Comprehensive framework for smart residential demand side management with electric vehicle integration and advanced optimization techniques.

IF 3.9 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Reports Pub Date : 2025-03-22 DOI:10.1038/s41598-025-93817-5

Subhasis Panda, Indu Sekhar Samanta, Buddhadeva Sahoo, Pravat Kumar Rout, Binod Kumar Sahu, Mohit Bajaj, Vojtech Blazek, Lukas Prokop, Stanislav Misak

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引用次数: 0

Abstract

The exponential deployment of electric vehicles (EVs) in the residential sectors in recent years allows better energy utilization in the decentralized and centralized levels of distribution systems due to their bidirectional operation and energy storage capabilities. However, to execute these, it is necessary to adopt residential demand side management (RDSM) to schedule energy utilization effectively to fetch economical and efficient energy consumption and grid stability and reliability, particularly during peak load conditions. The paper aims to formulate a robust and efficient RDSM technique to provide an energy utilization scheduling considering various influential factors and critical roles of EVs in RDSM. A Binary Whale Optimization Algorithm (BWOA) approach is proposed as an efficient algorithm for EV's impact on the RDSM for better energy scheduling. A single-objective formulation is presented with detailed modelling considering economic energy utilization as the primary objective with all possible equality and inequality system operational constraints. Secondly, the impact of EVs on the RDSM is studied from various perspectives in result analysis, considering EVs as load, storage devices, and different bidirectional modes of operation with other vehicles, residential components, and grids. In addition, the EVs role and the mutual influence with the integration of renewable energy sources (RES) and energy storage devices (ESDs) are extensively analyzed to provide better residential energy management (REM) in terms of economic, environmental, robust, and reliable points of view. The load priority based on consumer choice is also incorporated in the formulation. Extensive simulation is done for the proposed approach to show the effect of EVs on REM, and the results are impressive to show the EV's role as a load, as a storage device, and as a mutually supportive device to RES, ESD, and grid.

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基于电动汽车集成和先进优化技术的智能住宅需求侧管理综合框架。

近年来，电动汽车（ev）在住宅领域的指数级部署，由于其双向运行和储能能力，可以在分散和集中的配电系统中更好地利用能源。然而，要实现这些目标，必须采用居民需求侧管理（RDSM）来有效地安排能源利用，以实现经济高效的能源消耗和电网的稳定和可靠性，特别是在高峰负荷条件下。本文旨在建立一种鲁棒高效的RDSM技术，以提供考虑各种影响因素和电动汽车在RDSM中的关键作用的能量利用调度。针对电动汽车对RDSM的影响，提出了一种有效的双鲸优化算法（BWOA）。以经济能源利用为主要目标，考虑所有可能的相等和不相等系统运行约束，提出了一个单目标公式，并建立了详细的模型。其次，在结果分析中，从多个角度研究了电动汽车对RDSM的影响，考虑了电动汽车作为负载、存储设备，以及与其他车辆、住宅组件和电网的不同双向运行方式。此外，本文还广泛分析了电动汽车在可再生能源（RES）和储能设备（ESDs）整合中的作用和相互影响，以期从经济、环保、稳健和可靠的角度提供更好的住宅能源管理（REM）。基于消费者选择的负载优先级也被纳入到配方中。我们对所提出的方法进行了广泛的模拟，以显示电动汽车对REM的影响，结果令人印象深刻，显示了电动汽车作为负载、存储设备以及作为RES、ESD和电网相互支持的设备的作用。

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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来源期刊

Scientific Reports Natural Science Disciplines-

CiteScore

7.50

自引率

4.30%

发文量

19567

审稿时长

3.9 months

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