Optimal RTP Based Power Scheduling for Residential Load in Smart Grid

Joshi, Hemant; Pandya, Vivek

doi:10.1007/s40031-014-0112-1

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…As mentioned in [40], almost 68.9% of electrical loads are comprised of brushless DC motors; LED lights and PCs and telecom gadgets accept DC power. Before it is applied to the load, the DC is converted into AC by using inverters.…”

Section: Dsm In Nanogrid Microgrid and Smart Gridmentioning

confidence: 99%

Variable Load Demand Scheme for Hybrid AC/DC Nanogrid

Rauf

Kalair

Khan

2020

International Journal of Photoenergy

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This paper addresses the use of nanogrid technology in resolving the issue of blanket load shedding for domestic consumers. This is accomplished by using different load management techniques and load classification and utilizing maximum solar energy. The inclusion of DC-based load in basic load and DC inverter load in regular load and scheduling of the burst load during the hours of maximum solar PV generation bring novelty in this work. The term “nanogrid” as a power structure remains ambiguous in various publications so far. An effort has been done in this paper to present a concise definition of nanogrid. Demand side load management is one of the key features of nanogrid, which enables end users to know major characteristics about their energy consumption during peak and off-peak hours. A microgrid option with nanogrid facility results in a more reliable system with overall improvement in efficiency and reduction in carbon emission. PV plants produce DC power; when used directly, the loss will automatically be minimized to 16%. The AC/DC hybrid nanogrid exhibits 63% more efficiency as compared to AC-only nanogrid and nearly 18% more efficiency as compared to DC-only nanogrid. Smart load shifting smoothens the demand curve 54% more adequately than during conventional load shifting. Simulation results show that real-time pricing is more economical than flat rate tariff for a house without DG, whereas flat rate results are more economical when DG are involved in nanogrids. 12.67%-21.46% saving is achieved if only flat rates are used for DG in nanogrid instead of real-time pricing.

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Section: Dsm In Nanogrid Microgrid and Smart Gridmentioning

confidence: 99%

Variable Load Demand Scheme for Hybrid AC/DC Nanogrid

Rauf

Kalair

Khan

2020

International Journal of Photoenergy

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“…In [18], an optimal load scheduling algorithm is used and simulation results showed up to 20% and 100% reduction in the payment cost and peak demand, respectively. The paper in [19] discussed the RTP and customers' preferences as an approach to reduce energy expenses and delay time while operating the appliances but the approach is less focused on peak moderation. A priority-induced DSM strategy using HEMC based on GA, EDE, BPSO and OSR scheme is proposed in [18] to minimize consumers' electricity payment cost while maintaining user comfort.…”

Section: Introductionmentioning

confidence: 99%

Optimal residential load scheduling under dynamic pricing and demand-side management

Hussain¹,

Yan²,

Shair³

et al. 2021

Int. J. Front. Eng. Tech. Res.

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Balancing electricity consumption and generation in the residential market is essential for power grids. The imbalance of power scheduling between energy supply and demand would definitely increase costs to both the energy provider and customer. This paper proposes a control function to normalize the peak cost and customer discomfort. In this work, we modify an optimization power scheduling scheme by using the inclined-block rate (IBR) and real-time price (RTP) technique to achieve a desired trade-off between electricity payment and consumer discomfort level. For discomfort, an average time delay between peak and off-peak is proposed to minimize waiting time. The simulation results present our model more practical and realistic with respect to the consumption constrained at peak hours.

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Home Electrical Energy Management System Using DijCostMin Algorithm

Akbar

Halomoan

Silalahi

2020

J. Phys.: Conf. Ser.

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In the afternoon until night, an electrical load is increased, it happened because to increase the usage of electrical devices by customers. These conditions in which increased electricity consumption by buyers at the same time with the quantity a large power have not been able to handle properly by PLN as the supplier of electrical energy in Indonesia. The impact is the occurrence of the power outage in rotation, to reduce these all, needs to be setting the use of electric power appropriate, in order to achieve the purpose of balance between demand and supply for electricity energy; especially on the household sectors. One of the tricks is enacting the management of the load on the side of their customers or well known as Demand-Side Management (DSM) and apply dynamic pricing on electricity tariff from the peak time and non-peak time. Home Electrical Energy Management System (HEEMS) is a system for managing electrical energy-based method DSM and apply dynamic pricing. HEEMS allows users to manage and monitor the usage of electricity. HEEMS serves to do scheduling on the use of an electrical device DijCostMin Algorithm based on data planning the use of devices electricity or load forecasting entered by users. The method that proposed is a success and effective to reduce energy demand is about 22.69% when peak time and reduce bills of electricity is about 8.38%.

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Optimal RTP Based Power Scheduling for Residential Load in Smart Grid

Cited by 3 publications

References 8 publications

Variable Load Demand Scheme for Hybrid AC/DC Nanogrid

Variable Load Demand Scheme for Hybrid AC/DC Nanogrid

Optimal residential load scheduling under dynamic pricing and demand-side management

Home Electrical Energy Management System Using DijCostMin Algorithm

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