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User-Friendly Demand Side Management for Smart Grid Network

机译:用户友好的智能电网网络需求侧管理

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Diverse methods for demand side management (DSM) have been proposed for residential areas. These techniques are effectual in reducing electricity cost by scheduling the customer loads. However, waiting time of user appliances is increased. In this research work a user-friendly technique is developed by using heuristic algorithm to overcome user inconvenience. Genetic algorithm is used for scheduling a residential load in smart grid (SG) network. By using Genetic algorithm in real time pricing (RTP) environment, our main purpose is to minimize both peak to average ratio (PAR), cost of electricity and maximize comfort level in sense of user priority and preferences. To attain our purpose, we categorize appliances according to their duty cycle. We used renewable energy source (RES) to meet peak hours and better scheduling of loads. Simulation work shows that our user-friendly algorithm plays a vital role in load scheduling and reduction in PAR values.
机译:已经针对居住区提出了多种需求侧管理(DSM)方法。这些技术可有效地通过安排客户负载来降低用电成本。但是,用户设备的等待时间增加。在这项研究工作中,通过使用启发式算法来开发一种用户友好的技术,以克服用户的不便。遗传算法用于调度智能电网(SG)网络中的居民负荷。通过在实时定价(RTP)环境中使用遗传算法,我们的主要目的是最大程度地降低峰均比(PAR),用电成本并在用户优先级和偏好方面最大化舒适度。为了达到我们的目的,我们根据设备的占空比对其进行分类。我们使用可再生能源(RES)来满足高峰时间和更好地安排负荷。仿真工作表明,我们的用户友好型算法在负载调度和降低PAR值方面起着至关重要的作用。

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