智能电网环境中数据驱动的需求侧编排

2021 IEEE 8th International Conference on Adaptive Science and Technology (ICAST) Pub Date : 2021-11-25 DOI:10.1109/ICAST52759.2021.9682049

Wisdom O. Okafor, S. Edeagu, Chibuzo C. Ogbonna, O. Iloanusi

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引用次数: 0

摘要

在电力使用领域寻求有意义的生活，寻求通过基于数据的能源管理技术控制消费的形状来优化电力使用和供应。这将导致市场参与者在给定的电力供应与客户高能源需求的变化情况下的电力市场价格预测。在本研究中，智能电表数据同时用于生成有用的数据，以确定电力需求和供应的力量。本文采用伯努利和二项分布模型确定激活基准函数和需求侧分类阈值。结果表明，考虑到主要在非洲国家有限的可用电力资源和不稳定的可再生能源，使用智能电表数据，最大限度地控制和能源管理效率是可能的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Data-Driven Demand Side Orchestration in a Smart Grid Environment

The quest for meaningful living in the area of electricity usage seeks to optimize electricity usage and supply by controlling the shape of consumption via data-based energy management techniques. This leads to electricity market price forecasting for the market participants in the given present varying electric power supply with customers high energy demand. In this research, the smart meter data is concomitantly used to generate useful data for settling forces of demand and supply of electric power. The Bernoulli and Binomial distribution models are used in this paper to determine the activation benchmark function and the demand side classification threshold value. The results show that using smart meter data, maximum control, and energy management efficiency is possible given the limited available power resources and unstable renewable energy sources mainly in African nations.

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2021 IEEE 8th International Conference on Adaptive Science and Technology (ICAST)

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