Demand response within the energy-for-water-nexus - A review. ESRI WP637, October 2019

A promising tool to achieve more flexibility within power systems is demand re-sponse (DR). End-users in many strands of industry have been subject to research up to now regarding the opportunities for implementing DR programmes. One sector that has received little attention from the literature so far, is wastewater treatment. However, case studies indicate that the potential for wastewater treatment plants to provide DR services might be significant. This review presents and categorises recent modelling approaches for industrial demand response as well as for the wastewater treatment plant operation. Furthermore, the main sources of flexibility from wastewater treatment plants are presented: a potential for variable electricity use in aeration, the time-shifting operation of pumps, the exploitation of built-in redundan-cy in the system and flexibility in the sludge processing. Although case studies con-note the potential for DR from individual WWTPs, no study acknowledges the en-dogeneity of energy prices which arises from a large-scale utilisation of DR. There-fore, an integrated energy systems approach is required to quantify system and market effects effectively

Demonstrating demand response from water distribution system through pump scheduling

Significant changes in the power generation mix are posing new challenges for the balancing systems of the grid. Many of these challenges are in the secondary electricity grid regulation services and could be met through demand response (DR) services. We explore the opportunities for a water distribution system (WDS) to provide balancing services with demand response through pump scheduling and evaluate the associated benefits. Using a benchmark network and demand response mechanisms available in the UK, these benefits are assessed in terms of reduced green house gas (GHG) emissions from the grid due to the displacement of more polluting power sources and additional revenues for water utilities. The optimal pump scheduling problem is formulated as a mixed-integer optimisation problem and solved using a branch and bound algorithm. This new formulation finds the optimal level of power capacity to commit to the provision of demand response for a range of reserve energy provision and frequency response schemes offered in the UK. For the first time we show that DR from WDS can offer financial benefits to WDS operators while providing response energy to the grid with less greenhouse gas emissions than competing reserve energy technologies. Using a Monte Carlo simulation based on data from 2014, we demonstrate that the cost of providing the storage energy is less than the financial compensation available for the equivalent energy supply. The GHG emissions from the demand response provision from a WDS are also shown to be smaller than those of contemporary competing technologies such as open cycle gas turbines. The demand response services considered vary in their response time and duration as well as commitment requirements. The financial viability of a demand response service committed continuously is shown to be strongly dependent on the utilisation of the pumps and the electricity tariffs used by water utilities. Through the analysis of range of water demand scenarios and financial incentives using real market data, we demonstrate how a WDS can participate in a demand response scheme and generate financial gains and environmental benefits

Approximation of System Components for Pump Scheduling Optimisation

© 2015 The Authors. Published by Elsevier Ltd.The operation of pump systems in water distribution systems (WDS) is commonly the most expensive task for utilities with up to 70% of the operating cost of a pump system attributed to electricity consumption. Optimisation of pump scheduling could save 10-20% by improving efficiency or shifting consumption to periods with low tariffs. Due to the complexity of the optimal control problem, heuristic methods which cannot guarantee optimality are often applied. To facilitate the use of mathematical optimisation this paper investigates formulations of WDS components. We show that linear approximations outperform non-linear approximations, while maintaining comparable levels of accuracy

Multi-criteria analysis applied to multi-objective optimal pump scheduling in water systems

This work presents a multi-criteria-based approach to automatically select specific non-dominated solutions from a Pareto front previously obtained using multi-objective optimization to find optimal solutions for pump control in a water supply system. Optimal operation of pumps in these utilities is paramount to enable water companies to achieve energy efficiency in their systems. The Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is used to rank the Pareto solutions found by the Non-Dominated Sorting Genetic Algorithm (NSGA-II) employed to solve the multi-objective problem. Various scenarios are evaluated under leakage uncertainty conditions, resulting in fuzzy solutions for the Pareto front. This paper shows the suitability of the approach for quasi real-world problems. In our case-study, the obtained solutions for scenarios including leakage represent the best trade-off among the optimal solutions, under some considered criteria, namely, operational cost, operational lack of service, pressure uniformity and network resilience. Potential future developments could include the use of clustering alternatives to evaluate the goodness of each solution under the considered evaluation criteria

Rehabilitation of a water distribution system using sequential multiobjective optimization models

Identification of the optimal rehabilitation plan for a large water distribution system (WDS) with a substantial number of decision variables is a challenging task, especially when no supercomputer facilities are available. This paper presents an initiative methodology for the rehabilitation of WDS based on three sequential stages of multiobjective optimization models for gradually identifying the best-known Pareto front (PF). A two-objective optimization model is used in the first two stages where the objectives are to minimize rehabilitated infrastructure costs and operational costs. The optimization model in the first stage applies to a skeletonized WDS. The PFs obtained in Stage 1 are further improved in Stage 2 using the same two-objective optimization problem but for the full network. The third stage employs a three-objective optimization model by minimizing the cost of additional pressure reducing valves (PRVs) as the third objective. The suggested methodology was demonstrated through use of a real and large WDS from the literature. Results show the efficiency of the suggested methodology to achieve the optimal solutions for a large WDS in a reasonable computational time. Results also suggest the minimum total costs that will be obtained once maximum leakage reduction is achieved due to maximum possible pipeline rehabilitation without increasing the existing tanks

Multiobjective optimization of water distribution systems accounting for economic cost, hydraulic reliability, and greenhouse gas emissions

In this paper, three objectives are considered for the optimization of water distribution systems (WDSs): the traditional objectives of minimizing economic cost and maximizing hydraulic reliability and the recently proposed objective of minimizing greenhouse gas (GHG) emissions. It is particularly important to include the GHG minimization objective for WDSs involving pumping into storages or water transmission systems (WTSs), as these systems are the main contributors of GHG emissions in the water industry. In order to better understand the nature of tradeoffs among these three objectives, the shape of the solution space and the location of the Pareto-optimal front in the solution space are investigated for WTSs and WDSs that include pumping into storages, and the implications of the interaction between the three objectives are explored from a practical design perspective. Through three case studies, it is found that the solution space is a U-shaped curve rather than a surface, as the tradeoffs among the three objectives are dominated by the hydraulic reliability objective. The Pareto-optimal front of real-world systems is often located at the "elbow" section and lower "arm" of the solution space (i.e., the U-shaped curve), indicating that it is more economic to increase the hydraulic reliability of these systems by increasing pipe capacity (i.e., pipe diameter) compared to increasing pumping power. Solutions having the same GHG emission level but different cost-reliability tradeoffs often exist. Therefore, the final decision needs to be made in conjunction with expert knowledge and the specific budget and reliability requirements of the system. © 2013. American Geophysical Union. All Rights Reserved.Wenyan Wu, Holger R. Maier, and Angus R. Simpso

Pump Scheduling for Optimised Energy Cost and Water Quality in Water Distribution Networks

Delivering water to customers in sufficient quantity and quality and at low cost is the main driver for many water utilities around the world. One way of working toward this goal is to optimize the operation of a water distribution system. This means scheduling the operation of pumps in a way that results in minimal cost of energy used. It is not an easy process due to nonlinearity of hydraulic system response to different schedules and complexity of water networks in general. This thesis reviewed over 250 papers about pump scheduling published in the last 5 decades. The review revealed that, despite a lot of good work done in the past, the existing pump scheduling methods have several drawbacks revolving mainly around the ability to find globally optimal pump schedules and in a computationally efficient manner whilst dealing with water quality and other complexities of large pipe networks. A new pump scheduling method, entitled iterative Extended Lexicographic Goal Programming (iELGP) method, is developed and presented in this thesis with aim to overcome above drawbacks. The pump scheduling problem is formulated and solved as an optimisation problem with objectives being the electricity cost and the water age (used as a surrogate for water quality). The developed pump scheduling method is general and can be applied to any water distribution network configuration. Moreover, the new method can optimize the operation of fixed and variable speed pumps. The new method was tested on three different case studies. Each case study has different topography, demand patterns, number of pumps and number of tanks. The objective in the first and second case studies is to minimise energy cost only, whereas in the third case study, energy cost and water age are minimized simultaneously. The results obtained by using the new method are compared with results obtained from other pump scheduling methods that were applied to the same case studies. The results obtained demonstrate that the iELGP method is capable of determining optimal, low cost pump schedules whilst trading-off energy costs and water quality. The optimal schedules can be generated in a computationally very efficient manner. Given this, the iELGP method has potential to be applied in real-time scheduling of pumps in larger water distribution networks and without the need to simplify the respective hydraulic models or replace these with surrogate models

Controlling evaporation loss from water storages

[Executive Summary]: Evaporation losses from on-farm storage can potentially be large, particularly in irrigation areas in northern New South Wales and Queensland where up to 40% of storage volume can be lost each year to evaporation. Reducing evaporation from a water storage would allow additional crop production, water trading or water for the environment. While theoretical research into evaporation from storages has previously been undertaken there has been little evaluation of current evaporation mitigation technologies (EMTs) on commercial sized water storages. This project was initiated by the Queensland Government Department of Natural Resources and Mines (NRM) with the express aim of addressing this gap in our knowledge. The report addressed i) assessment of the effectiveness of different EMT’s in reducing evaporation from commercial storages across a range of climate regions, ii) assessment of the practical and technical limitations of different evaporation control products, and iii) comparison of the economics of different EMT’s on water storages used for irrigation

Non-linear economic model predictive control of water distribution networks

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper addresses a non-linear economic model predictive control (EMPC) strategy for water distribution networks (WDNs). A WDN could be considered as a non-linear system described by differential-algebraic equations (DAEs) when flow and hydraulic head equations are considered. As in other process industries, the main operational goal of WDNs is the minimisation of the economic costs associated to pumping and water treatment, while guaranteeing water supply with required flows and pressures at all the control/demand nodes in the network. Other operational goals related to safety and reliability are usually sought. From a control point of view, EMPC is a suitable control strategy for WDNs since the optimal operation of the network cannot be established a priori by fixing reference volumes in the tanks. Alternatively, the EMPC strategy should determine the optimal filling/emptying sequence of the tanks taking into account that electricity price varies between day and night and that the demand also follows a 24-hour repetitive pattern. On the other hand, as a result of the ON/OFF operation of parallel pumps in pumping stations, a two-layer control scheme has been used: a non-linear EMPC strategy with hourly control interval is chosen in the upper layer and a pump scheduling approach with one-minute sampling time in the lower layer. Finally, closed-loop simulation results of applying the proposed control strategy to the D-Town water network are shown.Peer ReviewedPostprint (author's final draft