Editing IPCC:AR6/WGIII/Chapter-9 (section)

==== 9.4.3.2 Appliances and Lighting ====

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Electrical appliances have a significant contribution to household electricity consumption ( [[#Pothitou--2017|Pothitou et al. 2017]] ). Ownership of appliances, the use of appliances, and the power demand of the appliances are key contributors to domestic electricity consumption ( [[#Jones--2015|Jones et al. 2015]] ). The drivers in energy use of appliances are the appliance type (e.g., refrigerators), number of households, number of appliances per household, and energy used by each appliance ( [[#Chu--2006|Chu and Bowman 2006]] ; [[#Cabeza--2014|Cabeza et al. 2014]] ; [[#Spiliotopoulos--2019|Spiliotopoulos 2019]] ). At the same time, household energy-related behaviours are also a driver of energy use of appliances ( [[#Khosla--2019|Khosla et al. 2019]] ) ( [[#9.5|Section 9.5]] ). Although new technologies such as IoT linked to the appliances increase flexibility to reduce peak loads and reduce energy demand ( [[#Kramer--2020|Kramer et al. 2020]] ), trends show that appliances account for an increasing amount of building energy consumption (Figure 9.8). Appliances used in Developed Countries consume electricity and not fuels (fossil or renewable), which often have a relatively high carbon footprint. The rapid increase in appliance ownership ( [[#Cabeza--2018b|Cabeza et al. 2018b]] ) can affect the electricity grid. Moreover, energy intensity improvement in appliances such as refrigerators, washing machines, TVs, and computers has counteracted the substantial increase in ownership and use since the year 2000 (International Energy Agency 2019b).

But appliances are also a significant opportunity for energy efficiency improvement. Research on energy efficiency of different appliances worldwide showed that this research focused in different time frames in different countries (Figure 9.12). This figure presents the number of occurrences of a term (the name of a studied appliance) appearing per year and per country, according to the references obtained from a Scopus search. The figure shows that most research carried out was after 2010. And again, this figure shows that research is mostly carried out for refrigerators and for brown appliances such as smart phones. Moreover, the research carried out worldwide is not only devoted to technological aspects, but also to behavioural aspects and quality of service (such as digital television or smart phones).

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[[File:a72b324a6d6a060c609085cfabe07c8b IPCC_AR6_WGIII_Figure_9_12.png]]

'''Figure 9.12''' | '''Energy efficiency in appliances research.''' Year and number of occurrences of different appliances in each studied country/territory.

Lighting energy accounts for around 19% of global electricity consumption ( [[#Attia--2017|Attia et al. 2017]] ; [[#Enongene--2017|Enongene et al. 2017]] ; [[#Baloch--2018|Baloch et al. 2018]] ). Many studies have reported the correlation between the decrease in energy consumption and the improvement of the energy efficiency of lighting appliances (Table 9.1). Today, the new standards recommend the phase out of incandescent light bulbs, linear fluorescent lamps, and halogen lamps and their substitution by more efficient technologies such as compact fluorescent lighting (CFL) and light-emitting diodes (LEDs) (Figure 9.8). Due to the complexity of these systems, simulation tools are used for the design and study of such systems, which can be summarised in [[#Baloch--2018|Baloch et al. (2018)]] .

Single-phase induction motors are extensively used in residential appliances and other building low-power applications. Conventional motors work with fixed speed regime directly fed from the grid, giving unsatisfactory performance (low efficiency, poor power factor, and poor torque pulsation). Variable speed control techniques improve the performance of such motors ( [[#Jannati--2017|Jannati et al. 2017]] ).

Within the control strategies to improve energy efficiency in appliances, energy monitoring for energy management has been extensively researched. [[#Abubakar--2017|Abubakar et al. (2017)]] present a review of those methods. The paper distinguishes between intrusive load monitoring (ILM), with distributed sensing, and non-intrusive load monitoring (NILM), based on a single point sensing.

'''Table 9.1 | Typesof domestic lighting devices and their characteristics.''' Source: adapted from [[#Attia--2017|Attia et al. (2017)]] .

{| class="wikitable"
|-
| '''Type of lighting device'''

| '''Code in plan'''

| '''Lumens per watt [lm W''' –1 ''']'''

| '''Colour temperature [K]'''

| '''Lifespan [h]'''

| '''Energy use [W]'''

|-
| Incandescent

| InC

| 13.9

| 2700

| 1000

| 60

|-
| Candle incandescent

| CnL

| 14.0

| 2700

| 1000

| 25

|-
| Halogen

| Hal

| 20.0

| 3000

| 5000

| 60

|-
| Fluorescent TL8

| FluT8

| 80.0

| 3000–6500

| 20,000

| 30–40

|-
| Compact fluorescent

| CfL

| 66.0

| 2700–6500

| 10,000

| 20

|-
| LED GLS

| LeD

| 100.0

| 2700–5000

| 45,000

| 10

|-
| LED spotlight

| LeD Pin

| 83.8

| 2700–6500

| 45,000

| 8

|-
| Fluorescent T5

| FluT5

| 81.8

| 2700–6500

| 50,000

| 22

|-
| LED DT8

| LeDT8

| 111.0

| 2700–6500

| 50,000

| 15

|}

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