Optimal energy recovery by means of pumps as turbines (PATs) for improved WDS management

Abstract In water networks characterized by a significant variation in ground elevations the necessity of pumping water in some areas is complicated by a conflicting requirement to reduce excess pressures in other areas. This and the increasing cost of electricity has led to the use of Pumps-operating-As-Turbines (PATs) devices that can reduce pressure (and leakage) whilst harvesting energy. This paper presents a methodology for optimal water distribution system (WDS) management, driving the optimization by minimizing the surplus pressure at network nodes and the operational pumping costs and maximizing the income generated through energy recovery. The method is based on a highly parallelized Evolutionary Algorithm, employing an hydraulic solver to evaluate hydraulic constraints. Water demands at network nodes are considered as uncertain variables modelled by using a probabilistic approach in order to take into account unknown future demands. The approach is demonstrated in different case studies. Results obtained highlight that the economic benefits of installing PATs for energy recovery in conjunction with a combined pump-scheduling and pressure management regime is especially related to the input network characteristics. Further analysis of the importance of the probabilistic approach and of the influence of the interval time step adopted for the optimization has been evaluated

Battle of Postdisaster Response and Restoration

[EN] The paper presents the results of the Battle of Postdisaster Response and Restoration (BPDRR) presented in a special session at the first International water distribution systems analysis & computing and control in the water industry (WDSA/CCWI) Joint Conference, held in Kingston, Ontario, Canada, in July 2018. The BPDRR problem focused on how to respond and restore water service after the occurrence of five earthquake scenarios that cause structural damage in a water distribution system. Participants were required to propose a prioritization schedule to fix the damages of each scenario while following restrictions on visibility/nonvisibility of damages. Each team/approach was evaluated against six performance criteria: (1) time without supply for hospital/firefighting, (2) rapidity of recovery, (3) resilience loss, (4) average time of no user service, (5) number of users without service for eight consecutive hours, and (6) water loss. Three main types of approaches were identified from the submissions: (1) general-purpose metaheuristic algorithms, (2) greedy algorithms, and (3) ranking-based prioritizations. All three approaches showed potential to solve the challenge efficiently. The results of the participants showed that for this network, the impact of a large-diameter pipe failure on the network is more significant than several smaller pipes failures. The location of isolation valves and the size of hydraulic segments influenced the resilience of the system during emergencies. On average, the interruptions to water supply (hospitals and firefighting) varied considerably among solutions and emergency scenarios, highlighting the importance of private water storage for emergencies. 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G., … Ohar, Z. (2018). Battle of the Attack Detection Algorithms: Disclosing Cyber Attacks on Water Distribution Networks. Journal of Water Resources Planning and Management, 144(8), 04018048. doi:10.1061/(asce)wr.1943-5452.0000969Walski, T. M. (1993). Water distribution valve topology for reliability analysis. Reliability Engineering & System Safety, 42(1), 21-27. doi:10.1016/0951-8320(93)90051-yWang, Y., Au, S.-K., & Fu, Q. (2010). Seismic Risk Assessment and Mitigation of Water Supply Systems. Earthquake Spectra, 26(1), 257-274. doi:10.1193/1.3276900Yoo, D. G., Kang, D., & Kim, J. H. (2016). Optimal design of water supply networks for enhancing seismic reliability. Reliability Engineering & System Safety, 146, 79-88. doi:10.1016/j.ress.2015.10.001Zhang Q. F. Zheng K. Diao B. Ulanicki and Y. Huang. 2018. “Solving the battle of post-disaster response and restauration (BPDRR) problem with the aid of multi-phase optimization framework.” In Proc. 1st Int. WDSA/CCWI 2018 Joint Conf. 14. Kingston Canada: Open Journal Systems

Municipal climate adaptation plans: an assessment of the benefit of Nature-Based Solutions for urban local flooding mitigation

The proposed framework aims to evaluate the effectiveness of the NBS small-scale interventions on five densely urbanized sub-catchments located in the urban area of the Municipality of Potenza. Starting from the definition of the hydrological response of each basins the SCS curve number method was applied in different CN scenarios modeled through geospatial analysis. The results allowed to quantify the reduction in peak flood that reaches the ponding area due mainly to the part of precipitation retained temporarily at the ground surface as interception brought by more permeable soils in urban context

The Influence of Potential Flood Hazard Areas for Urban Adaptation to Climate Change

In the modern context of climatic uncertainty, the management of the resilient transformation process of the city emerges as a priority challenge for urban planning to develop a multidisciplinary and inter-scalar approach, transferring knowledge between sectors and encouraging the whole system thinking. In detail, the present work investigates the interferences between the potential flood hazard areas and the emergency planning of the municipality of Potenza. Critical nodes have been identified in the infrastructure network as essential features for coordinating rescue interventions to protect the population in a disaster. Indeed, the plan must be flexible in all emergencies, including unexpected ones. Therefore, a new perspective of risk management aims to reduce sources of risk and strengthen the ability to reduce the variability of performance, and complement the risk analysis with frameworks and practices that support system-wide resilience

Calibration Procedure for Water Distribution Systems: Comparison among Hydraulic Models

Proper hydraulic simulation models, which are fundamental to analyse a water distribution system, require a calibration procedure. This paper proposes a multi-objective procedure to calibrate water demands and pipe roughness distribution in the context of an ill-posed problem, where the number of measurements is smaller than the number of variables. The proposed methodology consists of a two-steps procedure based on a genetic algorithm. Firstly, several runs of the calibrator are performed and the corresponding pressure and flow-rates values are averaged to overcome the non-uniqueness of the solutions problem. Secondly, the final calibrated model is achieved using the calibrator with the average values of the previous step as the reference condition. Therefore, the procedure enables to obtain physically based hydraulic parameters. Moreover, several hydraulic models are investigated to assess their performance on this optimisation procedure. The considered models are based either on concentrated at nodes or distributed along pipes demands approach, but also either on demand driven or pressure driven approach. Results show the reliability of the final calibrated model in the context of the ill-posed problem. Moreover, it is observed the overall better performance of the pressure driven approach with distributed demand in scarce pressure condition

Stochastic Generation of District Heat Load

Modelling heat load is a crucial challenge for the proper management of heat production and distribution. Several studies have tackled this issue at building and urban levels, however, the current scale of interest is shifting to the district level due to the new paradigm of the smart system. This study presents a stochastic procedure to model district heat load with a different number of buildings aggregation. The proposed method is based on a superimposition approach by analysing the seasonal component using a linear regression model on the outdoor temperature and the intra-daily component through a bi-parametric distribution of different times of the day. Moreover, an empirical relationship, that estimates the demand variation given the average demand together with a user aggregation coefficient, is proposed. To assess the effectiveness of the proposed methodology, the study of a group of residential users connected to the district heating system of Bozen-Bolzano is carried out. In addition, an application on a three-day prevision shows the suitability of this approach. The final purpose is to provide a flexible tool for district heat load characterisation and prevision based on a sample of time series data and summary information about the buildings belonging to the analysed district