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Demand Side Management for Smart Houses: A Survey

doi: 10.3390/su13126768
Continuous advancements in Information and Communication Technology and the emergence of the Big Data era have altered how traditional power systems function. Such developments have led to increased reliability and efficiency, in turn contributing to operational, economic, and environmental improvements and leading to the development of a new technique known as Demand Side Management or DSM. In essence, DSM is a management activity that encourages users to optimize their electricity consumption by controlling the operation of their electrical appliances to reduce utility bills and their use during peak times. While users may save money on electricity costs by rescheduling their power consumption, they may also experience inconvenience due to the inflexibility of getting power on demand. Hence, several challenges must be considered to achieve a successful DSM. In this work, we analyze the power scheduling techniques in Smart Houses as proposed in most cited papers. We then examine the advantages and drawbacks of such methods and compare their contributions based on operational, economic, and environmental aspects.
- United Arab Emirates University United Arab Emirates
- American University of Ras Al Khaimah
- University of Alabama in Huntsville United States
- American University of Ras Al Khaimah
- United Arab Emirates University United Arab Emirates
demand side management, Environmental effects of industries and plants, TJ807-830, power scheduling, TD194-195, Renewable energy sources, Environmental sciences, smart grids, GE1-350
demand side management, Environmental effects of industries and plants, TJ807-830, power scheduling, TD194-195, Renewable energy sources, Environmental sciences, smart grids, GE1-350
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).9 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
