Elsevier

Environmental Modelling & Software

Volume 73, November 2015, Pages 272-285
Environmental Modelling & Software

A systemic framework and analysis of urban water energy

https://doi.org/10.1016/j.envsoft.2015.08.009Get rights and content

Highlights

  • Defines boundaries for the water-energy system.

  • Creates a framework for consistent analysis and management.

  • Clarifies how models address parts of the energy effect of the water ‘system’.

  • Quantifies water-related energy across multiple boundaries.

Abstract

Energy impacts of urban water systems are substantial, but not typically analysed systemically. We develop a new system boundary framework including a utility, the ‘bulk water supply authority’ (SB1); the ‘urban water system’ including water use (SB2); and the ‘regional water system’ (SB3). We use the framework to review existing models and show that most address only one boundary. We apply the framework to quantify thermal equivalents of water-related energy in SB1 and SB2, and identify that over 96% of water-related energy in South East Queensland (SEQ) is outside SB1 and within SB2. Consideration of energy influenced by water use is paramount to systemic energy efficiency and optimisation in the urban water system. Clear articulation of system boundaries will improve modelling and management of the energy impact of urban water. Systemic modelling will help decision makers answer increasingly integrated and cross-system and sector questions regarding water and energy interactions.

Introduction

The influence of urban water supply, water use and wastewater services is significant. It accounts for 13–18% of State electricity use, and 18–32% of state natural gas consumption in Australia and the United States (Kenway et al., 2011a, Kenway et al., 2011b, Kenway et al., 2011c, Klein et al., 2005). The energy use of water utilities for pumping and treatment typically accounts for 10% of water-related energy. Energy use related to water use within households, industry and commerce typically accounts for more than 80% of the energy use in the “urban water cycle” for example, for water heating (Arpke and Hutzler, 2006, Cheng, 2002, Stokes and Horvath, 2009). Water-related energy is energy use which is directly or indirectly influenced by changes to water (Klein et al., 2005).

Energy use for water is a growing business risk in many nations, both to water utilities and the populations they support (Goldstein et al., 2008, Hightower and Pierce, 2008, Victorian Water Industry Association, 2011, WBCSD, 2009). In Australia, for example, the energy demand for urban water is anticipated to increase by approximately 200% of 2007 levels by 2030 (Cook et al., 2012, Kenway et al., 2008). Most of the influence is due to increased dependence on energy-intensive water supply sources such as desalination and recycling. Population growth, spreading cities, and tightening water and wastewater regulatory standards also contribute to growing energy demands. In combination with rising electricity costs, the total energy bill paid by water utilities is anticipated to grow in Australia to around 500% of 2007 levels by 2030 (Cook et al., 2012).

Most analysis of the water-energy nexus ignores discussion of “the system boundary”. In the relatively few papers observed where boundary issues are mentioned, the observations are brief. For example, in a thorough review of integrated modelling, (Bach et al., 2014), system boundary delineation is described as selecting the “level of integration”. Clear articulation of boundary, and acknowledgement on the significant influence on results, is an important issue because the “selected” boundary can have a major influence on decisions connected to the aim of the study. For example, Paton et al. (2014), propose an integrated framework to assess “urban water supply security of systems with non-traditional sources of water under climate change”. The issue of system boundary is not discussed in the method which aims to identify preferred solutions. The authors conclude that “should minimising greenhouse gas emissions [of new water sources] be an objective, the high-energy of desalination plants would render these alternatives as less favourable than indicated by this study”.

Boundary definition is a critical first step in modelling analysis (Decker et al., 2000, French and Geldermann, 2005, Satterthwaite, 2008, Sterman, 1991) inextricably interconnected with the study aims. Without a clear boundary description, it is impossible to know which factors should be included in, or excluded from, analyses (Sterman, 1991). The boundary unequivocally influences decisions of the apparent best option (2007; French and Geldermann, 2005, Parnell et al., 2011). Consequently, clear boundaries are paramount to good decision-making. But how should we define these boundaries given the highly interconnected nature of urban water and energy systems?

Given this, the research question and modelling objective of this work focusses on understanding how boundaries of the urban water system can be defined to quantify their wide energy impacts. This information contributes internationally to a new structure, method, and language relevant for water (or energy) analysts wishing to systematically evaluate the energy effect of water within cities. It is also relevant to those wishing to compare and prioritise options across those boundaries. It is particularly relevant when comparisons are needed across options water supply and demand solutions which is increasingly needed in urban water management (Rozos and Makropoulos, 2013).

A hypothesis driving our work is that most current analysis of energy influences in urban water deal only with parts of the “water system”. An outcome of this is that it is difficult for decision-makers to identify true least-energy (or ultimately least-cost) solutions in the design and operation of urban water systems. Our rationale is that consideration of wider boundaries than individual water utilities is necessary in order to identify solutions which address water-energy problems, rather than moving them around.

Section snippets

Background and context

This paper addresses the first stage of a wider project exploring the extent to which a bulk water supply authority (Seqwater) can improve energy efficiency (and related costs and greenhouse gas emissions) directly through their operations, as well as influencing systemic change. The research objective is to evaluate energy efficiency, and improve systemic decision-support in urban water. Systemic efficiency is encouraged by the Statement of Obligations under which Seqwater operates (Queensland

Material and methods

This research had three principle methods: (i) identification of energy questions relevant to water stakeholders; (ii) definition of system boundary, and (iii) use of the boundary to quantify water-related energy throughout the system.

System boundaries

Three boundaries were defined to reflect the main grouping of the diverse questions identified. As discussed in Section 3.2, this was an iterative process as the definition of the boundaries themselves led to new and clearer versions of the questions. The boundaries defined included: the bulk water supply assets (System Boundary 1, SB1); and the urban water system (SB2). A third boundary, the regional water system, was also conceptualised (SB3) (Fig. 2). These are described below.

System boundary 1 – the bulk water supply asset system

As many

Conclusions

This paper demonstrates how defining system boundaries provided a framework against which the wide-ranging impacts of urban water could be considered. Analysis of system boundaries 1 and 2 identified that approximately 90% of water-related energy use is outside the boundary of water and wastewater utilities in South East Queensland. Over 96% is outside the influence of the Bulk Water Supplier (SB1). The dominant component of water-related energy is influenced by water end use. While this is

Acknowledgements

The authors would like to thank Seqwater for their support of this research and active participation in the research. We also thank the Australian Research Council (LP120200745) and Smart Water Fund for support. Thanks to stakeholders for their comments and Steve Conrad and Beatriz Reutter for comments on earlier drafts.

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