电力电容器与无功补偿》
北大核心
2016年第6期105-111,共7页
Power Capacitor & Reactive Power Compensation
基金
国家电网公司资助项目(SG121-DL-71-15-006)
关键词
电能质量经济性评估
公共信息模型
事件型电能质量
电能质量数据
economic evaluations for power quality
common information model
event-based power qua- lity
continuous power quality
power quality data.
