Neural Network Based Demand Side Management Using Load Shifting

Hemanth, G. R.; Raja, S. Charles; Suganya, S.; Venkatesh, P.

doi:10.1109/npec.2018.8476754

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…It uses a human-in-loop approach to shift the loads considering the probability density function of consumer's usage pattern of appliances and cost function. In [25], the major objective of DSM, i.e., cost reduction, is achieved by using the load shifting technique. For sample test, industrial load comprising of 109 appliances is tested.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Recent Challenges and Methodologies in Smart Grid Demand Side Management: State-of-the-Art Literature Review

Nasir¹,

Bukhari

Raza³

et al. 2021

Mathematical Problems in Engineering

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The concept of smart grid was introduced a decade ago. Demand side management (DSM) is one of the crucial aspects of smart grid that provides users with the opportunity to optimize their load usage pattern to fill the gap between energy supply and demand and reduce the peak to average ratio (PAR), thus resulting in energy and economic efficiency ultimately. The application of DSM programs is lucrative for both utility and consumers. Utilities can implement DSM programs to improve the system power quality, power reliability, system efficiency, and energy efficiency, while consumers can experience energy savings, reduction in peak demand, and improvement of system load profile, and they can also maximize usage of renewable energy resources (RERs). In this paper, some of the strategies of DSM including peak shaving and load scheduling are highlighted. Furthermore, the implementation of numerous optimization techniques on DSM is reviewed.

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Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Recent Challenges and Methodologies in Smart Grid Demand Side Management: State-of-the-Art Literature Review

Nasir¹,

Bukhari

Raza³

et al. 2021

Mathematical Problems in Engineering

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“…Artificial neural network (ANN) is the network containing artificial neurons that are modeled based on human brain. A DSM technique incorporating load shifting approach was presented in [20]. A test system containing 109 devices is taken into consideration and a neural network is used to minimize mean square error.…”

Section: E Artificial Neural Network Based Dsmmentioning

confidence: 99%

Role of Demand Side Management Techniques in Reducing Electricity Demand of Residential Users

Mahin

Ahmed

Huq

et al. 2019

EJECE

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Demand of electrical energy is growing day by day worldwide. To meet this increasing demand, generation is needed to be increased subsequently. Increasing generation is not an easy task as it may require setting up new generating units, changing transmission lines, control equipments, etc. Moreover, increased generation also causes increased environment pollution. An alternate approach that can create balance between demand and supply of electricity without increasing generation is demand side management (DSM). Furthermore, demand side management has the potential to reduce the use of energy resources resulting in less environment pollution. In this paper, three DSM techniques: using solar system, load limiting, deliberate load reduction are applied for residential users of Dhaka, Bangladesh and the results are compared with two traditional techniques: energy efficiency, direct load control. It has been found that by using solar system at home significant amount of electrical energy can be saved.

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