面向智能电网需求侧管理的电力负荷与成本优化

A. Afzaal, M. Nazir
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引用次数: 2

摘要

提出了一种智能电网负荷与成本优化机制。每个智能家居的负荷都是在实际使用前一小时预测的。为了满足每个消费者的预期负荷,考虑了多种电力资源,包括可再生能源资源。此外,还计算了从多个资源中获取PL的成本。在提出的模型中,3-4个智能家居以集群的形式分组。为了减少电费,该系统还允许在集群内相邻的智能家庭之间共享电力。为了验证OELC机制,进行了大量的数值模拟,结果显示电力用户的电力负荷和成本显著降低。未来,为了增强OELC的功能,可以考虑防止网络攻击的安全性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing Electricity Load and Cost for Demand Side Management in Smart Grid
This paper proposes a mechanism for OELC (Optimizing Electricity Load and Cost) for smart grid. The load of every smart home is predicted one-hour prior to their actual usage. To fulfill PL (Predicted Load) of each consumer, multiple resources of electricity are considered, including RE (Renewable Energy) resources. Furthermore, cost to get PL from multiple resources is calculated. In proposed model 3-4 smart homes are grouped in the form of clusters. To reduce the amount of electricity bills, system also allows privileges to share electricity between adjacent smart homes within a cluster. To validate the OELC mechanism, extensive numerical simulations are conducted which shows a significant reduction in electricity load and cost for electricity consumers. In future, to enhance the functionality of OELC, security from cyber-attacks can be considered
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