This study proposes a novel and replicable method to evaluate the cost-effectiveness of residential photovoltaic (PV) systems with battery storage (ESS) based on actual electricity consumption data from Italian households. The method integrates one year of real 15 min-interval household electricity consumption data, downloaded from the Italian national consumption portal (ARERA), with simulated PV generation and storage operation. Unlike most existing studies that rely on fully simulated demand profiles, this approach integrates real consumption data to more accurately capture daily and seasonal demand variability and the temporal mismatch with PV generation. The methodology has been validated through a case study of a residential dwelling in a Mediterranean area, with reversible heat pump loads and no existing PV or ESS, assuming the installation of a 3 kWp PV system and a 5.76 kWh ESS. Results show that adding ESS nearly doubles self-consumption (from 32.0% to 68.7%) and self-sufficiency (from 24.9% to 53.5%), while reducing grid imports by 38.0% and energy exports by 59.5%. Annual savings rise by 112%, but the payback period lengthens from 10.5 to 14.4 years, reflecting the trade-off between higher self-consumption and battery cost. Beyond these specific results, the main contribution of this work lies in demonstrating how publicly available real consumption data can be combined with energy simulation to support transparent and replicable evaluations of PV and ESS systems. Implemented through a calculation tool, this method can support designers, households, and policy-makers in assessing optimal ESS sizing, evaluating economic feasibility without the need for complex modelling or proprietary data. This methodology contributes to sustainability goals by reducing dependence on fossil fuels, improving the energy autonomy of buildings, and supporting decarbonization policies.
High-Resolution Analysis of Solar and Storage Integration in Residential Buildings with Reversible Heat Pumps
Calabrese N.
2025-01-01
Abstract
This study proposes a novel and replicable method to evaluate the cost-effectiveness of residential photovoltaic (PV) systems with battery storage (ESS) based on actual electricity consumption data from Italian households. The method integrates one year of real 15 min-interval household electricity consumption data, downloaded from the Italian national consumption portal (ARERA), with simulated PV generation and storage operation. Unlike most existing studies that rely on fully simulated demand profiles, this approach integrates real consumption data to more accurately capture daily and seasonal demand variability and the temporal mismatch with PV generation. The methodology has been validated through a case study of a residential dwelling in a Mediterranean area, with reversible heat pump loads and no existing PV or ESS, assuming the installation of a 3 kWp PV system and a 5.76 kWh ESS. Results show that adding ESS nearly doubles self-consumption (from 32.0% to 68.7%) and self-sufficiency (from 24.9% to 53.5%), while reducing grid imports by 38.0% and energy exports by 59.5%. Annual savings rise by 112%, but the payback period lengthens from 10.5 to 14.4 years, reflecting the trade-off between higher self-consumption and battery cost. Beyond these specific results, the main contribution of this work lies in demonstrating how publicly available real consumption data can be combined with energy simulation to support transparent and replicable evaluations of PV and ESS systems. Implemented through a calculation tool, this method can support designers, households, and policy-makers in assessing optimal ESS sizing, evaluating economic feasibility without the need for complex modelling or proprietary data. This methodology contributes to sustainability goals by reducing dependence on fossil fuels, improving the energy autonomy of buildings, and supporting decarbonization policies.| File | Dimensione | Formato | |
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