The water demand is increasing worldwide of around 1% per year since the 1980s, due to a combination of population growth, socio-economic development, and changing consumption patterns. The expectations foreseen an increase from 20% to 30% by 2050 over the current level. Considering the different water end-uses, the households consumptions account for 12% and the data show a growth of domestic water demand around 600% in the period 1960-2014. The climate change has worsened the situation. Indeed over 2 bln people in the world have lived water stress conditions, due to water scarcity or inadequate water infrastructure. In Italy, the water network is old: the 60% of the infrastructure has been installed more than 30 years ago. On average, the losses correspond to 43% of total water immitted, with peaks up to 70%. In addition, even if the water is less expensive than gas and electricity, it is the sector that registers highest shares of arrear customers and unauthorised consumption. The Internet of Things (IoT) has opened the opportunity of smart meters for utility. In this work, we have developed an analytical model to assess a cost-benefit analysis concerning both economic and environmental impacts of smart meters in Italy. It represents an innovative approach, though which are 7 benefits evaluated and quantified: remote meter reading, efficient maintenance (which includes identification and reduction of pipe leakages and faulty meters), demand management, arrear consumers control, fraud reduction and accurate billing. We have assumed a total meter park of 200’000 devices and supposed two cases for the simulation, distinguishing between ‘full costs’ and ‘delta costs’ for each one. ‘Full costs’ when the smart meters substitute working traditional meters, ‘delta costs’ when the new devices replace old meters that would be changed in any case in the near time. The two cases are rollouts of 10.000 and 50.000 meters. Each case has been declined in 6 scenarios, coming from the combination of 2 costs level (min, max) and 3 benefit level (min, avg, max). The results are evaluated considering 3 economic (NPV, IRR, PBT) and 3 environmental KPI’S (Absolute water saving, Relative water saving, Energy Efficiency) for each scenario. Finally, we have provided two curves (one for ‘full cost’, one for ‘delta costs’) that consider the NPV associated to several meters roll-out (from 10.000 to 200.000), to underline the presence of additional factors as economies of scale and smart water grid extended benefits.
La domanda di acqua sta aumentando in tutto il mondo di circa l'1% all'anno dagli anni '80, a causa di una combinazione tra la crescita della popolazione, sviluppo socioeconomico e mutevoli modelli di consumo. Si prevede un aumento dal 20% al 30% entro il 2050 rispetto al livello attuale. Considerando i diversi usi dell'acqua, i consumi domestici rappresentano il 12% (AQUASTAT, n.a.). I dati mostrano una crescita della domanda di acqua domestica intorno al 600% nel periodo 1960-2014 (World Research Institute, 2020). Il cambiamento climatico ha peggiorato la situazione. Infatti, oltre 2 miliardi di persone hanno vissuto condizioni di stress idrico. In Italia la rete idrica è vecchia: il 60% delle infrastrutture è stato installato più di 30 anni fa. Mediamente le perdite corrispondono al 43% sul totale d’acqua immessa con punte fino al 70%. Inoltre, anche se l'acqua è meno costosa del gas e dell'elettricità, registra una quota maggiore di clienti morosi. L'Internet of Things (IoT) ha aperto l'opportunità dei contatori intelligenti per le utilities. In questa tesi, abbiamo sviluppato un modello analitico per valutare un'analisi costi-benefici riguardante gli impatti sia economici che ambientali dei contatori intelligenti in Italia. Rappresenta un approccio innovativo, per il quale vengono valutati sette vantaggi: lettura dei contatori a distanza, manutenzione efficiente (suddivisa in diminuzione perdite e riduzione dei contatori difettosi), gestione della domanda, controllo dei clienti morosi, riduzione delle frodi e fatturazione su consumi effettivi. Abbiamo ipotizzato un parco contatori di 200.000 dispositivi e ipotizzato due casi, distinguendo tra "costi completi" e "costi differenziali" per ciascuno. "Costi completi" quando i contatori intelligenti sostituiscono i contatori tradizionali funzionanti, "costi differenziali" quando i nuovi dispositivi sostituiscono i contatori difettosi. I due casi sono rollouts di 10 e 50 mila. Ogni caso ha 6 scenari, derivanti dalla combinazione di 2 livelli di costo (minimo, massimo) e 3 livelli di beneficio (minimo, medio, massimo). I risultati sono 3 KPI economici (NPV, IRR, PBT) e 3 ambientali (Risparmio idrico assoluto, Risparmio idrico relativo, Efficienza energetica) per ogni scenario. Infine, abbiamo fornito due curve intermedie (una per "costo pieno", una per "costi delta") che considerano il NPV di rollout con diverse quantità di contatori per calcolare i vantaggi aggiuntivi (come gestione della pressione, economie di scala).
Smart water metering : analytical model computation for an estimated costs and benefits analysis
UGGERI, DAVIDE;SIMEON, EDOARDO
2019/2020
Abstract
The water demand is increasing worldwide of around 1% per year since the 1980s, due to a combination of population growth, socio-economic development, and changing consumption patterns. The expectations foreseen an increase from 20% to 30% by 2050 over the current level. Considering the different water end-uses, the households consumptions account for 12% and the data show a growth of domestic water demand around 600% in the period 1960-2014. The climate change has worsened the situation. Indeed over 2 bln people in the world have lived water stress conditions, due to water scarcity or inadequate water infrastructure. In Italy, the water network is old: the 60% of the infrastructure has been installed more than 30 years ago. On average, the losses correspond to 43% of total water immitted, with peaks up to 70%. In addition, even if the water is less expensive than gas and electricity, it is the sector that registers highest shares of arrear customers and unauthorised consumption. The Internet of Things (IoT) has opened the opportunity of smart meters for utility. In this work, we have developed an analytical model to assess a cost-benefit analysis concerning both economic and environmental impacts of smart meters in Italy. It represents an innovative approach, though which are 7 benefits evaluated and quantified: remote meter reading, efficient maintenance (which includes identification and reduction of pipe leakages and faulty meters), demand management, arrear consumers control, fraud reduction and accurate billing. We have assumed a total meter park of 200’000 devices and supposed two cases for the simulation, distinguishing between ‘full costs’ and ‘delta costs’ for each one. ‘Full costs’ when the smart meters substitute working traditional meters, ‘delta costs’ when the new devices replace old meters that would be changed in any case in the near time. The two cases are rollouts of 10.000 and 50.000 meters. Each case has been declined in 6 scenarios, coming from the combination of 2 costs level (min, max) and 3 benefit level (min, avg, max). The results are evaluated considering 3 economic (NPV, IRR, PBT) and 3 environmental KPI’S (Absolute water saving, Relative water saving, Energy Efficiency) for each scenario. Finally, we have provided two curves (one for ‘full cost’, one for ‘delta costs’) that consider the NPV associated to several meters roll-out (from 10.000 to 200.000), to underline the presence of additional factors as economies of scale and smart water grid extended benefits.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/171225