Progress on the demand side management in smart grid and optimization approaches,International Journal of Energy Research

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Progress on the demand side management in smart grid and optimization approaches
International Journal of Energy Research ( IF 4.3 ) Pub Date : 2020-06-26 , DOI: 10.1002/er.5631
Eity Sarker ₁ , Pobitra Halder ₂ , Mehdi Seyedmahmoudian ₁ , Elmira Jamei ₃ , Ben Horan ₄ , Saad Mekhilef ₅ , Alex Stojcevski ₁

Affiliation

The integration of demand side management (DSM) with smart grid (SG) can facilitate residents' transfer into smart homes and sustainable cities by reducing the carbon emission. This manuscript reviews the recent works related to the application of DSM in SG through discussing the techniques and algorithms and their associated challenges for effective implementation. This paper also critically discusses the operation mode of DSM, the profile of energy production, storage and consumption, and finally the benefit obtained by the DSM implementation. Previous literature suggested that DSM practice reduced peak‐to‐average ratio, energy cost and carbon emission by approximately 10% to 65%, 5% to 50%, and 14%, respectively. The implementation of DSM in SG deals with a number of challenges such as security and privacy, tariff regulation, energy transmission, distribution, and effective utilization of energy resources. A number of international organizations have taken various measures and solutions to guarantee the security and privacy of the DSM in SG discussed. So far, a number of algorithms have been used as optimization approach to solve the DSM optimization problems; however hybrid algorithms have showed better performance than single algorithms due to their faster convergence speed. At the end, the paper presents the research gaps and future research directions.

中文翻译：

智能电网需求侧管理及优化方法的研究进展

需求侧管理（DSM）与智能电网（SG）的集成可通过减少碳排放量，促进居民向智能家居和可持续城市的转移。该手稿通过讨论技术和算法及其有效实施所面临的挑战，回顾了与DSM在SG中的应用相关的最新工作。本文还批判性地讨论了DSM的运行模式，能源生产，存储和消耗的概况以及最终通过DSM实施所获得的收益。以前的文献表明，DSM的实践分别将峰均比，能源成本和碳排放量分别降低了约10％至65％，5％至50％和14％。在SG中实施DSM会遇到许多挑战，例如安全性和隐私，资费监管，能源的传输，分配和能源的有效利用。许多国际组织已采取各种措施和解决方案来保证在SG中讨论DSM的安全性和隐私性。到目前为止，已经使用许多算法作为优化方法来解决DSM优化问题。但是，由于混合算法具有更快的收敛速度，因此它们的性能比单一算法更好。最后，提出了研究空白和未来的研究方向。许多算法已用作解决DSM优化问题的优化方法。但是，由于混合算法具有更快的收敛速度，因此它们的性能比单一算法更好。最后，提出了研究空白和未来的研究方向。许多算法已用作解决DSM优化问题的优化方法。但是，由于混合算法具有更快的收敛速度，因此它们的性能比单一算法更好。最后，提出了研究空白和未来的研究方向。

更新日期：2020-06-26

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