Optimal Appliances Scheduling of Home Energy Management System Using Dynamic Programming Method for Auto Demand Response

Chen, Chang; Lee, Sheng-Hung; Wu, Ruay‐Nan; Lee, Chung-Heng

doi:10.1109/icce-tw46550.2019.8991994

Cited by 2 publications

(3 citation statements)

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“…Optimization studies are available in the literature that focus on a single optimization goal of reducing total electricity costs by scheduling the operation of consumer devices. A multiperiod consumer management methodology is proposed for scheduling the loads, considering different types of demand response and supply options under a dynamic pricing scheme [8]. To reduce costs under the time of use (TOU) pricing plan, mixed integer linear programming (MILP) is utilized to schedule residential appliances optimally while taking solar PV and battery energy storage system (BESS) installation into account [9].…”

Section: Literature Review Of Related Workmentioning

confidence: 99%

“…Depending on the matriarch's position, each elephant in the clan 𝑝𝑒 will shift positions. In the following iteration, 𝑝𝑒 will update the position for the elephant in the clan as per (8).…”

Section: Optimal Scheduling Of Loads By Deho Algorithmmentioning

confidence: 99%

“…𝑝𝑒 𝑗 +1 = 𝑝𝑒 𝑗 + 𝜌 * (𝑝𝑏𝑒𝑠𝑡 𝑗 − 𝑝𝑒 𝑗 ) * 𝑟 (8) 𝑝𝑒 𝑗 +1 1 and 𝑝𝑒 𝑗 are the newly updated and old positions for the elephant 𝑒 in the clan 𝑝𝑒 respectively. 𝜌 € [0,1] is the scale factor that determines the impact of the matriarch in clan 𝑝𝑖 on the elephant 𝑒.…”

Section: Optimal Scheduling Of Loads By Deho Algorithmmentioning

confidence: 99%

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Optimal scheduling and demand response implementation for home energy management

Priolkar,

Sreeraj

2024

IJECE

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The optimal scheduling of the loads based on dynamic tariffs and implementation of a direct load control (DLC) based demand response program for the domestic consumer is proposed in this work. The load scheduling is carried out using binary particle swarm optimization and a newly prefaced nature-inspired discrete elephant herd optimization technique, and their effectiveness in minimization of cost and the peak-to-average ratio is analyzed. The discrete elephant herd optimization algorithm has acceptable characteristics compared to the conventional algorithms and has determined better exploring properties for multi-objective problems. A prototype hardware model for a home energy management system is developed to demonstrate and analyze the optimal load scheduling and DLC-based demand response program. The controller effectively schedules and implements DLC on consumer devices. The load scheduling optimization helps to improve PAR by a value of 2.504 and results in energy cost savings of ₹ 12.05 on the scheduled day. Implementation of DLC by 15% results in monthly savings of ₹ 204.18. The novelty of the work is the implementation of discrete elephant herd optimization for load scheduling and the development of the prototype hardware model to show effects of both optimal load scheduling and the DLC-based demand response program implementation.

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Section: Literature Review Of Related Workmentioning

confidence: 99%

Section: Optimal Scheduling Of Loads By Deho Algorithmmentioning

confidence: 99%

Section: Optimal Scheduling Of Loads By Deho Algorithmmentioning

confidence: 99%

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