Modelling And Developing A Neighbourhood Low Carbon System For Five Dwellings In The U.K.

Abstract

This paper presents a case study of a neighbourhood low carbon energy system designed for five off-gas rural dwellings in the UK. The employment of the neighbourhood system aims to improve energy efficiency of the whole site, reduce dependency on heating oil or LPG for off-gas houses, maximize renewable energy usage on site, and minimize fuel poverty through affordable investments. System design is discussed and built on site survey, ongoing monitoring and validated modelling. Simulation is carried out in dynamic model HTB2. A ROI analysis is used to examine the long-term cost-effectiveness, taking into account any maintenance and replacement cost, degradation of system performance and discounting of money over time. The neighbourhood system scenario is compared with an alternative scenario of separate systems for individual houses, in terms of energy reduction, energy self-sufficiency, CO2 reduction and pay-back time. The simulation results indicate the designed optimal neighbourhood system can achieve similar self-sufficiency as that of a separate system scenario, with more than 70% of its electricity demand met by onsite electricity production. Both the neighbourhood system approach and the separate one can achieve carbon negative for the whole site, with the former contributing to 31% more carbon reduction than the latter. The neighbourhood system can be paid back within its lifespan, while the separate system approach can't. The payback time of the neighbourhood system can be reduced to 14 years if traditional bolt on PV system is used instead of building integrated PV. The outcome of the research demonstrated the affordability and replicability of the neighbourhood low carbon energy system, which can decrease fuel poverty, and meet government targets for CO2 reduction.

Exploring the potential of scaling up Smart Local Energy Systems to transform clusters of housing: Insights from a case study in Wales, UK

“…Li et al [5] compared household and cluster scale SLES. Their modelling study showed that the scaled-up system caused a decrease in CO2 emissions and shortening of return on investment; however, the self-sufficiency of the system decreased, and an average annual energy bill increased [5]. Solar power, applied by Li et al [5] and wind power are both practical options for RES at a cluster scale SLES [8].…”

“…Their modelling study showed that the scaled-up system caused a decrease in CO2 emissions and shortening of return on investment; however, the self-sufficiency of the system decreased, and an average annual energy bill increased [5]. Solar power, applied by Li et al [5] and wind power are both practical options for RES at a cluster scale SLES [8]. The installation of wind turbines (WT) typically occurs in rural, coastal, and offshore areas due to power production capabilities [9].…”

“…Wind turbines can generate large amounts of electricity [9], which can increase the income from exported surplus electricity and increase self-sufficiency of the system. This research aims to compare the feasibility of wind and solar powered SLES in a rural context, examining if changing the source of renewable electricity can benefit the system analysed by Li et al [5].…”

“…At the time of conducting this research, there are no universally accepted standards for assessing the performance of SLES [10]. The KPIs chosen to assess the modelled scenarios (Table 2) are supported by literature [5,10]. They are set to form a framework focusing on the technical aspects and feasibility of the system at a cluster scale, assessing technical, environmental and economic domains.…”

“…The heating is set to be on from 1 st October to 1 st April. To validate the energy use resulting from occupancy profiles shown in Table 4, annual consumption figures have been compared to UK average values and data from Li et al [5]. Pre-retrofit, House E relied on electricity for heating and DHW, resulting in much higher electricity use than other houses (Table 4).…”