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Optimising renewable energy integration in new housing developments with low carbon technologies

Abstract Since buildings account for more than one-third of final energy use, it is important to integrate renewable energy sources for new housing developments to reduce demand for grid energy and carbon emissions. This research investigates the potential of solar PV, energy storage, and electric vehicles in new housing developments and their associated grid impacts by taking the UK’s Cambridge, Milton Keynes, Oxford arc as a case study. Using published data on electrical loads for different types of dwellings, energy demands for new housing developments with and without renewable and low carbon technologies are analysed using techno-economic modelling frameworks. Technical analysis includes sizing and optimisation of PV and storage while economic analysis covers cost-benefit analyses, by considering a range of existing and future tariffs and subsidy schemes including Standard, Economy 7 (cheaper electricity for 7 h at night), Feed-in tariff, and the Smart Export Guarantee. Results show that installing PV panels and storage systems not only reduces the dwellings’ grid energy demand by 31% in January but also helps the dwellings to become net exporters of green electricity to the grid in July and hence saves a substantial amount of money by taking advantage of Feed-in and Economy 7 tariffs.
- Cranfield University United Kingdom
- Cranfield University United Kingdom
- University College London United Kingdom
690, New housing developments, Grid impacts, Solar PV, Electric vehicles (EVs), Renewable energy sources (RES), Battery storage
690, New housing developments, Grid impacts, Solar PV, Electric vehicles (EVs), Renewable energy sources (RES), Battery storage
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).36 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 1%
