The role of demand response in residential electricity load reduction using appliance shifting techniques

Purpose Some of the major concerns since the implementation of smart meters (prepaid meters) in some parts of Ghana is how electricity consumers have benefited from data obtained from these meters by providing important statistics on electricity-saving advice; this is one of the key demand-side mana...

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Bibliographic Details
Published in:International journal of energy sector management 2022-05, Vol.16 (4), p.605-635
Main Authors: Avordeh, Timothy King, Gyamfi, Samuel, Opoku, Alex Akwasi
Format: Article
Language:English
Subjects:
Air conditioning
Algorithms
Alternative energy sources
Appliances
Behavior
Capital costs
Consumer behavior
Consumers
Controllers
Cooking
Demand side management
Electric power demand
Electrical loads
Electricity
Electricity consumption
Electricity meters
Electricity pricing
End users
Energy consumption
Energy industry
Energy management
Energy storage
Household appliances
Households
Human behavior
Load shifting
Management methods
Manufacturing
Peak demand
Peak load
Refrigerators
Residential energy
Statistical analysis
Tariffs
Time dependence
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Summary:Purpose Some of the major concerns since the implementation of smart meters (prepaid meters) in some parts of Ghana is how electricity consumers have benefited from data obtained from these meters by providing important statistics on electricity-saving advice; this is one of the key demand-side management methods for achieving load reduction in residential homes. Appliance shifting techniques have proved to be an effective demand response strategy in load reduction. The purpose of this paper is therefore to help consumers of electricity understand when and how they can shift some appliances from peak to off-peak and vice versa. Design/methodology/approach The research uses an analysis technique of Richardson et al. (2010). In their survey on time-of-use surveys to determine the usage of electricity in households as far as appliance shifting was concerned, this study allowed for the assessment of how the occupants’ daily activities in households affect residential electricity consumption. Fell et al. (2014) modeled an aggregate of electricity demand using different appliances ( n ) in the household. The data for the peak time used in this study were identified from 05:00 to 08:00 and 17:00 to 21:00 for testing the load shifting algorithms, and the off-peak times were pecked from 10:00 to 16:00 and 23:00. This study technique used load management considering real-time scheduling for peak levels in the selected homes. The household devices are modeled in terms of controlled parameters. Using this study’s time-triggered loads on refrigerators and air conditioning systems, the findings suggested that peak loads can be reduced to 45% as a means of maintaining the simultaneous quality of service. To minimize peak loads to around 35% or more, Chaiwongsa and Wongwises (2020) have indicated that room air conditioning and refrigerator loads are simpler to move compared to other household appliances such as cooking appliances. Yet in conclusion, this study made a strong case that a decrease in household peak demand for electricity is primarily contingent on improvements in human behavior. Findings This study has shown that appliance load shifting is a very good way of reducing electrical consumption in residential homes. The comparative performance shows a moderate reduction of 1% in load as was found in the work done by Laicaine (2014). The results, however, indicate that load shifting to a large extent can be achieved by consumer behavioral change. The main response
ISSN:1750-6220
1750-6239
DOI:10.1108/IJESM-05-2020-0014