Introduction
Hope in off-grid electrification
Multi-tier framework for household electricity access
Tier 1 | Tier 2 | Tier 3 | Tier 4 | Tier 5 | |
---|---|---|---|---|---|
Peak power rating | > 12Wh, > 3W | > 200Wh, > 50W | > 1kWh , > 200W | > 3.4kWh , > 800W | > 8.2kWh , > 2kW |
and energy | |||||
Availability (h/day) | >4 | >4 | >8 | >16 | >23 |
Availability | >1 | >2 | >3 | >4 | >4 |
(h/evening) | |||||
Reliability | – | – | – | <14 disruptions per week | <3 disruptions |
per week | |||||
Quality | – | – | – | Voltage problems do not affect the use | |
of desired appliances | |||||
Affordability | – | – | – | Cost of 365 kWh/year <5% of | |
household income | |||||
Legality | – | – | – | Bill is paid to the utility or authorized | |
representative | |||||
Health and safety | – | – | — | Absence of past accidents and high risk | |
perception in the future |
Off-grid appliances
Importance of load profiles
Need for load profile construction
- Difficult to estimate It is tough to estimate the energy consumption behavior in off-grid communities if the electricity access has hitherto been limited.
- Starting point The load profile is the starting point in off-grid system design. In the absence of existing load profiles, as is the case with most off-grid locations, reliable load profile construction is crucial.
- Growth enabling Load profile construction for not just the present but an estimated future usage would benefit the off-grid system designers to enable the growth of the energy consumption in their off-grid systems.
Contributions
Background
Literature review
Load profile parameters
Peak and average loads
Energy demand
Load factor
Coincidence factor
Types of appliances
S. No. | Appliance | Needs | Typical rating [W] |
---|---|---|---|
1 | LED Lighting | a | 1–5 |
2 | Mobile charging/banks | b | 3–20 |
3 | Television | b | 10–50 |
4 | Radio | b | 2–5 |
5 | Fridges | c | 40–400 |
6 | Fan | f | 15–100 |
7 | Laptop | b | 30–100 |
8 | Solar water pumps | d | 40–800 |
9 | Tablets | b | 12–50 |
10 | Rice cooker | e | 200–250 |
11 | Clothes iron | d | 150–2000 |
12 | Grinders | d | 750–1000 |
13 | Hand power tools | d | 100–1000 |
14 | Hair clippers | d | 15–50 |
15 | Small speaker systems | b | 5–10 |
16 | Rice mills | d | 200–500 |
17 | Sewing machines | d | 40–100 |
18 | Soldering iron | d | 20–60 |
19 | Tea kettles | e | 100–800 |
Methodology
Load classification
Load j | Rating P [W] | \( T_{\min }\) | \( T_{\max }\) | Tm [h] | \( n_{\min } \) | \( n_{\max } \) | W1 | W1 | W2 | W2 | Quantity q [-] | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
start | length | start | length | ||||||||||||||||||||
T-1 | T-2 | T-3 | T-4 | T-5 | [mins] | [mins] | T-1 | T-2 | T-3 | T-4 | T-5 | [−] | [−] | [time] | [h] | [time] | [h] | T-1 | T-2 | T-3 | T-4 | T-5 | |
LED lighting | 2 | 2 | 2 | 2 | 2 | 30 | 240 | 6 | 8 | 8 | 12 | 12 | 1 | 12 | 4 | 2 | 18 | 6 | 3 | 5 | 5 | 8 | 12 |
Mobile phone charging | 3 | 3 | 3 | 3 | 3 | 5 | 120 | 6 | 8 | 8 | 8 | 8 | 1 | 12 | 0 | 1 | 6 | 18 | 2 | 3 | 3 | 5 | 5 |
Radio | 0 | 3 | 3 | 3 | 3 | 5 | 240 | 0 | 8 | 8 | 12 | 12 | 1 | 10 | 7 | 13 | 0 | 0 | 0 | 2 | 2 | 2 | 2 |
Fan | 0 | 15 | 20 | 35 | 35 | 5 | 600 | 0 | 8 | 8 | 12 | 16 | 1 | 10 | 7 | 12 | 0 | 0 | 0 | 1 | 2 | 4 | 4 |
TV | 0 | 12 | 18 | 29 | 29 | 5 | 240 | 0 | 8 | 8 | 12 | 12 | 1 | 10 | 7 | 7 | 17 | 6 | 0 | 1 | 1 | 2 | 2 |
Fridge | 0 | 0 | 54 | 54 | 54 | 5 | 30 | 0 | 0 | 3 | 8 | 24 | 5 | 15 | 5 | 19 | 0 | 0 | 0 | 0 | 1 | 1 | 1 |
Tablet | 0 | 0 | 18 | 18 | 18 | 5 | 120 | 0 | 0 | 6 | 12 | 12 | 1 | 10 | 0 | 1 | 6 | 18 | 0 | 0 | 1 | 1 | 1 |
Kettle | 0 | 0 | 0 | 400 | 400 | 5 | 15 | 0 | 0 | 0 | 1 | 1 | 1 | 8 | 7 | 14 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
Laptop | 0 | 0 | 0 | 60 | 60 | 5 | 240 | 0 | 0 | 0 | 6 | 6 | 1 | 10 | 0 | 1 | 6 | 18 | 0 | 0 | 0 | 1 | 1 |
Rice cooker | 0 | 0 | 0 | 200 | 200 | 30 | 30 | 0 | 0 | 0 | 1.5 | 1.5 | 1 | 3 | 10 | 2 | 17 | 3 | 0 | 0 | 0 | 1 | 1 |
Clothes iron | 0 | 0 | 0 | 150 | 150 | 5 | 20 | 0 | 0 | 0 | 2 | 2 | 1 | 2 | 6 | 16 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
Washing machine | 0 | 0 | 0 | 70 | 70 | 15 | 120 | 0 | 0 | 0 | 2 | 2 | 0 | 1 | 6 | 14 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
Air cooler | 0 | 0 | 0 | 500 | 500 | 30 | 120 | 0 | 0 | 0 | 4 | 12 | 0 | 8 | 9 | 9 | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
Power tools | 0 | 0 | 0 | 0 | 100 | 5 | 60 | 0 | 0 | 0 | 0 | 10 | 2 | 10 | 6 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
Grinders/millers | 0 | 0 | 0 | 0 | 750 | 10 | 120 | 0 | 0 | 0 | 0 | 10 | 2 | 10 | 6 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
Sewing machine | 0 | 0 | 0 | 0 | 40 | 5 | 120 | 0 | 0 | 0 | 0 | 10 | 3 | 20 | 6 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
Water pump | 0 | 0 | 0 | 0 | 750 | 5 | 30 | 0 | 0 | 0 | 0 | 4 | 0 | 2 | 5 | 12 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
Model parameters
Parameter | Definition | Notation | Type |
---|---|---|---|
Load type | Type of load in use. For example, TV, LED | j | Input |
lights, etc, chosen from the LCM | |||
Total load type | Total load types per category | N | Input |
Rated power | Rated power per load | P | |
Cycle time | Duration for which a load is operational | T | Generated |
Maximum usage | Maximum number of hours a load is | Tm | Input |
allowed to operate during the day | |||
Instances | Number of times a load is operated in | n | Generated |
the allowed usage window | |||
Usage window | The allowed time window within which the | W | Input |
loads are expected to be used | |||
Quantity of loads | The number of loads of each type | q | Input |
Start time | Start time of a load instance within the usage window | t | Generated |
Load occurrence | The ith occurrence of a load cycle | i | Generated |
Dynamic window | Dynamic window calculated as more | Wdyn | Generated |
load occurrences reduce the usage window | |||
Functioning time | Day long time interval showing the precise | f | Output |
time stamps when the load is active or inactive | |||
Peak window | The usage window where multiple appliances | Wpeak | Generated |
can potentially function simultaneously | |||
Coincidence factor | A design input between 0.2 and 1 that denotes | CF | Input |
the likelihood of appliances functioning simulatneously |
Usage window
Peak window and coincidence factor
Randomness and constraints
Stochastic load profile model
Assumptions in the methodology
The case of the refrigerator
Advantages of the methodology
Results and discussions
Stochastic load profiles for MTF
Load profiles: main parameters
Tier 1 | Tier 2 | Tier 3 | Tier 4 | Tier 5 | |
---|---|---|---|---|---|
\( P_{\max } \) (W) | 12 | 51 | 154 | 1670 | 3081 |
\( P_{\min } \) (W) | 6 | 35 | 113 | 583 | 1732 |
\( \overline {E_{\text {daily}}} \) (Wh) | 50 | 218 | 981 | 3952 | 9531 |
Load factor (-) | 0.17 | 0.18 | 0.26 | 0.10 | 0.13 |
Implications on system design
Comparison with field data
Conclusions
Recommendations and future work
Loads | Sample model number(s) | Source |
---|---|---|
LED lighting | SL 1220CF120 | Phocos (2016) |
Mobile phone | Samsung Guru Plus | Samsung (2016) |
Radio | Fosera, FS106 | GIZ (2016) |
Fan | ONergy 10” BOX FAN, | |
FS91, ONergy 16” PEDESTAL | ||
FAN, FS92, Ceiling Fan ME-103-DC | ||
TV | Fosera DC TV 15.6” 12 V, | Global LEAP (2016b) |
D.light design 18.5” LE185N91C, | ||
Mobisol 24” MSDV2310MY-308C1 | ||
Fridge | Solar Chill, FS52 , | |
Sundanzer DCR 50, DCR 165 | ||
Tablet | HP Pro Tablet 10 EE G1 | HP (2016) |
Kettle | Solar DC Kettle SE520, FS65 | GIZ (2016) |
Laptop | Generic Laptop | – |
Rice cooker | SR-3NA-S | Panasonic (2016) |
Clothes iron | Solar DC Power Iron Dry/ Spray | GIZ (2016) |
style-12V SL100S, FS192 | ||
Washing machine | Washing Machine CERAD, FS127 | GIZ (2016) |
Air cooler | DC Solar Air Conditioner, DC4812VRF | Hotspot Energy (2016) |
Power tools | Bosch 18V Lithium Ion 4-Tool Combo | GIZ (2016) |
Kit (CLPK414-181), FS84 | ||
Grinders/millers | Grain Mill Solar Milling, FS32 | GIZ (2016) |
Sewing machine | Sewing Machine CERAD, FS73 | GIZ (2016) |
Water pump | Solar Surface Slow Pump Dankoff, FS10 | GIZ (2016) |