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Integration of SCADA and embedded fuzzy-based load scheduling in Home Energy Management System with grid-connected PV

Sugeng Priyanto

Sugeng Priyanto

Department of Electrical Engineering, National Institute of Technology (ITN)Malang, Indonesia
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Priyanto, Sugeng
, 
Aryuanto Soetedjo

Aryuanto Soetedjo

Department of Electrical Engineering, National Institute of Technology (ITN)Malang, Indonesia
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Soetedjo, Aryuanto
 and 
Irrine Budi Sulistiawati

Irrine Budi Sulistiawati

Department of Electrical Engineering, National Institute of Technology (ITN)Malang, Indonesia
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Sulistiawati, Irrine Budi
  
Apr 27, 2025
Integration of SCADA and embedded fuzzy-based load scheduling in Home Energy Management System with grid-connected PV's Cover Image
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Article Category: Research Article
Published Online: Apr 27, 2025
Received: Sep 15, 2024
DOI: https://doi.org/10.2478/ijssis-2025-0020
Keywords
© 2025 Sugeng Priyanto et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1:

Architecture of home appliance scheduling system. FLC, fuzzy logic controller; SCADA, supervisory control and data acquisition.
Architecture of home appliance scheduling system. FLC, fuzzy logic controller; SCADA, supervisory control and data acquisition.

Figure 2:

Hardware configuration of home appliance scheduling system. HMI, human machine interface; MQTT, message queuing telemetry transport; SCADA, supervisory control and data acquisition.
Hardware configuration of home appliance scheduling system. HMI, human machine interface; MQTT, message queuing telemetry transport; SCADA, supervisory control and data acquisition.

Figure 3:

MQTT data communication. AC, air conditioner; FLC, fuzzy logic controller; HMI, human machine interface; MQTT, message queuing telemetry transport.
MQTT data communication. AC, air conditioner; FLC, fuzzy logic controller; HMI, human machine interface; MQTT, message queuing telemetry transport.

Figure 4:

Design of HMI main display. HMI, human machine interface.
Design of HMI main display. HMI, human machine interface.

Figure 5:

Project manager menu of Haiwell Cloud SCADA software. SCADA, supervisory control and data acquisition.
Project manager menu of Haiwell Cloud SCADA software. SCADA, supervisory control and data acquisition.

Figure 6:

Display designer tool of Haiwell Cloud SCADA software. SCADA, supervisory control and data acquisition.
Display designer tool of Haiwell Cloud SCADA software. SCADA, supervisory control and data acquisition.

Figure 7:

Architecture of FLC-based appliance scheduling. FLC, fuzzy logic controller; OM SCH, microwave oven schedule; RC SCH, rice cooker schedule; WH SCH, water heater schedule; WM SCH, washing machine schedule.
Architecture of FLC-based appliance scheduling. FLC, fuzzy logic controller; OM SCH, microwave oven schedule; RC SCH, rice cooker schedule; WH SCH, water heater schedule; WM SCH, washing machine schedule.

Figure 8:

FLC membership function. FLC, fuzzy logic controller.
FLC membership function. FLC, fuzzy logic controller.

Figure 9:

SCADA HMI main display. HMI, human machine interface; SCADA, supervisory control and data acquisition.
SCADA HMI main display. HMI, human machine interface; SCADA, supervisory control and data acquisition.

Figure 10:

SCADA HMI monitoring and control display. HMI, human machine interface; SCADA, supervisory control and data acquisition.
SCADA HMI monitoring and control display. HMI, human machine interface; SCADA, supervisory control and data acquisition.

Figure 11:

SCADA HMI FLC-based appliance scheduling display. FLC, fuzzy logic controller; HMI, human machine interface; OM SCH, microwave oven schedule; RC SCH, rice cooker schedule; SCADA, supervisory control and data acquisition; WH SCH, water heater schedule; WM SCH, washing machine schedule.
SCADA HMI FLC-based appliance scheduling display. FLC, fuzzy logic controller; HMI, human machine interface; OM SCH, microwave oven schedule; RC SCH, rice cooker schedule; SCADA, supervisory control and data acquisition; WH SCH, water heater schedule; WM SCH, washing machine schedule.

Figure 12:

PV power generation and home appliances’ power consumption profiles during a week.
PV power generation and home appliances’ power consumption profiles during a week.

Figure 13:

PV power generation and home appliances’ power consumption profiles in 1 day.
PV power generation and home appliances’ power consumption profiles in 1 day.

Figure 14:

Non-schedulable appliance power consumption profiles during a week.
Non-schedulable appliance power consumption profiles during a week.

Figure 15:

Microwave oven power consumption profiles during a week.
Microwave oven power consumption profiles during a week.

Figure 16:

Microwave oven power consumption profiles in 1 day.
Microwave oven power consumption profiles in 1 day.

Figure 17:

Rice cooker power consumption profiles during a week.
Rice cooker power consumption profiles during a week.

Figure 18:

Rice power consumption profiles in 1 day.
Rice power consumption profiles in 1 day.

Figure 19:

Water heater power consumption profiles during a week.
Water heater power consumption profiles during a week.

Figure 20:

Water heater power consumption profiles in 1 day.
Water heater power consumption profiles in 1 day.

Figure 21:

Washing machine power consumption profiles during a week.
Washing machine power consumption profiles during a week.

Figure 22:

Washing machine power consumption profiles in 1 day.
Washing machine power consumption profiles in 1 day.

Figure 23:

Energy consumption from the grid profile during a week.
Energy consumption from the grid profile during a week.

Comparison of energy consumption from grid during a week

Method Energy consumption from grid—Accumulation (watt-hours)
Monday Tuesday Wednesday Thursday Friday Saturday Sunday Reduction (%)
Fixed 5,323.05 11,004.72 16,573.01 22,108.64 27,563.92 33,313.99 38,815.19 0
Fuzzy-A 5,355.93 11,035.57 16,611.65 22,089.73 27,514.71 33,190.11 38,493.95 0.8
Fuzzy-B 5,311.13 10,974.73 16,540.05 21,800.74 27,178.19 32,820.40 38,102.80 1.8
Fuzzy-C 5,301.71 10,626.65 16,110.57 21,140.74 26,438.94 31,824.86 37,029.84 4.6

Comparison of daily energy consumption from grid

Method Daily energy consumption from grid (watt-hours)
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
Fixed 5,323.05 5,681.67 5,568.30 5,535.62 5,455.28 5,750.07 5,501.20
Fuzzy-A 5,355.93 5,679.64 5,576.08 5,478.09 5,424.97 5,675.41 5,303.84
Fuzzy-B 5,311.13 5,663.61 5,565.32 5,260.69 5,377.45 5,642.21 5,282.40
Fuzzy-C 5,301.71 5,324.94 5,483.92 5,030.17 5,298.20 5,385.92 5,204.98

Data delivery ratio during real-time simulation

Method Data delivery ratio (%)
Fixed 99.60
Fuzzy-A 99.61
Fuzzy-B 99.56
Fuzzy-C 99.70
Average 99.62

Some fuzzy rules in the second scenario (Fuzzy-B)

No. PV Power H8 PV Power H12 PV Power H15 Weekday RC SCH WH SCH1 WM SCH OM SCH WH SCH2
1 Low Low Low Work 7 8 12 14 15
2 Low Low Low Off 8 9 12 14 15
3 Low Low Med Work 7 8 12 15 16
4 Low Low Med Off 8 9 12 15 16
… … … … … … … … … …
21 Med High Low Work 6 7 10 14 15
22 Med High Low Off 7 8 10 14 15
23 Med High Med Work 6 7 10 15 16
24 Med High Med Off 7 8 10 15 16

Some fuzzy rules in the first scenario (Fuzzy-A)

No. PV Power H8 PV Power H12 PV Power H15 Weekday RC SCH WH SCH1 WM SCH OM SCH WH SCH2
1 Low Low Low Work 6 7 12 15 17
2 Low Low Low Off 8 9 12 14 15
3 Low Low Med Work 6 7 12 15 17
4 Low Low Med Off 8 9 12 15 16
… … … … … … … … … …
21 Med High Low Work 6 7 10 15 17
22 Med High Low Off 7 8 10 14 15
23 Med High Med Work 6 7 10 15 17
24 Med High Med Off 7 8 10 15 16

Some fuzzy rules in the third scenario (Fuzzy-C)

No. PV Power H8 PV Power H12 PV Power H15 Weekday RC SCH WH SCH1 WM SCH OM SCH WH SCH2
1 Low Low Low Work 9 10 12 13 14
2 Low Low Low Off 9 10 12 13 14
3 Low Low Med Work 9 10 12 14 15
4 Low Low Med Off 9 10 12 14 15
… … … … … … … … … …
21 Med High Low Work 8 9 11 13 14
22 Med High Low Off 8 9 11 13 14
23 Med High Med Work 8 9 11 14 15
24 Med High Med Off 8 9 11 14 15
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