Development of Infrastructue for Residential Load to Reduce Peak Demand and Cost of Energy in Smart Grid

I., Joshi Hemant; Choksi, Hemish R.

doi:10.17148/ijireeice.2015.3327

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…The sensing functionality is carried out by different types of embedded sensors and smart meters to detect the status of different areas of the grid in a real-time manner. The smart grid should support the two-way data transmission links between the control centers and the sensors [56]. Control instructions are transmitted from/to sensors or smart meters fixed in different places to support reliable and stable access to grid components and also to guarantee the high-performance operations of the smart grid.…”

Section: Case Studymentioning

confidence: 99%

The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

et al. 2018

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Prior studies in Wireless Sensor Network (WSN) optimization mostly concentrate on maximizing network coverage and minimizing network energy consumption. However, there are other factors that could affect the WSN Quality of Service (QoS). In this paper, four objective functions that affect WSN QoS, namely end-to-end delay, end-to-end latency, network throughput and energy efficiency are studied. Optimal value of packet payload size that is able to minimize the end-to-end delay and end-to-end latency, while also maximizing the network throughput and energy efficiency is sought. To do this, a smart grid application case study together with a WSN QoS model is used to find the optimal value of the packet payload size. Our proposed method, named Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP), along with other three state-of-the-art multi-objective optimization algorithms known as OMOPSO, NSGA-II and SPEA2, are utilized in this study. Different packet payload sizes are supplied to the algorithms and their optimal value is derived. From the experiments, the knee point and the intersection point of all the obtained Pareto fronts for all the algorithms show that the optimal packet payload size that manages the trade-offs between the four objective functions is equal to 45 bytes. The results also show that the performance of our proposed MOSFP method is highly competitive and found to have the best average value compared to the other three algorithms. Furthermore, the overall performance of MOSFP on four objective functions outperformed OMOPSO, NSGA-II and SPEA2 by 3%, 6% and 51%, respectively.

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Section: Case Studymentioning

confidence: 99%

The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

et al. 2018

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“…Where C hmg is the cost to get PL from in-house mini microgrid, P hmg is price for bidding and H hbm is hourly payback amount of investment. P hmg is the sum of multiple factors as shown in Equation (3).…”

Section: Details Of Oelcmentioning

confidence: 99%

Optimizing Electricity Load and Cost for Demand Side Management in Smart Grid

Afzaal

Nazir

2018

Mehran Univ. res. j. eng. technol.

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This paper proposes a mechanism for OELC (Optimizing Electricity Load and Cost) for smart grid. The load of every smart home is predicted one-hour prior to their actual usage. To fulfill PL (Predicted Load) of each consumer, multiple resources of electricity are considered, including RE (Renewable Energy) resources. Furthermore, cost to get PL from multiple resources is calculated. In proposed model 3-4 smart homes are grouped in the form of clusters. To reduce the amount of electricity bills, system also allows privileges to share electricity between adjacent smart homes within a cluster. To validate the OELC mechanism, extensive numerical simulations are conducted which shows a significant reduction in electricity load and cost for electricity consumers. In future, to enhance the functionality of OELC, security from cyber-attacks can be considered

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“…The power will be provided to remaining appliances in the next time slot of off-peak hours. In this way grid remains stable and the cost of electricity for end consumer is reduced [3]. Spiliotis et.…”

Section: Optimizing Electricity Load and Cost For Demand Side Managemmentioning

confidence: 99%

Optimizing Electricity Load and Cost for Demand Side Management in Smart Grid

Afzaal

Nazir

2018

Mehran Univ. res. j. eng. technol.

View full text Add to dashboard Cite

show abstract

Development of Infrastructue for Residential Load to Reduce Peak Demand and Cost of Energy in Smart Grid

Cited by 4 publications

References 9 publications

The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

Optimizing Electricity Load and Cost for Demand Side Management in Smart Grid

Optimizing Electricity Load and Cost for Demand Side Management in Smart Grid

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