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A Novel Fuzzy based Intelligent Demand Side Management for Automated Load Scheduling

机译:自动负载调度的新型模糊基于智能需求副管理

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Developments in smart-grid technologies can be associated with rising awareness among general populace of renewable energy as well as the need of distributed generation via these sources. Improvement in efficiency of electrical energy from Renewable Sources (RS) can be achieved by collaborating advanced structures with intelligent metering technology. The smart meters along with the distributed generation sources are being widely used in smart grid applications. An intelligent energy management system is key to monitor and control the processes at consumer and supplier end. Thus, an intelligent system for various computation and procurements can be considered a part of smart-grid. It is within consideration that a part of the energy demand by the building is covered by this Intelligent Demand Management Structure (IDMS). The IDMS is an indispensable tool in order to guarantee greatest added value to the smart meter. The practical and theoretical integration and application of IDMS with the smart meter is presented in this article. The article proposes a novel algorithm based on fuzzy optimization logic employed to the intended system. Fuzzy Controller Logic (FCL) language was used to create the fuzzy rules while the execution was carried out in Python. The designed algorithm is tested in the real time with the load profile of a practical setup. The proposed FCL based algorithm saved a maximum of 15% energy in best cased scenarios.
机译:智能电网技术的发展可能与可再生能源普通民众的升高意识相关,也可以通过这些来源的分布式发电。通过与智能计量技术合作的先进结构可以实现来自可再生源(RS)的电能的提高。智能仪表以及分布式的发电源广泛用于智能电网应用。智能能源管理系统是监控和控制消费者和供应商最终流程的关键。因此,可以考虑用于各种计算和采购的智能系统是智能电网的一部分。正常考虑到建筑物的一部分能源需求由此智能需求管理结构(IDMS)涵盖。 IDMS是一个不可或缺的工具,以保证智能仪表的最大值。本文提出了具有智能电表的IDM的实用和理论集成和应用。本文提出了一种基于用于预期系统的模糊优化逻辑的新算法。模糊控制器逻辑(FCL)语言用于在Python中执行执行时创建模糊规则。使用实际设置的负载曲线实时测试设计的算法。所提出的FCL基于FCL的算法在最佳的外壳方案中保存了最多15%的能量。

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