| 摘要: |
| 基于大数据平台模式下建立科学合理的电量分析预测管理办法及分析预测模型具有重要意义。基于此，设计一种基于用电分析的配网用户用电特性市场分析预测应用系统方案。给出了系统总体方案设计，包括系统总体架构、技术平台架构和大数据分析方法。其次，重点对系统功能架构、源数据平台层、大数据计算平台、系统接口和安全管理进行了方案设计，给出了设计应遵循的原则和技术实现方式。最后，应用系统设计方案中的电力相似月法模型，以广东某市2000~2008年历史用电量数据为基础，进行了实例分析。所设计的应用系统方案，具备对用电市场数据进行深入分析、挖掘的能力，科学预测的能力及提高全局用电市场分析的管理能力，为用电市场的营销服务策略制定提供支撑与保证。 |
| 关键词: 用电特性 市场分析预测 应用系统 大数据平台 电力相似月模型 数据挖掘 |
| DOI：10.7667/PSPC160805 |
| 投稿时间：2016-06-03修订日期：2016-07-21 |
| 基金项目:中国南方电网科技项目资助(GDKJ00000052) |
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| Schematic design of distribution network users' power consumption features market analysis and forecasting application system |
| MA Faxuan |
| (Dongguan Power Supply Bureau of Guangdong Power Grid Co., Ltd., Dongguan 523000, China) |
| Abstract: |
| It’s of great significance to build scientific and rational electricity analysis and forecasting management method and model under big data platform mode. Based on which, a schematic design of application system is developed for market analysis and forecasting of distribution network users’ power consumption features. Scheme design of overall system is given, including system overall framework, technical platform and big data analysis methods. Next, an emphasis is made on schematic design of the system functional architecture, source data platform level, big data computing platform, system interface and security management; and the principles followed by the design and corresponding technical implementation approaches are given. Finally, the power similar month model in designed system scheme is used as an example for case study, based on historical electricity consumption data of certain city in Guangdong Province from year of 2000 to 2008. The designed application system scheme has abilities of deep analysis and data mining and scientific prediction on electricity consumption market data, as well as management ability of improving system-wide and global electricity consumption market analysis, thus provides supports and guarantees for marketing service strategies making of power consumption markets. This work is supported by Science and Technology Projects of China Southern Power Grid (No. GDKJ00000052). |
| Key words: electricity consumption feature market analysis and forecasting application system big data platform power similar month model data mining |
