Smart Home Scheduling Using Demand Response in the presence of Different Electric Vehicles for Grid Import Cost Reduction | Zendy

S Girish | Zendy; Alexander Aguila Tellez | Zendy; R Harini | Zendy; S Hari Prasath | Zendy; Narayanan Krishnan | Zendy

Open Access

Smart Home Scheduling Using Demand Response in the presence of Different Electric Vehicles for Grid Import Cost Reduction

Author(s) -

S Girish,

Alexander Aguila Tellez,

R Harini,

S Hari Prasath,

Narayanan Krishnan

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3621908

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

This work aims to analyze the impact of usage patterns of multiple and different types of Electric Vehicles (EVs) and schedulable home (Smart Homes) on system reliability and suggest measures to improve system reliability. Distributed Generation (DG) using renewables is a salient feature of a smart grid. However, Renewable Energy Sources (RES) are highly intermittent. During times when energy available from RESs and EVs is lower than the demand, energy may be purchased from the grid at Real Time Price (RTP). Demand Response (DR) is performed on two scales: Incentive-Based Demand Response (IBDR) on the consumer side and Price Based DR (PBDR) on the grid side. Controllable loads are shifted based on RTP of grid at that hour to ensure energy balance in the system. Part of the curtailable load can be shed based on the availability of power depending on the usage patterns of individual customers to ensure reliability. This method of shifting of load ensures that the available renewable resources are utilised to its maximum. The shedding of loads ensure that the cost of electricity for the conusmers are less. In the existing methods of incorporating DR, only shifting of loads is performed thereby affecting the conusmer convenience. Also in the existing methods, only economic consideration is taken, which makes a new peak time in the system. The novelty of this work is analysing the impact of usage patterns with multiple and different types of EVs and implementing DR incorporating individual customer usage pattern for ensuring reliability of the system. Five different cases were analysed and in the presence of EVs and renewable energy sources the smart homes were considered, the SAIDI and SAIFI indices were found to be 0.8253 hours/ customer and 0.8253 interruptions/customer respectively and AENS was 2.9351 kWh/customer as the best result.

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