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A Comparison of Households’ Energy Balance in Residential Smart Grid Pilots in the Netherlands

doi: 10.3390/app9152993
This paper presents an analysis that frames the impact of various smart grid technologies, with an objective to provide a transparent framework for residential smart grid demonstration projects based on predefined and clearly formulated key performance indicators. The analysis inspects measured energy data of 217 households from three smart grid pilot projects in the Netherlands and a public dataset with smart meter data from 70 households as a reference. The datasets were evaluated for one year and compared to provide insights on technologies and other differences based on seven key performance indicators, giving a comprehensive overview: monthly electricity consumption (100–600 kWh) and production (4–200 kWh); annually imported (3.1–4.5 MWh) and exported (0.2–1 MWh) electricity; residual load; peak of imported (4.8–6.8 kW) and exported (0.3–2.2 kW) electricity; import simultaneity (20–70.5%); feed in simultaneity (75–89%); self-sufficiency (18–20%); and self-consumption (50–70%). It was found that the electrification of heating systems in buildings by using heat pumps leads to an increase of annual electricity consumption and peak loads of approximately 30% compared to the average Dutch households without heat pumps. Moreover, these peaks have a high degree of simultaneity. To increase both the self-sufficiency and self-consumption of households, further investigations will be required to optimize smart grid systems.
- Utrecht University Netherlands
- Eindhoven University of Technology Netherlands
- University of Twente Netherlands
Heat pumps, Technology, QH301-705.5, QC1-999, load duration curve, Consumption patterns, photovoltaic, Materials Science(all), heat pumps, smart grids, Biology (General), QD1-999, Instrumentation, energy system analysis, Engineering(all), self-sufficiency, Self-consumption, Fluid Flow and Transfer Processes, consumption patterns, Load duration curve, Self-sufficiency, T, Physics, Process Chemistry and Technology, Smart grids, Engineering (General). Civil engineering (General), Computer Science Applications, flexibility, Chemistry, Energy system analysis, TA1-2040, Flexibility, self-consumption, Photovoltaic
Heat pumps, Technology, QH301-705.5, QC1-999, load duration curve, Consumption patterns, photovoltaic, Materials Science(all), heat pumps, smart grids, Biology (General), QD1-999, Instrumentation, energy system analysis, Engineering(all), self-sufficiency, Self-consumption, Fluid Flow and Transfer Processes, consumption patterns, Load duration curve, Self-sufficiency, T, Physics, Process Chemistry and Technology, Smart grids, Engineering (General). Civil engineering (General), Computer Science Applications, flexibility, Chemistry, Energy system analysis, TA1-2040, Flexibility, self-consumption, Photovoltaic
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).13 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
