Investigation of sustainable and resilient design alternatives for water distribution networks

Nowadays there is a pronounced interest in the need for sustainable and resilient infrastructure systems to address the challenges of future infrastructure development. This paper presents a three-objective optimization model for the investigation of various sustainable and resilient design alternatives for water distribution networks. Although optimal design of water distribution networks is a thoroughly studied area, most researchers focused on efficient algorithms to solve the complex design problem. Cost has predominantly been the objective in previous studies with few models also considering resilience or environmental impacts (CO₂ emissions). This research combined all these parameters in a multi-objective model to obtain various sustainable and resilient design alternatives. The model is demonstrated on a three-loop benchmark network that was previously studied. The tradeoff between the objectives is further analyzed to identify the most beneficial solution from the pareto-optimal set of solutions. The dollar worth of enhancing resilience of the benchmark network by a unit is estimated to be in the range of $1.23 to $3.93 million, which translates to about 22% to 69% of the least possible life cycle cost. The results of this research reveal that resilience can be increased by paying a justifiable cost that will also compensate for CO₂ emissions.     

Optimal design of urban water supply pipe networks

This paper approaches the optimisation of looped water distribution networks supplied from one or more sources, according to demand variation. The pipe networks have concentrated outflows or uniform outflow along the length of each pipe. An optimisation model coupled with a computational iterative procedure of optimal discharges through pipes is developed on the basis of linear programming for the design of new or partially extended water distribution networks. The optimum solution obtained by this model consists of one or two pipe segments of different discrete sizes between each pair of nodes. The improved linear optimisation model guarantees a high reliability. Also, it is possible to take into account the network pipes with variable discharge on route. Additionally, the paper compares the linear optimisation model to some others, such as the classic model of economical velocities, the Moshnin model and a nonlinear model. This shows a good performance of the proposed model.     

Seismic design of water distribution networks using auto-generation techniques

A feasible approach that uses an auto-generation technique is proposed to design and retrofit water distribution networks (WDNs) subjected to earthquakes. Because pipelines are laid along roads, the road information is extracted and then integrated into the auto-generation technique whereby the rules relevant to laying the pipelines are established. An optimisation model with parameters of network topology and pipeline diameter is developed to design and retrofit WDNs, whose seismic functional reliability index serves as a constraint. An intelligent optimisation program via a particle swarm algorithm is employed to generate the optimal network after a number of evaluations and evolutions. For illustrative purposes, a hypothetical and a real WDN model are investigated, respectively. Numerical results indicate that the optimisation and design method developed in this paper provides a new perspective towards the rational balance between risk and investment.     

Multi-objective optimization of water distribution networks

Two multi-objective approaches to the consideration of pipe breakage data in water distribution network designs are formulated. Both models are based on the constraint method for multi-objective analysis. One model analyses the relationship between initial capital cost and subsequent repair and maintenance costs. Pipe breakage data is used to restrict the repair costs permitted in the system. The other model examines the relationships between initial pipe costs and the reliability of the pipes within the distribution network. In this second model, both the worst case and average system performance are examined in relation to the cost making model a three-objective approach. The pipe breakage data is used to restrict the expected number of failures allowed in any link. The actual number of expected breaks occurring in each link is then used to develop Poisson-based probabilities of node isolation. Application of the two approaches shows that the information obtained from such multi-objective approaches gives improved understanding into the nature of the issues behind initial cost and repair cost and initial cost and system reliability.     

Optimised design of energy efficient building façades via Evolutionary Neural Networks

Buildings are required to be more and more energy efficient, in order to comply with restrictive requirements of building regulations and energy certifications. Optimisation algorithms have shown to be effective in identifying good solutions for the design of efficient building services. In this article Evolutionary Neural Network Design (ENN-Design) has been adopted to drive the design of a typical façade module for an office building. This application is significant, since façades play a major role in the definition of the energy performance of buildings. Both single-objective and multi-objective optimisations have been carried out. The aim of the article is to introduce an innovative approach for improving the performance of building envelopes by means of a reasonable amount of calculation time.     

Shortest path criterion for sampling design of water distribution networks

Sampling design is often required for an appropriate assessment of monitoring points in water distribution networks to increase the effectiveness of measured data in calibrating the hydraulic model. Although many methods are available in the literature, they may be inadequate for reliable network calibration. This paper proposes a new method for the optimal collocation of monitoring points using a shortest path based approach. The monitoring points are identified by minimizing the sum of node distances from the closest sensor-node. Node distances were taken to be a weighted sum of the dimensionless arc length and the absolute head loss along arc. To ensure robustness with respect to the presence of outliers among pipe lengths and/or pressure drops, adequate reference measures were chosen for normalization. The optimization problem was solved using Mixed Integer Programming and a variant of the K-Means algorithm. Alternative formulations considering different path blending and distance norms were also analyzed. Numerical experiments carried out on both theoretical and real water distribution networks showed the reliability of the proposed approach and a greater effectiveness compared to similar methods available in the literature.     

Equity in water supply in intermittent water distribution networks

Equity in water supply is one of the major problems faced in intermittent water distribution systems. A new index ‘uniformity coefficient’ is introduced to measure the equity in distribution of water within the network, which may be useful for performance evaluation of water distribution networks (WDNs). An iterative head‐driven analysis technique is developed to compute the uniformity coefficient of a network. The effect of various design parameters of WDN on the uniform coefficient is studied. The results indicate that equity in water supply is significantly affected by the location of the tank and layout of the network. The equity in water supply can be improved in an existing network by staggered supply.     

Seismic functional reliability analysis of water distribution networks

Due to the huge destructive power of strong earthquakes, many breaks appear on water pipelines after such events. As a result, water leaks from these breaks, causing function loss of water distribution networks (WDNs). In order to evaluate the seismic performance of WDNs, these leaks cannot be ignored. In this paper, by adding a leakage model to the hydraulic equation of WDNs in a daily operation state, a new hydraulic equation is established to describe WDNs after the occurrence of earthquakes. As it is a stochastic equation, a random perturbation method is used to solve the equation and give the mean, standard deviation and skewness of the nodal head. In the meantime, a performance function is established to evaluate the reliability of WDNs. Three reliability analysis methods, a mean first-order second-moment method and two third-moment methods, are used to give the seismic functional reliability of WDNs. Meanwhile, two networks, a small WDN and an actual WDN which suffered serious damages during the Wenchuan Earthquake, 2008, are studied to compare the efficiency and precision of the three reliability methods.     

Energy use, CO2 emissions and waste throughout the life cycle of a sample of hotels in the Balearic Islands

Tourism is the most developed economic sector in the Balearic Islands. The great rise in construction activities within the last 50 years, the increase in energy use, in CO₂ emissions and in waste production due to tourism, as well as an electrical energy production system mainly based on coal and fossil fuels is not an environmentally sustainable scenario. The aim of this study is to identify the processes that have had the greatest impact on the life cycle of a tourist building. In order to do this, the energy uses, CO₂ emissions and waste materials generated have been estimated, assuming a life cycle of 50 years, within a sample of hotels from the Balearic Islands. The results show that the operating phase, which represents between 70% and 80% of the total energy use, is the one with the greatest impact; that the energy use due to the manufacture of materials represents a fifth of the total and that electric consumption is the main cause of CO₂ emissions because of the regional energy system.     

Shortening the search time in optimization of water distribution networks

Various optimization techniques have been implemented for minimizing the costs associated with water distribution networks (WDNs). In this regard, meta-heuristic algorithms have represented the highest efficiency. One of the weaknesses of these algorithms is their high computational costs, which make their implementation sometimes impracticable for optimization of large real life WDNs. In this article an optimization model based on the ant colony optimization algorithm is presented for least cost design of WDNs. In the proposed model, ants select pipe diameters so that the energy loss per unit length of pipes will be in a specific range. In this model, the number of objective function evaluations is small. Two sample networks have been optimized using the proposed model. Obtained results show that the model presented in this article has a very low search time, which makes its implementation possible for large real-life WDNs.     

Energy efficient design and occupant well-being: Case studies in the UK and India

The purpose of this paper is to demonstrate the relationships between sustainable building design and occupant well-being. It starts with a definition of sustainable design and well-being, and focuses on the relationships between energy performance and occupant feedback. Methodologically it draws on detailed monitoring and surveys of 12 case study office buildings in the UK and India, and the paper uses the data to explore whether energy use and associated CO₂ emissions are correlated to occupant satisfaction and comfort. The results demonstrate that increased energy use in the case study buildings is associated with increased mechanisation (e.g. centralised air conditioning) and reduced occupant control. This reduced control in turn is shown to relate to reduced occupant comfort and satisfaction. Finally, the paper reveals that the reported health conditions of occupants correlates strongly with their levels of satisfaction. The overall conclusion is that energy use in typical office buildings is inversely correlated with the well-being of the occupants: more energy use does not improve well-being.     

Reducing CO2 emission from exhaust gases using molten carbonate fuel cells: a new approach

The aim of this study is to couple molten carbonate fuel cell (MCFC) stack with integrated gasification combined cycle fed by refinery residues, to remove CO₂ from gas turbine exhaust gases that have CO₂ emission rate of 14,200 ton/year. By applying multi-objective optimisation (MOO) using genetic algorithm, the optimal values of operating load and the corresponding values of objective functions are obtained. The MOO of the MCFC system regarding two scenarios is performed. The first scenario is minimisation of cost of electricity (COE) and CO₂ emission rate. Objective functions of the second scenario are the same as in the first scenario while CO₂ tax is taken into account. Results show that the second scenario has 29.5% lower average optimal COE and 2.5% lower average emission rate in comparison with the first scenario. A sensitivity analysis is also performed to study the effect of fuel price and CO₂ tax variations on optimal solutions.     

A multi-objective approach for detecting and responding to accidental and intentional contamination events in water distribution systems

The protection against contamination events in water distribution systems involves two distinct phases: detection of the presence of a contaminant and implementation of actions to isolate and/or expel it rapidly. The problem of detection is confronted by installing a series of monitoring stations, strategically placed across the distribution system and consisting of sensors to detect the presence of contaminants. The actions to be implemented may include operations on distribution system devices (valves and hydrants) or injection of reagents to eliminate the contaminant, or simply alert users. The procedure proposed here attempts to address the problems related to the two phases by means of two consecutive optimisation processes, both of them performed off-line and assuming a specific 24-hour water demand sequence in each network node, whereas the accidental/intentional injection of contaminant can occur in any node and at any hour of the day. With reference to this vast range of possible injection scenarios, the first multi-objective optimisation process defines the position of a pre-selected number n_s of sensors across the distribution system in order to minimise the expected percentage of undetected contamination events and the expected volume of contaminated water consumed up to the beginning of the response operations following detection. A single configuration of stations is then selected from the Pareto front produced by this optimisation process (‘knee point’ of the Pareto front). At the end of this first optimisation process and with reference to the selected set of sensors, a potentially contaminated area in the network is associated to each sensor for each sub-period of the day. The second multi-objective optimisation process is then aimed to identify, with reference to each station and sub-period, and thus inside the corresponding potentially contaminated area, the hydrant-opening and valve-closing operations to be carried out in order to minimise both the number of operations and the expected volume of contaminated water consumed between the beginning of the response operations and the disappearance of the contaminant, assuming the availability of an unlimited number of response teams. Once these devices have been identified (‘knee point’ of the Pareto front relevant to the second optimisation process), an a posteriori analysis is performed to determine the sequence in which they should be activated based on the number of response teams actually available. In these optimisation processes, a hydraulic and quality simulator (EPANET) is linked to a multi-objective genetic algorithm (NSGA-II) in order to compute the value of the objective functions of the problem across different contamination scenarios. The results obtained applying the procedure to a real and complex water distribution system have shown it to be a robust and effective method for reducing the impact on the population.     

谱聚类在给水管网分区优化中的应用

利用图划分技术和图论算法实现给水管网分区。根据给水管网分析,确定分区数量,建立权重邻接矩阵并计算图拉普拉斯矩阵及其特征向量,通过多路图划分对隐藏在特征向量中的聚类信息进行数据挖掘,采用遗传算法和K均值方法实现最佳节点聚类。利用PageRank和最短路径算法确定水表和阀门位置,最终实现给水管网优化分区。实际给水管网模型分区实例表明所提方法在给水管网分区的有效性。     

Analysis of water distribution networks with head-dependent outlets

Conventional methods of analysis of a water distribution system impose specified quantities of demand at the nodes and compute the corresponding residual heads. In this study an almost fixed relationship between the residual head and the corresponding outflow is assumed in the analysis. Ignoring this relationship where it is essential may not display the true picture of network performance. Studies in this direction are of recent origin but are seen to impose an upper limit on the outflow beyond a certain level of residual head. In this study a methodology is proposed which takes into account the residual head versus outflow relationship having no clamping of the outflow. An efficient solution technique is employed for solving the governing equations. The appropriateness of the methodology is demonstrated with examples.     

Application of MINOS to water collection and distribution networks

This paper attempts to solve the problem of optimal design of both water collection and distribution networks, using a Modular In-core Nonlinear Optimization System (MINOS). Both models are user oriented, arrive at a discrete solution and can handle large systems efficiently. Pre- and post-processors are used to handle input and output data respectively. Network optimal design aspects such as transformation of variables, loop defining algorithms, reliability of redundant links, and the discretization problem are discussed. Four examples are solved to demonstrate the proposed model's capabilities.     

Current and future use of systems analysis in water distribution network design

Computer use in the design of water distribution networks was inititated through the use of network analysis techniques to determine system performance in terms of heads and flows. The last fifteen years, however, have seen the introduction of systems analysis optimization techniques to the range of computer models available for network design purposes. These optimization models differ markedly from the ‘traditional’ network analysis models in that they ‘design’ systems for specified loading conditions rather than just analysing the performance of predetermined systems under given loading conditions. Cost was the primary or only objective in almost all these early optimization models. Water distribution network design has, however, a number of other important objectives, such as maximizing reliability. Issues related to reliability concern include probability of component failure, probability of actual demands being greater than design values, and the system redundancy inherent within the layout of the network. The joint characteristics of these aspects of reliability are not well defined, and as a result no acceptable statement of overall distribution network reliability is yet available. The implications of these issues on each other and the design process as a whole are examined in detail. It is asserted that future work into the application of systems analysis techniques in general, and optimization models in particular, to the design of water distribution should be directed at the resolution of these issues. It is also claimed that the role of computer graphics in such models is not simply as a medium for displaying input parameters and output results such as head contours and flows in a clear graphical form. A more appropriate application of computer graphics is as a means for displaying parameters and characteristics of the reliability and redundancy such that the designer can ‘convert’ the available but inexact measures of these issues into practical statements of system performance.     

Forecasting future cooling demand in London

Cooling of buildings in the UK is responsible for around 15 TWh per year of energy demand, largely powered by electricity with highly related CO₂ emissions. The Greater London Authority wished to understand the potential impact of London's growing need for cooling on UK CO₂ emissions in the period up to 2030. This paper describes a model developed to analyse the cooling requirements for London's key building stock and assess how these would be affected by change in system mix, improvements in system efficiencies, and by varying degrees of climate change.The analysis showed that, if left unchecked, the growth in active cooling systems in London could lead to a doubling of CO₂ emissions from this source by 2030. This growth will be due to increase in building stock, increase in market share of cooling systems, and climate change. The last of these is difficult to predict, but by itself could add 260,000-360,000 tonnes of CO₂ emissions by 2030. This increase can be strongly mitigated, or even offset, by improvements in system efficiency. The difference between no efficiency improvements, and an assumed 1-3% annual efficiency improvement is around 340,000 tonnes by 2030.