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将车辆到家庭单元集成到智能家庭能源管理系统中的管理模型。

Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System.

作者信息

Almughram Ohoud, Ben Slama Sami, Zafar Bassam

机构信息

Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.

The Applied College, King Abdulaziz University, Jeddah 21589, Saudi Arabia.

出版信息

Sensors (Basel). 2022 Oct 24;22(21):8142. doi: 10.3390/s22218142.

Abstract

Integration of vehicle-to-home (V2H) centralized photovoltaic (HCPV) systems is a requested and potentially fruitful research topic for both industry and academia. Renewable energy sources, such as wind turbines and solar photovoltaic panels, alleviate energy deficits. Furthermore, energy storage technologies, such as batteries, thermal, and electric vehicles, are indispensable. Consequently, in this article, we examine the impact of solar photovoltaic (SPV), microgrid (MG) storage, and an electric vehicle (EV) on maximum sun radiation hours. As a result, an HCPV scheduling algorithm is developed and applied to maximize energy sustainability in a smart home (SH). The suggested algorithm can manage energy demand between the MG and SPV systems, as well as the EV as a mobile storage system. The model is based on several limitations to meet households' electrical needs during sunny and cloudy weather. A multi-agent system (MAS) is undertaken to ensure proper system operation and meet the power requirements of various devices. An experimental database for weather and appliances is deployed to evaluate and control energy consumption and production cost parameters. The obtained results illustrate the benefits of V2H technology as a prospective unit storage solution.

摘要

车辆到家庭(V2H)集中式光伏(HCPV)系统的集成对于工业界和学术界来说都是一个备受关注且可能成果丰硕的研究课题。可再生能源,如风力涡轮机和太阳能光伏板,可缓解能源短缺问题。此外,诸如电池、热能和电动汽车等储能技术也不可或缺。因此,在本文中,我们研究了太阳能光伏(SPV)、微电网(MG)储能和电动汽车(EV)对最大日照小时数的影响。结果,开发并应用了一种HCPV调度算法,以实现智能家居(SH)中的能源可持续性最大化。所建议的算法可以管理微电网和太阳能光伏系统之间的能源需求,以及作为移动储能系统的电动汽车的能源需求。该模型基于若干限制条件,以满足晴天和阴天时家庭的用电需求。采用多智能体系统(MAS)来确保系统正常运行,并满足各种设备的电力需求。部署了一个天气和电器实验数据库,以评估和控制能源消耗及生产成本参数。所得结果表明了V2H技术作为一种潜在的单位储能解决方案的优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96ca/9656865/377711d9a47f/sensors-22-08142-g0A1.jpg

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