- freely available
Energies 2019, 12(23), 4599; https://doi.org/10.3390/en12234599
2. Energy Transformation in Water Supply Systems
3. Review of Energy Assessment for Water Supply
3.1. Performance Assessment Methodologies for Water Supply
3.2. Energy Assessment Methodologies for Water Supply
3.3. Energy Assessment Methodologies for Water Supply—Based on Modeling of Physical Processes
- Efficiency metrics—describe the water supply energy efficiency (M1—the ratio between energy delivered to the user and energy supplied to the system and M2—the ratio between energy delivered to the user and the net energy in the pipe),
- Requirements metric—defined as the relationship between the required energy to be delivered to users (to fulfill water network requirements) and the amount of energy supplied to users. This indicator describes the pressure excess in the water supply network,
- Energy loss metrics—describe the relationship between energy loss and energy supplied to the pipes: M4—includes the part of energy loss connected with friction, but only for water flow, which is delivered to users and M5—includes the part of energy loss connected with friction, for water flow delivered to users and for water flow lost due to leakage.
4. Analysis of Current Research Papers and Technical Methodologies
4.1. Top-Down Methodologies
4.2. Bottom-Up Methodologies
4.3. Energy Balance for Water Supply Systems
- pumps, due to the imperfection of conversion of electrical energy to the kinetic and potential energy of water;
- pipes and valves, due to friction;
- leaks, due to the dissipation of energy with lost water mass caused by leaks in pipes and tanks;
- users, due to maintenance of pressures higher than required in the water supply network.
4.4. Reference Values and Performance Assessment
4.5. The Concept of Minimal Energy and an Ideal System
4.6. Tools and Software Supporting Energy Assessment of Water Supply Systems
4.7. Notes on Data Reliability andAvailability
4.8. Recommendation for Water Utilities
4.9. The Comparative Analyses of Methodologies
5. Gaps and Future Challenges
- Energy assessment is a part of the overall assessment of a water supply utility. In such an overall assessment, it is required to aggregate different indicators into a single indicator. The assessment of this type is presented in AquaRating , which uses weighted sum methods. There is great potential for testing other multi-criteria methods for the overall assessment of water utilities.
- Reference has been made to the need for and possibilities of introducing a labeling system for an energy assessment. Implementation of a labeling system will improve the possibility of an objective comparison of water supply systems.
- Performance of a full energy balance requires the use of a computer model of a water distribution system. The methodologies for building models for energy assessment should be unified. It seems reasonable to test how simplification of the model will affect the result of calculations. In particular, it would be useful to determine a standard time horizon, time step, and pattern characteristic (for how many seasons, patterns should be taken into account).
- The presented water balance case studies were performed using demand-driven simulation (DDA), in which the water demand does not depend on pressure. In recent years, much effort has been devoted to the development of pressure-driven simulation (PDD) [50,51,52,53,54]. PDD is particularly helpful in analyses of the impact of pressure reduction. Pressure reduction can also cause a reduction in pumps’ energy demand and water loss. It is reasonable to implement an energy balance for a PDD model also.
- In the context of climate change, GHG emissions assessment is coming to play an important role in performance evaluation. The main source of emissions from a supply system is indirect emissions due to electrical energy consumption . It should be noted that analyzing only these emissions may be insufficient. There are other emission sources in water supply systems, such as direct emissions from trucks (when the water is supplied by trucks) and fuel engines, and indirect emissions related to the use of various reagents in water treatment and disinfection. It is also important to analyze the carbon footprint over the whole life-cycle (production, use, and disposal phase) [30,38]. All analyses related to climate mitigation should be performed according to the Intergovernmental Panel on Climate Change (IPCC) recommendation .
- The energy balance is derived based on the law of energy conservation for the water supply network. This law is usually described using the Bernoulli equation. In the analyzed literature, thermodynamic descriptions of water supply networks concern only losses of kinetic and potential energy, as well as imperfections of energy transformations in pumps. There are no complete descriptions of all types of energy transformation in water supply systems (physical, chemical, and thermal energy). There is also no comprehensive description of the water supply system derived from the second law of thermodynamics (using an entropy and exergy approach). In light of the analysis of energy assessment of water supply systems, it is reasonable and necessary to develop an energy model for those systems. Such a model can be determined using the first and second laws of thermodynamics. This model will allow the analysis of changes in all types of energy in systems.
- Currently, energy assessment in the water supply is limited to water distribution systems. To reduce overall energy consumption, users’ plumbing should also be analyzed. Reducing water demand has a significant impact on energy usage. There are several methods for assessing and labeling water usage efficiency [2,22]. It may be useful to integrate these methods with the energy balance for water supply.
6. Summary and Conclusions
Conflicts of Interest
Computer Tools, Modeling Case Study, Remarks
|1. IWA Manual of Performance Indicators for Water Supply Services |
|IWA Manual of Best Practice Performance Indicators for Water Supply Services is a standard for the development of a performance assessment system for water utilities. The manual referred to 166 indicators, divided into six groups: water resources indicators (four indicators), personnel indicators (26 indicators), physical indicators (15 indicators), operational indicators (40 indicators), quality of service indicators (34 indicators), and economic and financial indicators (47 indicators).||The following indicators related to energy were specified in the physical indicators group:||Top-down methodology|
There were several computer applications in which this methodology was implemented, e.g., Sigma software , AWAR-P .
The manual presented a guide for implementing a performance assessment system. The indicators might be used by water utility managers, benchmarking organizations, statistical offices, and water regulation offices.
The manual also contained examples of application, remarks on data quality, and recommendations on how to increase performance using the system of indicators. Possibilities of using performance assessment indicators as a part of asset management were also presented.
|2. ECAM—Energy Performance and Carbon Emissions Assessment and Monitoring Tool |
|ECAM (Energy Performance and Carbon Emissions Assessment and Monitoring Tool) is a tool developed under the Wastewater Companies for Climate Mitigation project, implemented by GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit) and the IWA (International Water Association). The tool could be used to evaluate all processes in both water and wastewater systems.||The main aim of this evaluation was to calculate GHG emissions (CO2 emission equivalent) for all processes. Two types of emissions were distinguished:|
For a water distribution system, it was possible to assess topographical energy. The following indicators were used:
A free and open Web-based platform for the performance assessment and Web-based learning platform.
During the project, a Web-based platform for water utility systems was developed. Several case studies were presented on the platform. There was also a set of good practices for improving energy efficiency, presented on the Web-based knowledge platform.
|3. IBNET—The International Benchmarking Network [7,8]|
|IBNET is a World Bank project. Its main aim was to provide data about water utilities worldwide for utility managers, regulators, authorities, investors, and the general public. The project was open to all water utilities, which could send data about their performance using a toolbox. Data were freely available to all and were published by the Web application. The performance indicators in IBNET concerned 14 areas: service coverage, water consumption and production, operating costs and staff, non-revenue water, meters, network performance, quality of service, billings and collections, financial performance, assets.||The project related to water and wastewater infrastructure assessment.|
The following data on energy consumption were collected under the project:
A free and open Web-based platform.
Data were sent voluntarily by water utilities; e.g., 2445 utilities took part in the survey in 2015, 769 in 2016, and 545 in 2017. All data were free and publicly available via an Internet application. The application could be used to create reports and compare different indicators at the global level. Due to the wide range of the project, it was not possible to verify all of the data. The platform is an appropriate tool to perform macroeconomic analyses, but the possibilities of assessing single utilities might be limited.
|4. AquaRating |
|AquaRating is a performance assessment system for water utilities. The result of the evaluation was an aggregated “rating” of a utility’s performance. The project had been developed by the International Water Association and the Inter-American Development Bank. In the project, 112 assessment factors were aggregated in eight groups: service quality, investment planning and implementation efficiency, operating efficiency, business management efficiency, financial sustainability, access to service, corporate governance, and environmental sustainability. The evaluation used both performance indicators (quantitative assessment) and good practices (qualitative assessment). The good practices were a set of recommendations for water utilities related to management. Methods of assessment were specified for each indicator and good practice, as well as the method for aggregating all of the criteria into a single “rating”.||The energy assessment was carried out as part of the assessment of the implementation of the following good practices:|
[SA-V3]—energy consumed by all drinking water and wastewater processes (kWh)
[SA-V4]—energy generated in facilities linked to the “system” (kWh)
[SA-V5]—annual emission of CO2 equivalent in the calendar year preceding the rating date (tons CO2),
[SA-V15]—number of inhabitants (inhabitants).
The reduction of CO2 emission is also proposed as a part of good practices:
Web-based platform (available to participants).
The project website contained many case studies. The methodology had been implemented by water utilities in countries, including Argentina, China, Colombia, Ecuador, Spain, El Salvador, Fiji, Sierra Leone, Jamaica, and Mexico.
|5. EPA’s Energy Use Assessment Tool |
|The EPA’s Energy Use Assessment Tool was developed by the United States Environmental Protection Agency (US EPA) to support small and medium-sized water utilities in conducting energy audits.||The assessment was based on data on electricity consumption (read from meters) for all devices, such as pumps, blowers, HVAC installations, lighting, etc. The data were assigned to processes (e.g., distribution pumping, filtration, clarification, HVAC, low service pumping, etc.). The audit was recommended for a minimum period of one year (optimally five years). As part of the assessment, the trend of changes in the value of energy consumption was checked, and the most energy-consuming processes were selected. The audit enabled the assessment of changes in the value of energy consumption indicators within the enterprise (internal benchmarking). Also, energy cost data were collected for the performance of economic analyses.||Top-down methodology|
Excel spreadsheet (free access via the US EPA website).
Some case studies were presented in the guide, as well as audit tips and recommendations.
|6. Water Research Foundation—Toolbox for Water Utility Energy and Greenhouse Gas Emission Management |
|The main objective of the toolbox was to present a framework for energy and GHG emission assessments for water utilities. The document contained a review of energy and GHG emissions assessment programs and presented currently used models and algorithms and future research needs for energy evaluation. Strategies and best practices for utilities were also presented under the project.||In this project, methodologies for energy and GHG emission assessment from various countries were presented, along with case-studies from different countries. GHG accounting standards (IPPC, UNFCCC, etc.) were described. The sources and types of GHG emissions from water and wastewater treatment facilities were distinguished. Emissions were classified by scope designation, ownership level (direct/indirect), and contribution sources. Energy benchmarking and management tools and software were reviewed. The report was supplemented by the results of a survey on the use of energy assessment tools by different water utilities.|
In the report, it was shown that it was not possible to develop a single methodology for energy and GHG emissions assessment for all water utilities. A methodology should always be selected, taking into account the local conditions and aims. It was only possible to lay down general standards and good practices. The report presented a decision framework for GHG emissions’ accounting and reporting. According to this framework:
|The study presented a review of methodologies and did not indicate one as the best.|
The report contained many case studies from different countries.
|7. Energy Index Development for Benchmarking Water and Wastewater Utilities |
|These guidelines were sponsored jointly by the AWWA Research Foundation, California Energy Commission, and New York State Energy Research and Development Authority. The objective of the research was to review existing energy data and assessment methods used by utilities, develop a statistical model and characteristics of energy use, apply and evaluate a benchmark score system, which is similar to the EPA’s Energy Star rating system, and present case studies of the use of the metrics at sample utilities.||During the research, information characterizing utilities was collected by means of a survey. The analysis was made using data from 125 water utilities. The main aim of the analysis was to find the correlation between different water utility working parameters and energy use.|
In the survey, the water utilities were asked about raw water parameters, water treatment objectives, water treatment processes and residual handling parameters, water distribution parameters, water energy use parameters, and general water parameters. About 100 parameters were considered in the investigation. Statistical data characterizing water utilities were presented in the report. During the investigation, the statistical model was tested to find the correlation between different parameters and energy consumption in water utilities. A combination of the six best-represented model parameters was found. Using this parameter, the water utility energy model was constructed as:
LN(Source kBty/yr) = 8.2394
+0.4993 × LN(total system flow kGD)
−0.063 × LN(purchased water flow + 1kGD)
+ 0.3724 × LN(total pumping horsepower)
+ 0.0620 × LN(production pumping horsepower + 1)
+ 0.2385 × LN(distribution main length miles)
+ 0.0991 × LN(distribution system elevation change feet)
For the development of an energy performance metric, the ratio between average energy use and the energy calculated from the model was used. This ratio was used to assess utilities’ performance.
In the report, some of the data from the survey were presented. These data made it possible to perform aggregated analyses. There was also data on particular water utilities. In the document, more detailed analyses were performed for utilities with the highest and lowest energy scores. Several case studies were given.
|8. WATERGY: Energy and Water Efficiency in Municipal Water Supply and Wastewater Treatment—Cost-Effective Savings of Water and Energy |
|WATERGY is a project carried out by the Alliance to Save Energy and concerned the relationships between water and energy in all elements of a water and sewage system. The report described all elements of the system (devices and processes) in which significant amounts of energy were consumed.||The report recommended an energy audit for all devices. It was stated that in order to increase energy efficiency, three elements were necessary:||No single methodology was indicated as the best. The guide was rather a review and collection of best practices.|
The report contained many case studies from different countries, including South Africa, India, Brazil, and Mexico.
|9. Tools for Energy Footprint Assessment in Urban Water Systems |
|This article described the possible use of the software UWOT—The Urban Water Operating Tool  for modeling the interaction between water and energy in a city.||The authors proposed using unit values (kWh/L) that were calculated in UWOT. A “library” of specific (unit) energy consumption was defined in UWOT. The main advantage of the presented methodology was the possibility of comparing different scenarios of system development. For these scenarios, opportunities for energy demand reduction could be identified. The system facilitated the identification of the elements, which require the most urgent modernization. The methodology enabled the analysis of such objects as pumping stations and turbines. It was mainly the results of measurements that were analyzed (computer models of water transport systems were not analyzed).||Top-down methodology|
Software—the UWOT model for water supply management .
In the research, a large case study was analyzed. The example of Athens (about 6 million inhabitants) was presented. In that agglomeration, energy recovery was currently used. The paper indicated potential ways of increasing energy recovery from this system.
|10. Classification of Water Supply Systems Based on Energy Efficiency |
|In this article, the authors proposed the use of an indicator for classifying water supply systems in energy terms. In the study, the authors presented an example of the classification of Brazilian systems based on indicators obtained by the Brazilian National Sanitation Information System.||The following performance indicators were presented in this paper:|
EI—Efficiency index—this indicator serves to compare obtained efficiency with the maximum efficiency of the pumps, and is given as:
—the current efficiency of the motor pump (%)
—maximum possible efficiency of the motor pump set under the same operating conditions (%)
—power of the motor pump set (kW)
—total power installed in the system (kW).
RC—Reservoir capacity—the capacity that pumping station reservoirs have to meet to maintain the water supply during peak hours, calculated as:
—number of operational hours during peak hours in 1 year
—the average power consumed by the pumping station during peak hours
—power installed at the pumping station
782—assumed number of peak hours during 1 year
—the number of pumping stations in the system.
RI—Roughness index—this evaluates the increase in the roughness of pipelines due to aging and is defined as:
—current Hazen–Williams roughness coefficient
—Hazen–Williams roughness coefficient of a new pipe of the same material
—the number of pipelines in the system.
CLI—Connection loss index—describes water loss from the system, calculated as:
—the volume of water produced annually (m3)
—the volume of water imported annually (m3)
—the volume of water consumed for service annually (m3)
—the volume of water effectively consumed annually (m3)
—the number of service connections in the system (-).
SC—Specific consumption of electricity—the amount of energy needed to produce 1m3 of water, defined as:
—specific consumption of electricity.
—the volume of water macrometered at the exit of the water treatment station, simplified treatment units and wells, and at the inlet of the imported water (m3)
—the volume of water exported annually (m3)
—the volume of water imported annually (m3).
WMI—Water metering index:
—the number of active connections with metering.
Using statistical analysis, the indicator values were assigned to five classes (A, B, C, D, E).
Some of the indicators were identical to indicators collected by SNIS (the national system of information on sanitation in Brazil)  and indicators from the IWA Performance Indicators guidelines . The authors presented the values of indicators for various water utilities in Brazil. A case study covered 4941 water utilities and was developed using data from SNIS. Because SNIS did not collect all of the indicators and additional measurements needed to be performed, not all indicators were calculated for the 4941 utilities. A full case study (with all indicators) was given for 21 pumping stations.
|11. Energy Indicators and Savings in Water Supply |
|This article was one of the first publications on measuring energy efficiency for water supply systems. The research was carried out in selected cities in Switzerland. The article proposed indicators for assessing the efficiency of energy use in water supply systems. The concept was based on a definition of minimal energy (Emin), which is needed to ensure water supply.||The minimal energy is defined as “the least energy theoretically needed (without friction or pumping loss) to transport the water from its production locations to the users, at an operational pressure of about 6 bar (88 psi).”|
Using the concept of minimum energy, indicators characterizing the water supply network are defined as:
Qv is the annual amount of water used by consumers (m3).
If WS < 0, then it is possible to recover electrical energy from the water supply system. This occurs, for example, when the water source is located higher than the receivers.
E is the energy actually consumed during one year (kWh).
The authors presented the following assessment ranges for this indicator:
The methodology was developed in Switzerland (in mountain regions), where there is a possibility of recovering significant amounts of energy from the distribution system. The authors presented several case studies from that country. Attention was drawn to the benefits of using performance indicators to assess the potential for recovery of energy from the water supply network. In the article, the factors, which influence the energy quality indicators (I2), were analyzed. The possibilities of saving energy through better network design and rehabilitation (cleaning of pipes, replacement of pumps) were emphasized.
|12. Energy Audit of Water Networks |
|This article described a methodology for performing energy audits of water networks. The method was developed using the energy conservation law (Bernoulli equation). The audit was performed using computer models of water supply networks. Analyses made it possible to evaluate indicators for water supply system assessment, which could be used for better planning of action to increase energy efficiency. The paper presented the components of the energy audit (Figure A1—Appendix B) and equations for calculating their value.||The authors presented equations for calculating values for components of the energy audit. The values were calculated using the modeling of a water distribution system.|
On the basis of the energy audit, the following indicators are determined for a water supply system:
—the specific weight of water (kG/m3)
—the total demand of node i during the simulation period tp(m3)
n—number of nodes (-)
—minimum required piezometric head at node I (mH2O)
<1, meaning that the pressure is lower than required—the customer service standard is not fulfilled;
=1, the ideal situation, when there is no excess pressure—generally impossible from the point of view of system topography;
>1, when there is excess pressure—this situation is the most frequent, and, in this case, it is possible to recover energy from the network, e.g., by the use of turbines.
Computer modeling of a water distribution system—the EPANET model. The authors also developed a computer application: ITA Energy .
The article was supplemented with a case study with the calculation of water audit values and indicators for a simple water supply network (consisting of 10 nodes, a pump, and two tanks).
The article presented a standard methodology for conducting an energy audit of a water network. The audit could be used to better describe the energy used in the network and assess its performance. The authors recommended combining the technical audit with economic (energy price) and environmental (greenhouse gas emission) audits for a more holistic evaluation of a water utility.
|13. Energy Assessment of Pressurized Water Systems |
|This article presented additional performance indicators for a pressure water supply system. In the research, new performance indicators for the Energy Audit of Water Networks  were presented.||In the article, an “ideal system” was defined as a system with no friction, head losses, leaks, or excess pressure. The concept of an ideal system was used for developing performance indicators for water supply. In the research, three new performance indicators were presented:|
The efficiency index of the ideal system, with full energy recovery, can be calculated as:
—the minimum energy required by users (constant, no matter whether the system is real or ideal) (kWh)
—topographic energy required by the ideal system, corresponding to the minimal amount of energy, which should be delivered to the system to maintain the required pressure at a critical point. This energy at points other than critical (e.g., those where excess pressure is present) can be recovered by turbines (kWh)
—total supplied energy for the ideal system (kWh)
—supplied excess energy for the ideal system (present at all nodes where excess pressure is present) (kWh)
In the ideal system, = 0—all excess energy is recovered by turbines. In this case, = 1.
In a real system, for economic reasons (related to the installation of turbines in the system), only a part of is recovered.
The efficiency of an ideal system, without energy recovery, can be calculated from the formula:
—total supplied energy for the ideal system (kWh)
The article presented an algorithm for improving the efficiency of a water distribution system. In the algorithm, methods of evaluating performance indicators (using cost/benefit analysis) were proposed.
Computer modeling of a water distribution system—the EPANET model.
By calculating , one could determine the difference between a real and ideal system. By evaluating changes in this difference over time, one could define and monitor goals for improving energy efficiency. The paper presented methods for improving the energy efficiency of a system, such as reduction of leaks, reduction of energy related to friction in pipes, application of turbines, pump replacement, and improvement of the network structure. A case study of an agricultural irrigation system, covering 55 km of network and 400 water intakes, was presented.
|14. Towards an Energy Labeling of Pressurized Water Networks |
|This paper described procedures to minimize energy consumption in a water distribution system. The authors proposed a methodology for labeling water energy usage in water supply systems.||The authors proposed a six-stage methodology for energy improvement in a water system:||Bottom-up methodology|
The EPANET model was used.
A case study concerned an orange irrigation system in Cap de Terme, Villarreal (Spain). In the article, the authors described all six stages of the energy assessment and improvement methodology and presented examples of structural and operational actions, which could be carried out. The authors did not describe the methodology of energy labeling of water distribution systems but stated that the development of this methodology was the main objective of a new EC directive project, which is now under evaluation.
|15. Labeling Water Transport Efficiencies |
|The authors presented metrics for objective assessment of the efficient use of energy in the water supply. The metrics were based on adding environmental costs to water and energy costs. The main contribution of this paper was a global energy score (IS), which is a combination of several metrics.||The global energy score IS could be calculated as:|
—the energy embedded in leaks
—economic energy leakage losses reference level
—the energy dissipated through friction in pipes and valves
—economic energy friction losses references level
—energy pumping station losses
—economic energy pumping losses reference level
—global energy loss reference, equal to + +
γ1—the weighting factor for energy leakage losses reference
—the weighting factor for energy friction losses reference
—the weighting factor for energy pumping losses reference
The value of actual losses was calculated by means of an energy audit .
The reference value of an indicator could be calculated using:
The EPANET model was used.
The authors presented a case study using a simple network with 13 pipes, 10 nodes, two pumps, and a reservoir. The authors presented an energy and water audit for the network. In the article, the authors also provided a detailed description of methods of calculating reference values for the indicators.
|16. A Comprehensive and Well Tested Energy Balance for Water Supply Systems |
|This article presented energy balance and performance indicators for assessing water distribution networks. The methodology consisted of three stages: system characterization and data collection, energy balance calculation, and performance indicator assessment. The authors described the novel features of their audit method and differences between their energy balance and previous ones (e.g., Cabrera et al. ).||The methodology was based on three stages:|
E2—Energy in excess per unit of authorized consumption (kWh/m3), defined as:
E2 = (Etot − Emin− Erec)/∀AC
Etot—total input energy
Emin—the minimum required energy to supply consumers
Erec—energy recovery from the system
∀AC—annual authorized consumption
E2 (natural)—Natural energy in excess per unit of authorized consumption (kWh/m3), defined as:
E2 (natural) = (EN − Emin− Erec)/∀AC
EN—natural energy input to the system
Figure A2 Energy balance scheme 
E2 (shaft)—Shaft energy in excess per unit of authorized consumption (kWh/ m3), defined as:
E2 (shaft) = (ES − Emin− Erec)/∀AC
ES—shaft energy input to the system
E3—Ratio of the total energy in excess (–), defined as:
E3 = (Etot − Emin− Erec)/Emin
E3 (network)—Ratio of the energy in excess due to network operation and layout (–), defined as:
E3 (network) = (Esurp + Ediss,pAC + Ediss,vAC)/Emin
Esurp—surplus energy in the system
Ediss,pAC—energy loss due to friction associated with authorized consumption
Ediss,vAC—energy loss in valves associated with authorized consumption
E3 (pumps)—Ratio of the energy in excess due to dissipated energy in pumps, defined as:
E3 (pumps) = (Ediss,SAC)/Emin
Ediss,SAC—dissipated energy in pumping stations
E3(losses)—Ratio of the energy in excess due to water losses, defined as:
E3 (losses) = (EWL− ErecWL)/Emin
EWL—input energy associated with water loss
ErecWL—component of recovery energy associated with water loss
The simplified assessment did not require modeling. During the complete assessment, the EPANET model of a water distribution system could be used to calculate the energy balance values.
The simplified energy balance was tested for 17 water utilities in Portugal, and it was shown that there was significant potential for energy saving in the water sector through reductions in water loss, changes in the network operation layout, and reduced pump inefficiency.
The complete assessment was performed using a calibrated model of a water distribution system supplying water to 62,306 consumers in southern Portugal. The simulation was made for one year, considering winter and summer daily consumption patterns with a 15-min time interval.
|17. Energy Balance for a Water Distribution System |
|In this research, the energy balance for a water distribution system was presented. The balance was obtained using the law of energy conservation.||The energy balance was presented as follows:|
—the energy at sources (kWh)
—the energy at pumps (kWh)
—the energy lost in pipe friction (kWh)
—the energy lost in valves (kWh)
—the energy recovered at turbines (kWh)
—the energy at tanks (kWh)
—the energy used to raise the water to node elevation (kWh)
—the energy delivered to customers or leaks (kWh)
A computer model of a water distribution system was used.
Two case studies for the energy balance were presented. It was noted that the energy balance allowed one to compare different systems. It was emphasized that it could be difficult to compare energy balance values between systems because each system has specific characteristics. It was also necessary to collect a large quantity of data to perform an audit. Because of this, the authors stated with regard to the energy balance: “it is not certain whether this can become a practical engineering tool”. It was pointed out that the minimization of energy losses might be profitable only for water mains. The authors pointed out that in some countries, such as the United States, networks are designed for fire conditions, and therefore the values of energy losses due to friction in pipes are usually small or negligible. The energy balance could be used to better describe the network, but, in engineering practice, the derivation of the balance would not in itself increase energy efficiency. Increased efficiency is possible only through corrective actions. In some cases, the preparation of a balance might support the planning of such tasks.
|18. Energy Metrics for Water Distribution System Assessment: Case Study of the Toronto Network |
|The authors presented an energy metric for a water distribution system based on EPANET modeling. Aggregate indicators of capacity, efficiency, and costs were given.||The energy metric was derived from the following general equation:|
—the energy supplied at pumps, tanks, and reservoirs (Wh)
—the energy dissipated in pipes, pumps, connections, and valves due to friction and inefficiency (Wh)
—the energy lost due to leakage of pressurized water (Wh)
—the energy delivered to nodes or tanks in the form of pressure and velocity, including requirements and excess energy (Wh)
—the potential energy established by the difference in elevation between supply and delivery
The authors presented equations for calculating each value.
The EPANET model was used.
The case study concerned a skeletonized model of the Toronto water distribution system. The system consisted of 6000 km of water mains and served a population of 470,000. The article included a graph of daily energy dissipation due to different causes in two scenarios: winter and summer. Also, the daily cost of energy and the amount of CO2 produced were presented. The calculated metrics for all pipes were shown on maps.
|19. From Energy Balance to Energy Efficiency Indicators, Including Water Losses |
|The main objective of this work was to determine a methodology for assessing the energy efficiency of the entire water supply system and to determine the impact of water losses on the value of energy efficiency indicators. Indicators were determined on the basis of the energy balance described by Cabrera et al. .||The following performance indicators were proposed as additions to the energy balance:|
—the difference between the minimum potential energy of water supplied to users and potential energy input to the system during the simulation period; Emin was determined according to the definition given by Pelli and Hitz 
—the energy actually consumed by the pumps (kWh)
—the energy consumed by the pumps in hypothetical zero-leakage conditions (kWh)
LEE—Leakage energy efficiency, defined as:
—the energy supplied to the water by all pumping stations (kWh)
EPANET software was used for the calculation of performance indicators.
The methodology was tested in two case studies. The first concerned Ganaceto DMA, part of the water distribution system in Modena, Italy, with a 35.37 km network, serving a population of 2925. The second was for Marzaglia DMA, part of the Modena system with a 5km network, serving a population of 1247, with two variable-speed pumps.
|20. Measuring Energy Efficiency in Urban Water Systems Using a Mechanistic Approach |
|In this paper, the authors presented an energy efficiency metric for raw water extraction in an urban water supply system. The authors gave a score based on the ratio between minimum and actual energy usage in water utilities. This approach was contrasted with a benchmarking method based on an empirical approach.||The mechanistic approach was based on analyzing the energy requirements of each asset in the process. The scope of the research was limited to raw water pumping. The thermodynamic score was defined as:|
—minimum required energy (J), described as a function:
—theoretical minimum required to deliver raw water to the treatment station, defined as:
The authors used the Darcy–Weisbach equation to calculate friction loss.
The scope of the research was limited to raw water pumping. A case study for eight voluntary water utilities in Virginia was described. The result obtained for the thermodynamic score was compared with an energy benchmarking methodology . The authors compared the two methods and showed the advantages and disadvantages of each. Both types of methodology were needed for a good complete assessment.
|21. Modeling of Hydraulic and Energy Efficiency Indicators for Water Supply Systems |
|The authors proposed a methodology for calculating energy efficiency indicators for pumps. The main aim of the research was to create new energy effectivity indicators. The main reason for undertaking the research was problems with using standard energy consumption indicators (unit energy consumption per m3). The proposed indicators were developed using the general definition of effectiveness, described as the ratio of the targeted effect on the number of resources necessary to implement the process.||The following performance indicators were proposed:|
—the energy delivery to the user (kWh)
—the total energy consumed by the system (kWh)
—the minimum energy necessary to meet consumer demand, assuming that there is no pressure excess at any junction (kWh)
—target-value energy, the minimum energy supplied to the system, assuming that the system is operated optimally in technological terms. This value is obtained through optimization;
—current energy consumption (kWh)
The authors proposed a general energy efficiency indicator. This indicator described how the current situation (value of indicators) corresponded to the optimal hydraulic conditions of operation. This indicator was defined as:
VA—target value of the analyzed component (indicator)
S—current value of the indicator
The authors focused only on the assessment of the energy use of pumps (using characteristics of pumps and pipes).
The methodology was based on comparing the values of indicators for pumps in operation and model pumps operating in optimal conditions. The analyzed case study concerned a simple system consisting of a pump and a reservoir. In the study, the potential gains from optimization were calculated. The authors gave examples of methods for determining optimal pump operating conditions. The study was supplemented by guidelines for improving energy efficiency in water supply systems.
|22. Impact of Pipe Roughness on Pumping Energy in Complex Distribution Systems |
|This paper considered the impact of pipe roughness on the amount of energy consumed in the process of pumping water and the impact of system rehabilitation on increasing the energy efficiency of the system.||Potential energy savings for various recovery plans for the water supply network were analyzed. The Hazen–Williams equation was used to estimate head losses in pipes. The methodology entailed comparing different scenarios of system modernization and calculating the percentage change in energy dissipation for each scenario.||Bottom-up methodology|
A computer model of a water distribution system was used.
The research was conducted using real data for a system consisting of 28 pumping stations, 5900 km of network, and 121 pumps, which pump 530 megaliters of water per day, supplying the one-million population of a city in the Midwestern United States. The case study showed that even in the case of a large system, the savings from pipe rehabilitation would be small. The authors calculated the possible savings at only 0.7% to −0.2%. For some scenarios, network renovation might increase the energy consumption of the entire system.
|23. Pipe-Level Energy Metrics for Energy Assessment in Water Distribution Networks |
|This article described methods for assessing energy transformation in individual pipelines of water supply systems.||The following equation was obtained as an energy balance for pipes:|
—the energy supplied to the upstream end of the pipe (kWh)
—the energy delivered to the user to satisfy demand at required pressure head (kWh)
—the energy that flows out of the pipe to meet downstream user demands (kWh)
—the energy lost from water loss due to leakage (kWh)
—friction energy loss to meet the demand at the end of each pipe (kWh)
—friction energy loss to carry a portion of the flow to meet leakage at the end of each pipe (kWh)
—frictional losses associated with the conveyance of flow to downstream users (kWh)
—local energy losses through valves or turbine, or blockages (kWh)
The article described methods for calculating the above values, using computer models of water supply networks. The EPANET software was used.
The authors proposed performance indicators, describing the efficiency of energy use in the water supply system:
The authors used the EPANET Toolkit and Visual Basic code to model the water supply system.
The article presented example calculations of the energy balance and performance metrics for water supply networks. Two case studies were presented. The first concerned a network with 12 pipes with a total length of 19,260 m. The second concerned the network reported by Cabrera  with 14 pipes totaling 40 km. Numerical values of the calculated indices were given, but no rules for their evaluation (acceptable values) were defined.
|24. Life-Cycle Energy Analysis of a Water Distribution System |
|The authors proposed an LCA (life-cycle energy analysis) to assess the total amount of energy consumed during the production, operation, and disposal of water transport lines. The total energy consumption was calculated using unit indicators.||According to the methodology, the total amount of energy necessary for the production, use, and utilization of the pipeline was defined as a sum of energy used during:||Bottom-up methodology|
The authors used the EPANET model to estimate energy dissipation due to friction.
Case study analyses were carried out, for example, simple water supply networks consisting of 16 and 20 nodes (the New York Tunnel problem). A sensitivity analysis was also carried out—the authors showed how the final result (the total amount of energy consumed) was affected by changes in the model parameters, such as pipe roughness.
|25. Life-Cycle Assessment of a Water Distribution System Pump |
|Use of the EIO-LCA (economic input-output life-cycle assessment) methodology was proposed to determine the overall life cycle costs of pumps. The article described a model only for pumps, the element of the water supply system with the highest energy demand.||Methods for determining life cycle costs, the amount of energy consumed, and greenhouse gas emissions were described. Indicators and rules for calculating the values of these parameters for the EIO-LCA methodology were given. The methodology of indicator assessment consisted of comparing values of indicators for different pump operation scenarios. In the analysis, technical aspects (energy consumption), as well as environmental (greenhouse gas emissions) and economic aspects (cost, planning period, discount rate, etc.), were considered.||Bottom-up methodology |
The hydraulics of the system were represented by the pump and system characteristic curves.
A case study considered a pump installed in an Ontario water treatment plant. The analyses covered the years from 1997 to 2003.
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|Performance Indicators, Reference Value, and Performance Assessment||Physical Process Modeling||Set of Recommendation|
|1. IWA Manual of Performance Indicators for Water Supply Services ||Top-Down||Five indicators|
No reference value
|No||The set of recommendation about implementing a performance assessment system is presented|
|2. ECAM—Energy Performance and Carbon Emissions Assessment and Monitoring Tool ||Top-Down||18 indicators|
Internal benchmarking and reference value from literature
|No||Web-based learning platform|
|3. IBNET—The International Benchmarking Network [7,8]||Top-Down||Two indicators|
|No||A Web-based platform for supporting water utility managers was developed in the project.|
|4. AquaRating ||Top-Down||Two indicators with a reference value|
Eight good practice
|No||Set of good practice, a case study published on a Web page|
|5. EPA’s Energy Use Assessment Tool ||Top-Down||Unit energy usage and cost indicators|
|No||Guide and Excel spreadsheet|
|6. Water Research Foundation—Toolbox for Water Utility Energy and Greenhouse Gas Emission Management ||Top-Down||No (present a review of indicators used in other projects)||No||Several case studies and recommendation arepresented|
|7. Energy Index Development for Benchmarking Water and Wastewater Utilities ||Top-Down||Performance metric (ratio between average energy use and the energy calculated from the statistical model)||Statistical model||Several case studies and recommendation arepresented|
|8. WATERGY: Energy and Water Efficiency in Municipal Water Supply and Wastewater Treatment—Cost-Effective Savings of Water and Energy ||Top-Down||No||No||The guide shows a collection of best practices|
|9. Tools for Energy Footprint Assessment in Urban Water Systems ||Top Down||Unit energy usage||No||Recommendations described in case study|
|10. Classification of Water Supply Systems Based on Energy Efficiency ||Top Down||Six performance indicators|
|No||The study shows the methodology which can help to assess big groups of different water utilities (e.g., In regulatory benchmarking)|
|11. Energy Indicators and Savings in Water Supply ||Bottom-Up||Two performance indicators|
The reference value based on the concept of minimal energy is presented
|Yes (model of ideal energy)||Set of recommendation about the possibility of energy recovery from the water supply system|
|12. Energy Audit of Water Networks ||Bottom-Up||Five performance indicators|
The concept of “minimal energy” can be used to determine a reference value
|Yes (computer model of water distribution system)||Recommendation about the energy audit of the water distribution system|
|13. Energy Assessment of Pressurized Water Systems ||Bottom-Up||Three performance indicators, additional to indicators from “Energy Audit of Water Networks”|
The concept of “minimal energy” can be used to determine a reference value
|Yes (computer model of water distribution system)||Presentation of methods for improving energy efficiency|
|14. Towards an Energy Labeling of Pressurized Water Networks ||Bottom-Up||Indicators from “Energy audit Water Networks” ||Yes (computer model of water distribution system)||Energy improvement methodology is presented with examples of structural and operational actions which can be carried out|
|15. Labeling Water Transport Efficiencies ||Bottom-Up||Global energy score indicators|
Reference value based on the economic level of leakage (ELL), infrastructure leakage index (ILI), economic level of friction (ELF), minimum efficiency index (MEI), and energy efficiency index (EEI)
|Yes (computer model of water distribution system)||Recommendation about methods of calculating reference values for the indicators|
|16. A Comprehensive and Well Tested Energy Balance for Water Supply Systems ||Bottom-Up|
|Seven performance indicators, additional to indicators from “Energy audit  of Water Networks” and Ph5 indicators from IWA Manual|
|Yes (computer model of water distribution system)||Recommendation about energy saving in the water sector through reductions in water loss, changes in the network operation layout, and reduced pump inefficiency|
|17. Energy Balance for a Water Distribution System ||Bottom-Up||No||Yes (computer model of water distribution system)||Example of action connected with energy consumption reduction|
|18. Energy Metrics for Water Distribution System Assessment: Case Study of the Toronto Network ||Bottom-Up||Several energy metrics are presented, but there are no new indicators described||Yes (computer model of water distribution system)||The big case study (Toronto network) is presented as a good practice of energy assessment|
|19. From Energy Balance to Energy Efficiency Indicators, Including Water Losses ||Bottom-Up||Four performance indicators||Yes (computer model of water distribution system)||Two case studies are presented to show how to choose appropriate strategies of energy reduction in the supply system|
|20. Measuring Energy Efficiency in Urban Water Systems Using a Mechanistic Approach ||Bottom-Up||One aggregated performance indicator|
The concept of “minimal energy” can be used to evaluate indicators value
|Yes (simple model based on Darcy–Weisbach equation)||In the study, the recommendation about supplement benchmarking with a mechanistic approach is underlined|
|21. Modeling of Hydraulic and Energy Efficiency Indicators for Water Supply Systems ||Bottom-Up||Three performance indicators and one general energy efficiency indicator (which can be used to evaluate changing energy consumption over time)||Yes (simple model based on characteristics of pumps and pipes)||The study is supplemented by guidelines for improving energy efficiency in water supply systems. The authors give examples of methods for determining optimal pump operating conditions|
|22. Impact of Pipe Roughness on Pumping Energy in Complex Distribution Systems ||Bottom-Up||No||Yes (computer model of water distribution system)||The case study shows the possible savings from pipe rehabilitation|
|23. Pipe-Level Energy Metrics for Energy Assessment in Water Distribution Networks ||Bottom-Up||Five performance indicators|
No reference value
|Yes (computer model of water distribution system)||Authors show the possibility to use metrics to help municipalities identify energy inefficiencies in and guide the rehabilitation of water mains to reduce energy use and operating cost|
|24. Life-Cycle Energy Analysis of a Water Distribution System ||Bottom-Up||No||Yes (computer model of water distribution system)||In the publication, the recommendation about model parameters’ impact on energy usage is presented.|
|25. Life-Cycle Assessment of a Water Distribution System Pump ||Bottom-Up||No||Yes (simple model based on pumps and pipes characteristic curves)||In the article, several conclusions about life-cycle costs, energy consumption, and GHG emissions are presented|
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