Water Demand Profiles Research Articles

Small-scale district heating system as heat storage for decentralized solar thermal collectors during non-heating period

Solar thermal energy usage in the Baltic countries is currently low, so there is a need to find technically and economically feasible solutions to increase the appeal of this technology. Integration of solar energy into existing district heating systems is a way to increase the share of renewable energy sources while utilizing the existing infrastructure, thereby reducing capital investments, as well as mitigating the risk of solar collector overheating and eliminating the need for local storage tanks in buildings. This study presents a parametric study for evaluating the effectiveness of using a district heating system to store heat produced by decentralized solar thermal collectors and comparing the district solution to the traditional local solution. The TRNSYS 18 model was developed for this purpose. The model investigates the impact of different hot tap water demand profiles as well as pipeline diameters and lengths on system energy efficiency, showing a statistically significant difference (p < 0.05) between installing solar collectors on residential and restaurant or office roofs, and no significant difference (p = 0.24) between restaurant and office. The model shows that solar energy can be shared within a 500 m distance between neighborhoods and that a larger main pipeline diameter can increase overall system efficiency.

Social practice theory and household water demand: A review of literature and research evidence

AbstractThe changing climate, rapid increases in global consumption, and shock events are increasing stress on water resources globally. For policy makers and water sector stakeholders tasked with reducing demand, and for academic researchers interested in understanding how these complex issues intertwine to create current and future water demand profiles, the shortcomings of individualized behavior change approaches driven by psycho‐econometric understandings of resource consumption is increasingly evident. Since the early 2000s, social practice theory has been increasingly recognized as deepening understandings of the complex ways water is consumed and the dynamic factors that influence household demands. This review examines evidence of how social practice ideas are deployed in academic research in scope (theory; geographical; practices entities/performances; sites, locations, and temporality of practices; infrastructural configurations); methods (historical; talk—interviews, focus groups; diaries; ethnography and home tours; surveys; living labs, experiments, design methods; mixed methods); and implications (co‐production; materiality; diversity; disruption and insecurity; inequalities) including for policy and practice. Emerging from the review is a set of ideas that demonstrate how to apply insights from social practice more effectively in water studies and in water management, aiding the exploration of new areas of enquiry, policies and mechanisms to enable less intensive patterns of water use. This review points to a need for increased collaboration across the water sector and wider stakeholders to enact deep and meaningful change to how water is supplied and consumed in society.This article is categorized under: Human Water &gt; Water Governance Human Water &gt; Methods Human Water &gt; Value of Water

Reliability and availability modelling of a retrofitted Diesel-based cogeneration system for heat and hot water demand of an isolated Antarctic base

The reduction of greenhouse gas emissions is a relevant challenge for a sustainable development. Waste heat could be used to produce hot water by using a recovery system. This article studies the availability of a combined heat and power systems (CHP) in extreme area (Antarctic) through the integration of a waste heat recovery system with a diesel generator to produce hot water. The reliability and availability principles are incorporated to explore how the profile of hot water consumption and the hot water storage tank size affect system availability. Different combined heat and power systems are thus classified, and their availability indexes modelled by adopting the continuous Markov approach and the state space model. The results indicate that the CHP systems availability is strongly influenced by the daily hot water demand profile. As a useful recommendation, one of the considerations for increasing availability, reducing costs and greenhouse gas emissions with the CHP system is to include a hot water tank in the analysis.

The impact of mutual interaction between electric and water distribution systems via demand response

Peak demands for electricity and water can be managed in a sustainable size and shape via residential demand response. Moreover, the mutual interaction of electric and water distribution management systems can enable to present new services and benefits. The collaborative loads that have both manageable electrical demand and water capacity can have great roles in the interaction. Peak electricity demand can be shaped by deferring their working schedule, interrupting of their run cycles, and assigning new set values that can lead to less consumption when the electricity demand and its price are high. In this paper, novel methods were introduced to uncover the impact of the residential electric demand response on household water demand. The methods were proposed for manageable capacities of electricity and water, daily normalized profile, feature extraction, and problem formulation. A feature extraction method based on Empirical Mode Decomposition was used to find convenient case profiles for incentives. Realistic electricity and water demand profiles were generated with twelve activities in 100 houses via MATLAB. Time intervals of the electricity tariff and the intervals belong to the user’s daily habits were placed in the activity-based power profiles. A high correlation was obtained in the daily normalized demand for electricity and water. Collaborative appliances had a significant share (approximately 34%) in total electricity demand. Deferring collaborative loads from on-peak time caused the shaping of the water demand. The amount of the water managed in on-peak time was between 87.35 L and 120.96 L case by case in a home.

Evaluation of harvesting urban water resources for sustainable water management: Case study in Filton Airfield, UK

Filton Airfield in the UK is a new community under development aiming to become self-sufficient in its water supply toward a circular economy. Urban water management strategies, water demand minimization, urban resource reuse, and wastewater discharge minimization, can improve the urban circular economy. Understanding the practical impacts of those strategies is crucial for a new development area like Filton. As a site investigation, the physiochemical and microbial characteristics of raw rainwater showed acceptable for irrigation and drinking water, indicating no significant risk of using rainwater collected within Filton, but still requiring a treatment process depending on chosen applications. This study further conducted stochastic water demand profiles and urban water cycle simulations at a block scale, taking possible rainwater harvesting (RWH) and greywater recycling (GWR) options for non-potable purposes to quantitatively assess the impact of urban water management strategies on urban harvesting potential indicators (0–100%). When the RWH was implemented, the water demand minimization potential varied from 62% to 71%. Meanwhile, the combined use of RWH and GWR yielded even better results in terms of water demand minimization, peaking at 78% due to the additional supply from GWR. The combination also reduced wastewater production potential from 100% to 54% and consequently improves self-sustainability potential from 0 with no recycling, to 44% with only GWR, and to 100% with the combined use of RWH and GWR. The sensitivity analysis revealed that wastewater discharge is the most sensitive to variations in rainfall patterns (wet and dry conditions) and urban density (water demand patterns), indicating that both need to be balanced for better implementation of urban water harvesting strategies. This study can provide insights into the applicability of urban water resource harvesting and its assessment approaches in existing and new development areas.

Water demand profile before and during COVID-19 pandemic in a Brazilian social housing complex

The COVID-19 pandemic has changed the way resources are consumed around the world. The relationship between the pandemic and water consumption has important implications for the management of water use and must be evaluated in depth. The main goal of this research paper is to establish a comparison between pre-pandemic and pandemic water consumption profiles for 14 social-housing buildings located in Joinville, Southern Brazil. Telemetry data from each apartment were collected on an hourly basis before and during the COVID-19 pandemic. The analysis was based on descriptive statistics on the hourly and daily water consumption in addition to its profile plots. The best probability distribution fitting was also determined. To assess the differences in water consumption due to de pandemic, the Wilcoxon-Mann-Whitney test was employed and a Generalized Linear Model with mixed effects was fitted to the data. The Lognormal distribution was shown to be the most appropriate to model the water consumption data. Due to the COVID-19 pandemic, the two daily peak consumption periods changed from 12 h to 15 h and from 19 h to 21 h. The COVID-19 pandemic also impacted daily water consumption, leading to a small, yet significant, increase in demand in the first quarter of the pandemic period.

The impact of climate change on rainwater harvesting in households in Poland

In water management, climate changes require adaptation, protection of existing resources and the search for alternative water sources. Rainwater harvesting (RWH) is increasingly becoming an alternative water source, applicable for many directions of its use. The aim of the research was to analyse the influence of long-term climate change on the potential for rainwater harvesting in households in Central Europe in Poland. The analysis of long-term climate changes impact on the household rainwater harvesting potential was conducted for the 50-year period for 19 cities in Poland. The water balance model was operated in a day-step mode, and the research was carried out in four “time scales approach”. For the purpose of all analyses, a standard weekly water demand profile was developed. It includes the daily sub-profiles for every working day and weekend, covering the washing and toilet flushing needs for a 4-person household. In order to evaluate the long-term changes in residential harvesting in Poland, a hypothetical residential RWH was investigated in 19 locations and rainfall conditions. To illustrate the time-spatial variation of annual rainfall amounts in the analyzed period, the heat map was prepared as the pre-simulation stage. Results show that the design of RWH systems should be based on archival data and take into account the many years of rainfall changes. This will improve performance and secure benefits for the users of this system.

Human-Infrastructure Interactions during the COVID-19 Pandemic: Understanding Water and Electricity Demand Profiles at the Building Level.

When engineers design and manage a building’s water and electricity utilities, they must make assumptions about resource use. These assumptions are often challenged when unexpected changes in demand occur, such as the spatial and temporal changes observed during the coronavirus (COVID-19) pandemic. Social distancing policies (SDPs) enacted led many universities to close their campuses and implement remote learning, impacting utility consumption patterns. Yet, little is known about how consumption changed at the building level. Here, we aim to understand how water and electricity consumption changed during the pandemic by identifying characteristic weekly demand profiles and understanding how these changes were related to regulatory and social systems. We performed k-means clustering on utility demand data measured before and as the pandemic evolved from five buildings of different types at the University of Texas at Austin. As expected, after SDPs were enacted both water and electricity use shifted, with most buildings seeing a sharp initial decline that remained low until the university partially reopened. In contrast to electricity use, we found that water use was tightly coupled with SDPs. Our study provides actionable information for managers to mitigate negative impacts (e.g., water stagnation) and capitalize on opportunities to minimize resource use.

Meeting energy needs of low-income Sub-Saharan households with a Partially Hybridised Solar Technology (PHST): Experimental performance evaluation based on simulated solar radiation and demand profiles

Renewable energy technologies for sustainable development are rapidly attracting attention across many disciplines despite technical, economic, and social barriers that limit application beyond the laboratory. This study proposes novel semi-automated and automated domestic hot water and electricity demand simulation experiments to evaluate the performance of a proof-of-concept prototype under simulated solar conditions. The prototype is a Partially Hybridised Solar Technology (PHST) which integrates photovoltaic (PV) and low-temperature solar thermal technology for low-cost electricity and domestic hot water supply. The domestic hot water and electrical demand profiles, and the solar radiation utilised during the study represent typical conditions of off-grid households in Sub-Saharan Africa. The prototype delivered a thermal energy supply potential of 2,073±75kJ per day at an average solar thermal conversion efficiency of 29.4±1.0%. The average yield of Direct Current (DC) electricity was 273 Wh per day at a corresponding PV module efficiency of 12.1% but depended on the type of charge controller. These results provide essential baselines for future computer modelling work and techno-economic predictions for Sub-Saharan Africa. The study has important future implications to test standards guiding laboratory-based evaluation of Solar Home Systems (SHSs) for electricity and domestic hot water.

A novel spatial–temporal space heating and hot water demand method for expansion analysis of district heating systems

The fourth generation of district heating will play a significant role in the decarbonization of energy systems. In general, only space heating demand is considered when assessing the district heating potential, excluding hot water. In contrast, the hot water demand accounts for up to 18% of total final energy demand in buildings. Hence, in this paper, a spatial–temporal method for annual hot water demand is considered in conjunction with space heating demand while technically and economically assessing the expansion potential of the district heating. A bottom-up heat demand mapping process was carried out for Pristina city to identify the space heating demand of buildings, while a top-down approach was used for spatial mapping of hot water demand. Hourly, daily, weekly and seasonal hot water demand profiles, besides heating degree-day method used for space heating, were considered when estimating the temporal operation of district heating. The findings show that the existing district heating can be increased four times when excluding hot water and five times when considering both space heating and hot water demand of buildings. Moreover, the heat supply capacities needed in district heating to cover space heating and hot water demand would be 600 MW and 70 MW respectively.

Robust Scheduling for Pumping in a Water Distribution System under the Uncertainty of Activating Regulation Reserves

A new robust scheduling method for pumping water in a water distribution system under the uncertainty of activating regulation reserves is proposed in this paper. During the operation of power systems, utilizing the energy equipment of the customer to enhance supply-demand control is attracting attention. Because water pumps have been already installed, they can be regarded as a relatively inexpensive, operational, and flexible resource. Changes in the operation of the water pump can contribute to the power supply and demand control. The proposed method helps generate a robust daily schedule for pumping water and provides regulation reserves under the uncertainty of activating regulation reserves. It is based on electric energy prices and regulation reserves, hourly water demand profiles, and the properties of water flow quantity and the electricity consumption of water pumps. This method comprises an optimization model formulated using mixed integer linear programming, validated through simulations of water pumping scheduling under certain scenarios. The results indicate that the net operational cost decreased when water pumps provided regulation reserves; further, the operational feasibility of providing these reserves from water pumps is clarified. The proposed model makes it possible to optimize power system operation that integrates the water supply system.

Identifying and analyzing residential water demand profile; including the impact of COVID-19 and month of Ramadan, for selected developments in Dubai, United Arab Emirates

Abstract Consumption of water varies throughout the day due to the daily routines of the consumer. This pattern of daily water consumption is called the water demand profile. The initiatives to create these profiles are to improve hydraulic performance and to build energy conservation strategies for designed networks in Dubai. Therefore, the aim of the work presented here was to develop and analyze a domestic consumption profile for selected developments with socio-demographic factors including weekday/weekend variation, population, income, fasting during the month of Ramadan, and the outbreak of COVID-19. Data from more than 7000 smart meters were collected while water meters of more than 350 residential flats were examined manually. Water demand profiles generated from the data showed weekdays have more predictable peaks (morning 6–8 am and evening 5–7 pm) than weekends. During Ramadan, peak hours shifted to 7–10 am followed by 3–4 pm during workdays while peaks for low-income areas were higher due to a stricter working routine. The COVID-19 crisis has led to significant rise in observed consumption, with over a 30% increase during the month of Ramadan. The observed results, if compared with further end-use studies on more factors affecting demand profiles, can help in generating both cost and energy efficient networks.

Water-energy benchmarking and predictive modeling in multi-family residential and non-residential buildings

As the threat of climate change grows alongside a continual increase in urban population, the need to ensure access to water and energy resources becomes more crucial. In the context of the water-energy nexus in urban environments, this work addresses current gaps in understanding of coupled water and energy demand patterns and reveals apparent dissimilarities between utilization of water and energy resources for heterogeneous buildings. This study proposes a data-driven approach to identify fundamental water and energy demand profiles, cluster buildings into groups exhibiting similar water and energy use, and predict their demand. The clustering problem was cast as a two-stage cluster ensemble problem, in which several clustering methods with different settings were employed, and then the results obtained from partial view of the data were combined to achieve consensus among the partitionings. The influential drivers for water and energy consumption were identified, parametric and non-parametric prediction models were developed and compared, utilizing high and low temporal data resolution. The clustering analysis performed in this work revealed that water and energy consumption patterns of heterogeneous buildings are not exclusively characterized by general building characteristics. Analysis of the predictive models showed that an overall non-parametric model provides better predictions for water and energy compared with parametric models and that models with high and low data resolution provide comparable demand predictions. The results of this study highlight the value of data-driven modeling for revealing meaningful insights into usage patterns and benchmarking buildings’ performance to provide a meaningful measure of comparison to facilitate multi-utility management. Overall, the methods outlined in this study provide another step towards building greater resiliency within urban areas in preparation for future changes in population and climate.

Modelling, design, and experimental validation of a grid-connected farmhouse comprising a photovoltaic and a pumped hydro storage system

This paper investigates the value of using existing irrigation infrastructure to store surplus photovoltaic energy in a farmhouse. The irrigation system includes a reservoir and a water well. The depth of the water well is used to store energy in the form of gravitational potential energy. Throughout the day, photovoltaic energy is used to pump water from the bottom of a well to the reservoir at ground level, where this stored water is then used to meet demand by releasing the water back to the well through a hydro turbine. A controller is designed to manage the pump and the turbine efficiently to reduce daily electricity costs of the farmhouse. The proposed method is validated experimentally with a real pump and a turbine. The controller manages the pump power and turbine flow rate considering the losses of storage, the feed-in income, and the cost-saving for each decision. The proposed system is also simulated in MATLAB for a whole year using real data to investigate the economic aspects of this storage in different seasons with different irradiance, weather, energy demand, and water demand profiles.

Comparison of two dynamic approaches to modelling solar thermal systems for domestic hot water

In developing countries, the increase in the electricity access and therefore in the energy consumption through distributed energy solutions, leads to searching energy saving strategies. Solar Thermal Systems (STS) have been widely used to increase energy efficiency in residential sector in many countries, and several models are being developed to improve their performance and deployment. However many of existing software tools somehow fail to provide more sensitivity analysis to different parameters of STS performance, given their wide applicability.In this paper, two dynamic approaches to model STS are discussed: a developed hourly model based on energy balance of the STS components, and the simulation tool Polysun. A sensitivity analysis is made to different domestic hot water demand profiles and tank sizes, using as case study, a typical 5-person family house in Maputo, Mozambique.The results show that the developed hourly model can be used to evaluate and size solar thermal systems, having similar results to Polysun. However, regarding the auxiliary heating, Polysun approach leads to a higher or lower electrical auxiliary heating, depending on the control layer, resulting in over-sizing or under-sizing of the system, given that it considers the temperatures stratification while the developed model considers the energy balance in the tank as a whole.

A comprehensive study on the effect of hot water demand and PCM integration on the performance of SDHW system

In this study, a commercial SDHW for Tehran meteorological data is modeled numerically in order to investigate the effect of three main influential sets of parameters, including the solar system characteristics, the water demand profile, and the PCM integration. First, a sensitivity analysis of intrinsic parameters is conducted. Then, the system performance is analyzed under the thermal stratification effects. After recognition of the system, the effect of hot water demand and several time-profile is investigated. Finally, in order to determine the whole range of operating conditions, both fully-mixed (single-node) and fully-stratified (multi-node) tanks are considered for applying phase change material (PCM) as a storage medium. Genetic Algorithm (GA) is used to achieve the best PCM parameters including the melting temperature, and the total volume and its distribution in the storage tank. Sensitivity of the optimized PCM−embedded system to the melting temperature is conducted in order to propose some practical PCMs for use in such systems.According to the results, in the non-uniform high daily water consumption the thermal stratification is more beneficial which can lead to 9% increase in the ASF. Also, it is found out that a solar water heater system performance is very demand dependent so that it induces up to 8% ASF variation in different demand conditions. Therefore, integration of the PCM in SDHW systems, which can increase the ASF by 4%, is very case dependent with respect to the results of optimization and sensitivity analysis.

Reprint of: Smart meter enabled informatics for economically efficient diversified water supply infrastructure planning

Water efficiency measures and alternative supply sources alleviate peak water demand on urban water supply networks. Consequently, they also provide benefits to water service providers, in terms of augmentation deferrals and reduced sized infrastructure. However, while these benefits are acknowledged in the literature, they have not been thoroughly investigated and quantified. This paper empirically demonstrates how the installation of different potable water saving measures would affect the design of urban water supply networks. Peak day water demand profiles were developed for the baseline scenario, which represented the typical building code mandated for new dwellings constructed in Queensland, Australia, and for households fitted with water saving measures. The core novel feature of this study relates to the use of an innovative bottom-up approach to the development of demand profiles based on smart meters enabling comprehensive water end use datasets (i.e. demand in shower, tap, etc.) to be obtained. Hydraulic model runs were conducted for various water savings scenarios across different planning horizons to determine the scheduling of augmentations in a water supply study area. The results of the model runs showed deferred and eliminated augmentations, as well as reductions in infrastructure sizing for the water savings scenarios compared to the baseline scenario. Financial analysis (i.e. NPV) on trunk main augmentation requirements over 50 year asset life cycles indicated that savings of between $1,574,289 (11.4%) and $7,030,796 (51%) could be achieved by incorporating water efficiency and potable source substitution measures in new infill developments in the study region.

Urban residential energy consumption modeling in the Integrated Urban Metabolism Analysis Tool (IUMAT)

The Integrated Urban Metabolism Analysis Tool (IUMAT) is a system-based computational platform for quantifying the environmental impacts of urban development scenarios. IUMAT's EWM module is a bottom-up approach to generate energy, water, and material resources demand profiles based on building and neighborhood characteristics. This paper presents the EWM approach using national and regional datasets to identify the relationships between environmental impacts and resource use determinants within a simulation platform for urban metabolism analysis. We focus on residential energy consumption, which serves as a template for how the EWM module will be used to simulate commercial and industrial demand profiles. Quantile regression methods are applied to Residential Energy Consumption Survey (RECS) 2009 data to describe the impacts of physical and socio-economic parameters on end use residential energy profiles and create a modeling framework for residential energy prediction. Also, a method for quantifying CO2 emissions and water consumption associated with energy production is outlined.

Smart meter enabled informatics for economically efficient diversified water supply infrastructure planning

Water efficiency measures and alternative supply sources alleviate peak water demand on urban water supply networks. Consequently, they also provide benefits to water service providers, in terms of augmentation deferrals and reduced sized infrastructure. However, while these benefits are acknowledged in the literature, they have not been thoroughly investigated and quantified. This paper empirically demonstrates how the installation of different potable water saving measures would affect the design of urban water supply networks. Peak day water demand profiles were developed for the baseline scenario, which represented the typical building code mandated for new dwellings constructed in Queensland, Australia, and for households fitted with water saving measures. The core novel feature of this study relates to the use of an innovative bottom-up approach to the development of demand profiles based on smart meters enabling comprehensive water end use datasets (i.e. demand in shower, tap, etc.) to be obtained. Hydraulic model runs were conducted for various water savings scenarios across different planning horizons to determine the scheduling of augmentations in a water supply study area. The results of the model runs showed deferred and eliminated augmentations, as well as reductions in infrastructure sizing for the water savings scenarios compared to the baseline scenario. Financial analysis (i.e. NPV) on trunk main augmentation requirements over 50 year asset life cycles indicated that savings of between $1,574,289 (11.4%) and $7,030,796 (51%) could be achieved by incorporating water efficiency and potable source substitution measures in new infill developments in the study region.

Investigating the Financial Implications and Viability of Diversified Water Supply Systems in an Urban Water Supply Zone

Diversified water supply schemes can reduce both peak demand and overall demand in the urban water supply network. Consequently, they provide benefits to both the water utility and their customers including deferring network augmentations and reducing household water bills, respectively. However, the installation of different water saving scenarios also incurs additional costs which present a financial burden to the householder. This paper investigates the financial viability of installing alternative water supplies and water efficient appliances in a large scale area, taking into account both their benefits and incurred costs. Water demand profiles were developed for the baseline and various water saving scenarios for new dwellings in Queensland, Australia. Hydraulic model runs were conducted to determine system augmentation and pump power requirements for various water saving scenarios across different planning horizons in a water supply study area. The results of the modeling showed deferred augmentations and reduced pumping requirements for the water savings scenarios, compared to the baseline scenario; contributing to monetary savings to the utility. Cost benefits to the householders are from reduced mains water and energy consumption, with incurred costs from installing the water saving systems. A total net cost balance appraisal demonstrated monetary savings for the water efficient and rainwater tank scenarios while the greywater scenario produced negative net costs. The results are discussed along with incentives and potential savings to promote sustainable alternative water use in an urban area.