An Alternative Low-Cost Embedded NILM System for Household Energy Conservation with a Low Sampling Rate
Abstract
:1. Introduction
2. Principle of Nonintrusive Load Monitoring
- Event detection is the part that detects changes in electrical values that represent a change in the operating conditions of electrical appliances [24];
- Feature extraction of electrical data from the main meter is the extraction of certain features in relation to time;
- Classification is the part that breaks down or groups the electrical appliances that have been analyzed using the features extracted from the meter data.
3. Load Model
- The air conditioner is overloaded when switched on. Active power and inductive reactive power are components of these devices;
- The refrigerator is associated with a very high rise in P–Q when it is first switched on. Active power and inductive reactive power are components of this appliance;
- The electric iron, rice cooker, and kettle are resistive loads that have only active power. After the first time in the range, the electric iron will work for a narrow period like a pulse signal;
- When starting a television, it will switch between high and low active power before it reaches a steady state. Active power and capacitive reactive power are components of these devices;
- Active power and inductive reactive power are components of microwave ovens;
- A washing machine is an appliance that operates in many patterns of electrical power per use.
4. Proposed Embedded NILM Software
- To detect the changes in the data series, we first use change detection by estimating the reference line using polynomial equations and then finding the intersection between the data set and the reference line. If we first find a rising edge and then a falling edge in the same set of data, this indicates a pulsed electrical device. If the timing of the rising edge is far from the timing of the falling edge, an iron or kettle could be in operation.
- A three-point method is used to calculate ∆P and ∆Q [28,29,30,31]. There are nine possible patterns for this method. A Flat–Flat pattern means a stable condition of the load; otherwise, there are instabilities. To find a Flat–Flat pattern, it can be expressed as Equation (1):
- Pre-grouping of ∆P is divided into two conditions: by power size (<400 W and >400 W) and by power factor (unity lagging and leading).
- Four features of symmetry pattern extractions are selected in this article: ∆P, ∆Q, and the amount of intersection points (rising and falling edge) between the active power data and the reference line estimated by polynomial equations, and polynomial curves fitting the starting time of active power.
- Table 2 shows the conditions for classification. We start the grouping with the values ∆P and ∆Q. If the results of discrimination are unclear, the other characteristics must be used, as shown in Table 2, and Equation (2) is used for the final elimination of that grouping which has the most accurate correlation value:
5. Proposed NILM System Implementation
6. Results and Discussion
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Appliance | Percentage of Ownership of Appliance (%) | Average Power (Watts) | Percentage of Energy Consumption in the Residence (%) | Percentage of Energy Consumption in the Country (%) |
---|---|---|---|---|
Lighting | 99.9 | 42 | 9 | 15 |
Electric Fan | 98.8 | 60 | 8 | 14 |
Television | 94.2 | 69 | 8 | 14 |
Rice cooker | 91.4 | 750 | 4 | 6 |
Refrigerator | 90.6 | 103 | 17 | 26 |
Electric iron | 80.2 | 1015 | 1 | 1 |
Kettle | 78.6 | 700 | 1 | 2 |
Washing machine | 68.8 | 267 | 1 | 1 |
Air conditioner | 29.4 | 1150 | 45 | 19 |
Microwave oven | 24.7 | 1310 | 1 | 1 |
Others | - | - | 5 | 1 |
Appliance | Active Power Threshold (W) | Reactive Power Threshold (Var) | Chance to Pulse in One Data Set | Amount of Rising/Falling | Starting Curve Fitting |
---|---|---|---|---|---|
Air conditioner | 950 | 200 | 0 | 1/1 | Overshoot |
Refrigerator | 90 | 80 | 0 | 1/1 | High Overshoot |
Television | 50 | −6 | 0 | 2/1 | 2 Steps |
Electric iron | 1000 | 0 | 3 | 1/1 | 1 Step |
Kettle | 700 | 0 | 1 | 1/1 | 1 Step |
Rice cooker | 600 | 0 | 0 | 1/1 | 1 Step |
Microwave oven | 1350 | 100 | 2 | 2/1 | 2 Steps |
Washing machine | 200 | 120 | 5 | >2/>2 | Triangle |
Appliance | Total Events | TP | FP | FN | TN | Precision | Recall | Accuracy | F1-Score |
---|---|---|---|---|---|---|---|---|---|
Air conditioner | 2540 | 2454 | 21 | 40 | 2923 | 0.99 | 0.98 | 0.99 | 0.99 |
Refrigerator | 1543 | 1329 | 105 | 216 | 3964 | 0.93 | 0.86 | 0.94 | 0.89 |
Television | 125 | 97 | 60 | 28 | 5241 | 0.62 | 0.78 | 0.98 | 0.69 |
Electric iron | 790 | 738 | 22 | 52 | 4638 | 0.97 | 0.93 | 0.99 | 0.95 |
Kettle | 290 | 238 | 21 | 46 | 5139 | 0.92 | 0.84 | 0.99 | 0.88 |
Rice cooker | 52 | 44 | 10 | 8 | 5344 | 0.81 | 0.85 | 0.99 | 0.83 |
Microwave oven | 230 | 223 | 4 | 7 | 5171 | 0.98 | 0.97 | 0.99 | 0.98 |
Washing machine | 290 | 275 | 4 | 15 | 5119 | 0.99 | 0.95 | 0.99 | 0.97 |
Appliance | Total Energy [Meter] (kWh) | Total Energy [NILM] (kWh) | |
---|---|---|---|
Air conditioner | 91.8 | 89.1 | 0.96 |
Refrigerator | 34.5 | 31.4 | 0.90 |
Television | 6.2 | 5.3 | 0.81 |
Electric iron | 3.9 | 3.7 | 0.94 |
Kettle | 7.1 | 6.1 | 0.87 |
Rice cooker | 6.0 | 5.7 | 0.93 |
Microwave oven | 2.4 | 1.9 | 0.89 |
Washing machine | 5.2 | 4.2 | 0.86 |
Total | 157 | 148 | = 0.94 |
Appliance | Total Events | TP | FP | FN | TN | Precision | Recall | Accuracy | F1-Score |
---|---|---|---|---|---|---|---|---|---|
Air conditioner | 1056 | 976 | 16 | 66 | 1116 | 0.98 | 0.94 | 0.96 | 0.96 |
Refrigerator | 466 | 416 | 4 | 42 | 1688 | 0.99 | 0.91 | 0.98 | 0.95 |
Water heater | 256 | 238 | 2 | 10 | 1868 | 0.99 | 0.96 | 0.99 | 0.98 |
Electric iron | 300 | 244 | 4 | 20 | 1860 | 0.98 | 0.92 | 0.99 | 0.95 |
Kettle | 42 | 40 | 19 | 2 | 2049 | 0.68 | 0.95 | 0.99 | 0.79 |
Rice cooker | 46 | 42 | 4 | 4 | 2062 | 0.91 | 0.91 | 0.99 | 0.91 |
Microwave oven | 20 | 14 | 2 | 6 | 2092 | 0.88 | 0.70 | 0.99 | 0.99 |
Washing machine | 156 | 138 | 2 | 15 | 1968 | 0.99 | 0.90 | 0.99 | 0.94 |
Appliance | Total Energy [Meter] (kWh) | Total Energy [NILM] (kWh) | |
---|---|---|---|
Air conditioner | 60.0 | 56.6 | 0.93 |
Refrigerator | 37.7 | 36.6 | 0.95 |
Water heater | 23.9 | 23.4 | 0.95 |
Electric iron | 1.4 | 1.7 | 0.86 |
Kettle | 3.0 | 2.6 | 0.92 |
Rice cooker | 15.7 | 10.2 | 0.80 |
Microwave oven | 0.7 | 0.6 | 0.86 |
Washing machine | 3.3 | 2.3 | 0.83 |
Total | 145 | 134 | = 0.92 |
Appliance | Total Events | TP | FP | FN | TN | Precision | Recall | Accuracy | F1-Score |
---|---|---|---|---|---|---|---|---|---|
Air conditioner | 1899 | 1824 | 16 | 75 | 1718 | 0.99 | 0.96 | 0.97 | 0.97 |
Refrigerator | 1502 | 1308 | 105 | 214 | 2145 | 0.92 | 0.85 | 0.91 | 0.89 |
Water heater | 88 | 80 | 5 | 8 | 3473 | 0.94 | 0.90 | 0.99 | 0.92 |
Water pump | 206 | 162 | 50 | 44 | 3346 | 0.76 | 0.78 | 0.97 | 0.77 |
Microwave oven | 102 | 86 | 22 | 16 | 3450 | 0.79 | 0.84 | 0.98 | 0.81 |
Washing machine | 110 | 98 | 6 | 12 | 3454 | 0.94 | 0.89 | 0.99 | 0.91 |
Appliance | Total Energy [Meter] (kWh) | Total Energy [NILM] (kWh) | |
---|---|---|---|
Air conditioner | 171.0 | 153.0 | 0.94 |
Refrigerator | 69.8 | 55.9 | 0.89 |
Water heater | 10.0 | 9.1 | 0.91 |
Water pump | 5.4 | 4.3 | 0.79 |
Microwave oven | 5.8 | 4.9 | 0.84 |
Washing machine | 14.1 | 12.6 | 0.86 |
Total | 277 | 240 | = 0.92 |
List | House 1 | House 2 | House 3 | Average |
---|---|---|---|---|
Number of appliances | 8 | 8 | 6 | - |
Number of test days | 30 | 29 | 31 | - |
Number of events | 5860 | 2342 | 3907 | - |
Number of events detected | 5398 | 2104 | 3558 | - |
Total energy [METER] (kWh) | 157 | 145 | 277 | - |
Total energy [NILM] (kWh) | 148 | 134 | 240 | - |
F1-score | 0.90 | 0.91 | 0.88 | 0.897 |
0.94 | 0.92 | 0.92 | 0.927 |
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Biansoongnern, S.; Plangklang, B. An Alternative Low-Cost Embedded NILM System for Household Energy Conservation with a Low Sampling Rate. Symmetry 2022, 14, 279. https://doi.org/10.3390/sym14020279
Biansoongnern S, Plangklang B. An Alternative Low-Cost Embedded NILM System for Household Energy Conservation with a Low Sampling Rate. Symmetry. 2022; 14(2):279. https://doi.org/10.3390/sym14020279
Chicago/Turabian StyleBiansoongnern, Somchai, and Boonyang Plangklang. 2022. "An Alternative Low-Cost Embedded NILM System for Household Energy Conservation with a Low Sampling Rate" Symmetry 14, no. 2: 279. https://doi.org/10.3390/sym14020279
APA StyleBiansoongnern, S., & Plangklang, B. (2022). An Alternative Low-Cost Embedded NILM System for Household Energy Conservation with a Low Sampling Rate. Symmetry, 14(2), 279. https://doi.org/10.3390/sym14020279