Characterization of Energy Profile and Load Flexibility in Regional Water Utilities for Cost Reduction and Sustainable Development
Abstract
:1. Introduction
1.1. Overview and Motivation
1.2. Literature Review
1.3. Contribution
- Step-by-step data analytics was developed to discover, interpret, and visualize meaningful patterns from water industry energy consumption data. The developed method helped deliver a clean energy profile to characterize and identify energy flexibility for water utilities, especially in regional areas.
- The identified energy flexibility was used to explore the opportunities for cost reduction in the operation of water utilities through demand management. Several levels of demand management were considered to identify the quarterly and yearly savings of a water utility.
- The opportunities and benefits of installing solar and battery storage in the regional water industry sites were assessed for cost reduction and sustainable development.
- Recommendations are made for improving data coordination (interoperability) to enable the use of a single platform for identifying DR opportunities for different types of water utilities.
2. Methodology
- Step 1: Business Understanding
- Step 2: Data Mining
- Step 3: Data Cleaning
- Values beyond reasonable operational limits, possibly due to hardware errors.
- Missing values, possibly due to hardware errors or data collection at different time scales. For example, energy consumption was collected half-hourly, but some water pumps were collected hourly or nearly hourly.
- Time was not synchronized. The timing of the data could be out of synchronization because they were collected from different sources. To overcome this issue, we matched the events to energy consumption.
- Step 4: Data Exploration and Feature Engineering
- Step 5: Performing a Final Assessment
2.1. Data Classification and Diversity
2.2. Data Cleaning and Preparation
2.3. Wholesale and Retail Energy Tariff
2.4. Performance Index
2.5. Opportunity Assessment Process
3. Results
3.1. Data Acquisition
3.1.1. Data Selection and Processing
3.1.2. NEM Electricity Spot Price
3.2. Energy Profiling
3.3. Opportunity Assessment
3.3.1. DR Using Peak Load Shifting
3.3.2. Opportunity Assessment: Using Solar and Energy Storage
Site A1
Site B1
Site B2
4. Conclusions
- The energy and load profiles were characterized, revealing that most regional sites relied heavily on grid electricity.
- Three of the sites transitioned from an uneconomical state (EEI of more than one) to an economical state after a 5% peak load shift. The EEI values of one site remained above one even after a 20% peak load shift.
- Total savings increased by up to 60% with a 100% increase in PV with the existing battery size as the excess electricity could be utilized during peak hours rather than being exported to the grid.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
AEMO | Australian Energy Market Operator |
BOD | Biological Oxygen Demand |
COD | Chemical Oxygen Demand |
DR | Demand Response |
DO | Dissolved Oxygen |
EEI | Energy Efficiency Index |
NEM | National Electricity Market |
NMI | National Metering Identifier |
NREL | National Renewable Energy Laboratory |
NSRDB | National Solar Radiation Database |
RES | Renewable Energy Sources |
SAM | System Advisor Model |
SBR | Sequencing Batch Reactor |
SCADA | Supervisory Control and Data Acquisition |
SILO | Scientific Information for Land Owners |
SS | Suspended Solid |
TWAP | Time-Weighted Average Price |
VDO | Victorian Default Offer |
VWAP | Volume-Weighted Average Price |
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Sites/ Period | EEI (Using Retail Price) | EEI (Using Wholesale Price) | ||||||
---|---|---|---|---|---|---|---|---|
A1 | B1 | B2 | B3 | A1 | B1 | B2 | B3 | |
Q1 | 1.004 | 0.994 | 1.001 | 0.999 | 0.983 | 1.051 | 0.998 | 1.002 |
Q2 | 0.995 | 0.997 | 0.999 | 0.999 | 1.005 | 1.002 | 0.958 | 0.988 |
Q3 | 0.998 | 0.999 | 1.002 | 0.997 | 1.005 | 0.996 | 0.984 | 1.016 |
Q4 | 1.002 | 0.995 | 1.001 | 0.996 | 1.004 | 1.003 | 0.990 | 1.006 |
Annual | 0.990 | 1.002 | 1.038 | 1.003 | 0.995 | 1.021 | 1.016 | 1.008 |
Sites/ Period | A1 | B1 | B2 | B3 | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
5% | 10% | 15% | 20% | 5% | 10% | 15% | 20% | 5% | 10% | 15% | 20% | 5% | 10% | 15% | 20% | |
Q1 | 0.997 | 0.989 | 0.981 | 0.974 | 0.984 | 0.974 | 0.965 | 0.956 | 0.993 | 0.986 | 0.979 | 0.974 | 0.988 | 0.979 | 0.969 | 0.960 |
Q2 | 0.984 | 0.974 | 0.965 | 0.955 | 0.991 | 0.985 | 0.979 | 0.973 | 0.997 | 0.995 | 0.993 | 0.990 | 0.994 | 0.987 | 0.982 | 0.976 |
Q3 | 0.990 | 0.983 | 0.976 | 0.969 | 0.994 | 0.989 | 0.984 | 0.979 | 0.999 | 0.997 | 0.994 | 0.992 | 0.992 | 0.986 | 0.982 | 0.977 |
Q4 | 0.994 | 0.986 | 0.979 | 0.972 | 0.987 | 0.981 | 0.974 | 0.968 | 0.997 | 0.994 | 0.991 | 0.989 | 0.988 | 0.982 | 0.975 | 0.969 |
Annual | 0.982 | 0.975 | 0.967 | 0.959 | 0.995 | 0.987 | 0.981 | 0.974 | 1.033 | 1.028 | 1.024 | 1.019 | 0.996 | 0.988 | 0.981 | 0.974 |
Sites/ Period | A1 | B1 | B2 | B3 | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
5% | 10% | 15% | 20% | 5% | 10% | 15% | 20% | 5% | 10% | 15% | 20% | 5% | 10% | 15% | 20% | |
Q1 | 0.976 | 0.968 | 0.961 | 0.955 | 1.049 | 1.046 | 1.044 | 1.043 | 0.995 | 0.993 | 0.991 | 0.990 | 0.999 | 0.998 | 0.996 | 0.995 |
Q2 | 0.999 | 0.992 | 0.997 | 0.981 | 0.996 | 0.990 | 0.984 | 0.978 | 0.952 | 0.947 | 0.942 | 0.937 | 0.981 | 0.975 | 0.969 | 0.963 |
Q3 | 0.995 | 0.995 | 0.976 | 0.967 | 0.986 | 0.976 | 0.967 | 0.958 | 0.974 | 0.964 | 0.955 | 0.946 | 1.006 | 0.996 | 0.987 | 0.977 |
Q4 | 1.000 | 0.997 | 0.994 | 0.991 | 0.999 | 0.997 | 0.994 | 0.991 | 0.987 | 0.983 | 0.981 | 0.978 | 1.002 | 0.999 | 0.996 | 0.993 |
Annual | 0.988 | 0.982 | 0.976 | 0.969 | 1.016 | 1.011 | 1.010 | 1.002 | 1.012 | 1.010 | 1.003 | 1.000 | 1.003 | 0.998 | 0.993 | 0.989 |
Sites/ Load Shifting | A1 | B1 | B2 | B3 | ||||
---|---|---|---|---|---|---|---|---|
Retail Price | Wholesale Price | Retail Price | Wholesale Price | Retail Price | Wholesale Price | Retail Price | Wholesale Price | |
Original Cost | 1,214,498 | 1,147,504 | 22,401 | 16,714 | 250,766 | 174,371 | 137,653 | 97,296 |
5% | 11,570 | 8558 | 193 | 97 | 2270 | 889 | 1201 | 563 |
10% | 25,542 | 18,235 | 430 | 210 | 5040 | 1939 | 2677 | 1217 |
15% | 41,918 | 28,924 | 712 | 338 | 8311 | 3151 | 4426 | 1961 |
20% | 60,697 | 40,627 | 1037 | 482 | 12,082 | 4524 | 6448 | 2796 |
Direct Capital Cost | O&M Cost | Lifetime (Year) | Inflation Rate | Discount Rate | |
---|---|---|---|---|---|
PV | 700 AUD/kW | 10 AUD/kW/year | 25 | 2.5%/year | 6.4%/year |
BESS | 370 AUD/kWh, 270 AUD/kW | 15 AUD/kWh/year | 10 |
Percent Solar Increase | Export to the Grid (MWh) | Savings by Exporting to the Grid (AUD) | Savings by Using Battery Storage (AUD) |
---|---|---|---|
Present capacity | 20.40 | 2019 | 3365 |
25% increase | 42.25 | 4182 | 6970 |
50% increase | 99.88 | 9888 | 16,480 |
75% increase | 198.49 | 19,650 | 32,751 |
100% increase | 330.91 | 32,760 | 54,600 |
Percent Solar Increase | Export to the Grid (MWh) | Savings by Exporting to the Grid (AUD) | Savings by Using Battery Storage (AUD) |
---|---|---|---|
Present capacity | 25.33 | 2507 | 4178 |
25% increase | 41.52 | 4110 | 6850 |
50% increase | 59.05 | 5845 | 9743 |
75% increase | 77.49 | 7671 | 12,785 |
100% increase | 96.48 | 9551 | 15,918 |
Percent Solar Increase | Export to the Grid (MWh) | Savings by Exporting to the Grid (AUD) | Savings by Using Battery Storage (AUD) |
---|---|---|---|
Present capacity | 7.73 | 765 | 1276 |
25% increase | 14.98 | 1482 | 2471 |
50% increase | 26.95 | 2667 | 4446 |
75% increase | 46.15 | 4569 | 7615 |
100% increase | 74.89 | 7413 | 12,356 |
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Amin, B.M.R.; Shah, R.; Lim, S.; Choudhury, T.; Barton, A. Characterization of Energy Profile and Load Flexibility in Regional Water Utilities for Cost Reduction and Sustainable Development. Sustainability 2025, 17, 3364. https://doi.org/10.3390/su17083364
Amin BMR, Shah R, Lim S, Choudhury T, Barton A. Characterization of Energy Profile and Load Flexibility in Regional Water Utilities for Cost Reduction and Sustainable Development. Sustainability. 2025; 17(8):3364. https://doi.org/10.3390/su17083364
Chicago/Turabian StyleAmin, B. M. Ruhul, Rakibuzzaman Shah, Suryani Lim, Tanveer Choudhury, and Andrew Barton. 2025. "Characterization of Energy Profile and Load Flexibility in Regional Water Utilities for Cost Reduction and Sustainable Development" Sustainability 17, no. 8: 3364. https://doi.org/10.3390/su17083364
APA StyleAmin, B. M. R., Shah, R., Lim, S., Choudhury, T., & Barton, A. (2025). Characterization of Energy Profile and Load Flexibility in Regional Water Utilities for Cost Reduction and Sustainable Development. Sustainability, 17(8), 3364. https://doi.org/10.3390/su17083364