Nowadays the civil sector is focused on improving energy efficiency of the buildings, with the aim of obtaining residencies with extremely low energy consumption. We are still in a phase of experimentation of solutions widely studied at theoretical level regarding the application of techniques that modify the residential energy load. This thesis analyzes the experimentation in progress on an entire district if buildings in a neighborhood of Milan, through monitoring of residents using smart meters and smart plugs. Clustering techniques have been adopted to make residents segmentation into three groups based on energy consumption characteristics. Combining information of energy consumption and apartment type, most of one and two-room apartments have been clustered in “low” group and most of three and four-room into “medium” and “high”. Also, clustering of residents give the possibility to find who tend to be a virtuous consumer or who should lower their energy use to be more similar to their neighbors. Clustering results have been implemented in the simulation of a Renewable Energy Community (REC) in Merezzate. Here it was considered a single building made of 30 apartments that would share energy produced by a photovoltaic plant. Two scenarios are investigated, one with district heating and one where it is replaced with a heat pump. The introduction of the energy community brings a significant increase in the self-consumption of the PV plant already present, up to 76% in the case of district heating and 96% for the heat pump. The final part of the thesis consists of the feasibility analysis of demand side management strategies, making the hypothesis to “move” 20% of energy consumption from the high cost time slot to the low cost time slot. Both a first test with real PUN prices of peak hours and off-peak hours and a second Time of Use (ToU) scheme do not lead to significant benefits today given the small difference in cost of the time slots. The third DR strategy that has been tested is CPP, Critical Peak Pricing which brings savings in the order of 3% of the sole energy component of the electricity bill. The last DR mechanism that has been evaluated is IBP, incentive based pricing, where residents would receive a monetary compensation of 0,1 €/kWh for their active modification of energy consumption. Results of this case are the most promising, in the order of 6% of savings of energy cost.
Il settore civile è oggi incentrato sul miglioramento dell’efficienza energetica degli edifici, con lo scopo di ottenere residenze dal consumo energetico estremamente basso per combattere i cambiamenti climatici. Siamo ancora in una fase di sperimentazione di soluzioni ampiamente studiate a livello teorico per quanto riguarda l’applicazione di tecniche di modifica del carico energetico residenziale. Questa tesi analizza la sperimentazione in corso su un intero distretto di edifici di un quartiere di Milano, attraverso il monitoraggio dei residenti tramite smart meters e smart plugs. Sono state adottate tecniche di clustering per effettuare la segmentazione dei residenti in tre gruppi in base alle caratteristiche di consumo energetico. Combinando le informazioni sul consumo di energia e il tipo di appartamento, la maggior parte dei monolocali e bilocali sono stati raggruppati nel gruppo "basso" e la maggior parte dei trilocali e quadrilocali in "medio" e "alto". Inoltre, il clustering dei residenti dà la possibilità di trovare chi tende ad essere un consumatore virtuoso o chi dovrebbe abbassare il suo uso di energia per essere più simile ai suoi vicini. I risultati del clustering sono stati implementati nella simulazione di una Comunità Energetica a Merezzate. È stato considerato un unico edificio composto da 30 appartamenti che condividono l'energia prodotta da un impianto fotovoltaico. Sono stati studiati due scenari, uno con il teleriscaldamento e uno in cui questo viene sostituito da una pompa di calore. L'introduzione della comunità energetica porta un notevole aumento dell’autoconsumo del campo fotovoltaico già presente, fino al 76% nel caso di teleriscaldamento e 96% per la pompa di calore. La parte finale della tesi consiste nell'analisi di fattibilità delle strategie di demand side management, facendo l'ipotesi di "spostare" il 20% dei consumi energetici dalla fascia oraria ad alto costo a quella a basso costo. Sia un primo test con i prezzi reali delle ore di punta e delle ore non di punta, sia un secondo schema Time of Use (ToU) non portano oggi a vantaggi significativi data la piccola differenza di costo delle fasce orarie. La terza strategia DR che è stata testata è il CPP, Critical Peak Pricing che porta un risparmio nell'ordine del 3% della sola componente energetica della bolletta elettrica. L'ultimo meccanismo DR che è stato valutato è l'IBP, Incentive Based Pricing, dove i residenti riceverebbero una compensazione monetaria di 0,1 €/kWh per la loro modifica attiva del consumo energetico. I risultati di questo caso sono i più significativi, nell'ordine del 6% di risparmio del costo energetico.
Monitoring, data mining and demand side management strategies for a residential district in Milan
Perrucci, Nicola
2020/2021
Abstract
Nowadays the civil sector is focused on improving energy efficiency of the buildings, with the aim of obtaining residencies with extremely low energy consumption. We are still in a phase of experimentation of solutions widely studied at theoretical level regarding the application of techniques that modify the residential energy load. This thesis analyzes the experimentation in progress on an entire district if buildings in a neighborhood of Milan, through monitoring of residents using smart meters and smart plugs. Clustering techniques have been adopted to make residents segmentation into three groups based on energy consumption characteristics. Combining information of energy consumption and apartment type, most of one and two-room apartments have been clustered in “low” group and most of three and four-room into “medium” and “high”. Also, clustering of residents give the possibility to find who tend to be a virtuous consumer or who should lower their energy use to be more similar to their neighbors. Clustering results have been implemented in the simulation of a Renewable Energy Community (REC) in Merezzate. Here it was considered a single building made of 30 apartments that would share energy produced by a photovoltaic plant. Two scenarios are investigated, one with district heating and one where it is replaced with a heat pump. The introduction of the energy community brings a significant increase in the self-consumption of the PV plant already present, up to 76% in the case of district heating and 96% for the heat pump. The final part of the thesis consists of the feasibility analysis of demand side management strategies, making the hypothesis to “move” 20% of energy consumption from the high cost time slot to the low cost time slot. Both a first test with real PUN prices of peak hours and off-peak hours and a second Time of Use (ToU) scheme do not lead to significant benefits today given the small difference in cost of the time slots. The third DR strategy that has been tested is CPP, Critical Peak Pricing which brings savings in the order of 3% of the sole energy component of the electricity bill. The last DR mechanism that has been evaluated is IBP, incentive based pricing, where residents would receive a monetary compensation of 0,1 €/kWh for their active modification of energy consumption. Results of this case are the most promising, in the order of 6% of savings of energy cost.| File | Dimensione | Formato | |
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2021_12_Perrucci.pdf
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https://hdl.handle.net/10589/183653