基于离线优化和在线决策的光伏智能楼宇能量管理算法

doi:10.11930/j.issn.1004-9649.201805167

中国电力 ›› 2019, Vol. 52 ›› Issue (10): 123-131.DOI: 10.11930/j.issn.1004-9649.201805167

基于离线优化和在线决策的光伏智能楼宇能量管理算法

史训涛¹, 雷金勇¹, 黄安迪¹, 喻磊¹, 郭晓斌¹, 邹福强², 刘念²

1. 南方电网科学研究院, 广东广州 510080;
2. 新能源电力系统国家重点实验室(华北电力大学), 北京 102206

收稿日期:2018-05-25 修回日期:2019-01-09 出版日期:2019-10-05 发布日期:2019-10-12
作者简介:史训涛(1986-),男,工程师,从事智能配电技术研究工作,E-mail:shixt@csg.cn
基金资助:
国家重点研发计划资助项目（2017YFB0903400）；南方电网公司科技项目（SEPRI-K185035）。

An Energy Management Algorithm of PV-Assisted Smart Building Based on Offline Optimization and Online Decision

SHI Xuntao¹, LEI Jinyong¹, HUANG Andi¹, YU Lei¹, GUO Xiaobin¹, ZOU Fuqiang², LIU Nian²

1. Electric Power Research Institute, China Southern Power Grid, Guangzhou 510080, China;
2. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China

Received:2018-05-25 Revised:2019-01-09 Online:2019-10-05 Published:2019-10-12
Supported by:
This work is supported by National Key Research and Development Program of China (No.2017YFB0903400); the Science and Technology Project of China Southern Power Grid (No.SEPRI-K185035).

摘要/Abstract

摘要： 作为综合能源的重要发展形态，光伏智能楼宇的用电需求及光功率具有极大的不确定性，现有的能量管理方法很难完全适用，因此提出了基于离线优化和在线决策的光伏智能楼宇能量管理算法。首先，结合光伏智能楼宇的历史运行数据，建立了以运营收益最大化为目标的离线优化模型，通过离线优化为在线学习提供知识库；其次，为了实现分时电价条件下光伏智能楼宇的实时调度，建立了在线学习与认知规则相结合的在线决策算法，实时决策电动汽车充电功率以及可平移负荷的工作状况；最后，以某商业楼宇为例进行了仿真测试，结果表明所提算法在未来光功率、充电需求及可平移负荷未知的情况下具有良好的运行效果。

关键词: 光伏智能楼宇, 电动汽车, 可平移负荷, 光伏系统, 在线决策, 能量管理

Abstract: As an important development form of comprehensive energy, the charging demand and PV power of PV-assisted smart buildings have great uncertainty. The existing methods of energy management of PV-assisted smart buildings are not completely applicable. An energy management algorithm of PV-assisted smart building based on offline optimization and online decision is proposed in this paper. Firstly,combined with the historical operation data of photovoltaic intelligent buildings, an offline optimization model aiming at maximizing operating income is established, which provides a knowledge base for online learning through offline optimization. Then, in order to dispatch the smart building energy in real-time, under the condition of time-of-use price, the online algorithm is established combined with online learning and rule-based. The charging power of EVs and working conditions of shiftable loads can be decided using the online algorithm. Finally, taking a business building as an example, the proposed algorithm is tested. The simulation results show that the method can be operated without future information of PV power, charging demand and shiftable loads.

Key words: PV-assisted smart building, electric vehicle, suitable load, PV system, online decision, energy management

中图分类号:

TM615

史训涛, 雷金勇, 黄安迪, 喻磊, 郭晓斌, 邹福强, 刘念. 基于离线优化和在线决策的光伏智能楼宇能量管理算法[J]. 中国电力, 2019, 52(10): 123-131.

SHI Xuntao, LEI Jinyong, HUANG Andi, YU Lei, GUO Xiaobin, ZOU Fuqiang, LIU Nian. An Energy Management Algorithm of PV-Assisted Smart Building Based on Offline Optimization and Online Decision[J]. Electric Power, 2019, 52(10): 123-131.

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https://www.electricpower.com.cn/CN/Y2019/V52/I10/123

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基于离线优化和在线决策的光伏智能楼宇能量管理算法

An Energy Management Algorithm of PV-Assisted Smart Building Based on Offline Optimization and Online Decision

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基于离线优化和在线决策的光伏智能楼宇能量管理算法

An Energy Management Algorithm of PV-Assisted Smart Building Based on Offline Optimization and Online Decision

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