• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2018, Vol. 39 ›› Issue (9): 18-29.doi: 10.3969/j.issn.1000-7229.2018.09.003

• 综合需求响应 栏目主持 张宁副教授 • 上一篇    下一篇

综合能源系统负荷特性分析及应用研究

张涌新,沈弘,马静   

  1. 新能源电力系统国家重点实验室(华北电力大学),北京市 102206
  • 出版日期:2018-09-01
  • 作者简介:张涌新(1996),男,硕士研究生,主要研究方向为多能源系统负荷预测、电力系统优化控制; 沈弘(1995),男,硕士研究生,主要研究方向为多能源系统负荷预测、电力系统仿真建模; 马静(1981),男,博士,教授,主要研究方向为电力系统保护与控制。

Load Characteristic Analysis and Application Research on Integrated Energy System

ZHANG Yongxin,SHEN Hong,MA Jing   

  1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University),Beijing 102206,China
  • Online:2018-09-01

摘要: 综合能源系统能实现能源高效利用,在应对资源紧缺、环境污染等问题上具有重要意义。综合能源系统负荷特性分析及应用研究是综合能源系统设计、规划、运行的重要环节与工作基础。首先,针对所提综合能源系统负荷特性分析及应用关键问题,建立相应研究框架;随后,提出负荷坏数据辨识修正自动化实现方法;最后,基于研究框架探究实际综合能源系统负荷形态规律、不同类型用能数据增强多元负荷可预测性的可行性及进行电、冷综合需求响应的潜力。结果表明:所提框架及方法能较全面挖掘综合能源系统负荷特性,在提升负荷可预测性、充分发挥综合需求响应潜力等方面起到积极作用。

关键词: 综合能源系统, 负荷特性, 负荷预测, 综合需求响应, 坏数据辨识

Abstract: Integrated energy system can achieve efficient utilization of energy, and is of great significance in dealing with resource shortage and environmental pollution. Load characteristic analysis and application research are the vital parts and working basis of design, planning and operation of an integrated energy system. Aiming at the key problems about load characteristic analysis and application raised by this paper, a research framework is established. Then, the automatic realization method of bad load data identification and correction is put forward for actual integrated energy system load data. At last, based on the research framework, the load profile and law of the system at different time scales, the feasibility of enhancing the predictability of multiple loads with different types of energy data, and the potential of the integrated demand response between power and cold load are explored. The results show that the proposed framework can fully excavate the load characteristics of integrated energy system, and will play an active role in improving the predictability of load and giving full play to the potential of integrated demand response.

Key words: integrated energy system, load characteristics, load forecasting, integrated demand response, bad data identification

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