Role of distributed storage in a 100% renewable UK network

This study considers generation and demand challenges in a 100% renewable UK electricity grid and poses the question whether this can be addressed through the use of distributed energy storage. To explore this issue, hourly demand and electricity generation profiles for a year have been constructed for a variety of renewable sources and demand scenarios. Alongside baseline projections, further scenarios have been produced that include extensive uptake of electric heat pumps for domestic heating and hot water, as well as moderate uptake of electric vehicles. It is proposed that these technologies are used on a local scale to help integrate the additional renewable electricity generated within a pre?determined zone of the electricity network. Analysishas been carried out to determine the pinch points in the UK network where renewable electricity generation is greater than local electricity demand. From this, consideration has been made to understand the real impact distributed energy storage in the form of heat pumps and electric vehicles can have in helping balance a 100% renewable UK electricity grid. Initial results have foundthat depending on the demand scenario and location on the network, there is the potential to accommodate up to 50% of the excess electricity generated

Low-cost wind resource assessment for small-scale turbine installations using site pre-screening and short-term wind measurements

A two-stage approach to low-cost wind resource assessment for small-scale wind installations has been investigated in terms of its ability to screen for non-viable sites and to provide accurate wind power predictions at promising locations. The approach was implemented as a case study at ten UK locations where domestic-scale turbines were previously installed. In stage one, sites were pre-screened using a boundary-layer scaling model to predict the mean wind power density, including estimated uncertainties, and these predictions were compared to a minimum viability criterion. Using this procedure, five of the seven non-viable sites were correctly identified without direct onsite wind measurements and none of the viable sites were excluded. In stage two, more detailed analysis was carried out using 3 months onsite wind measurements combined with measure-correlate-predict (MCP) approaches. Using this process, the remaining two non-viable sites were identified and the available wind power density at the three viable sites was accurately predicted. The effect of seasonal variability on the MCPpredicted wind resource was considered and the implications for financial projections were highlighted. The study provides a framework for low-cost wind resource assessment in cases where long-term onsite measurements may be too costly or impractical

Energy storage against interconnection as a balancing mechanism for a 100% renewable UK electricity grid

This study considers generation and demand challenges of a 100% renewable UK electricity grid and how this could be addressed with interconnection or energy storage. Hourly demand and electricity generation profiles for a year have been constructed: Business as Usual (BAU) with a yearly demand of 540 TWh and Green Plus (GP) with a demand of 390 TWh, Two further scenarios based on the above have been considered with electrification of heating (ASHP) and electric vehicle transportation (EV). The resultant hourly imbalances have been used to calculate the interconnection and energy storage requirements. This paper discusses the findings of the BAU scenario. The calculated interconnector capacity required was found to be 60 GW and cost £58 billion. Energy storage capacity requirements vary depending on the selected technology. Rated capacity was estimated to be 14 GW with storage capacity of 3 TWh for pumped storage, 11 GW and 2.3 TWh for liquid air, and 65 GW and 13.6 TWh for hydrogen storage, at a cost of £65, £76 and £45 billion respectively. This paper indicates that storing hydrogen in underground caverns would offer the cheapest solution. However, whilst these technological solutions can address generation and demand imbalance in a fully renewable electricity grid, there clearly remain barriers to each technology

Location, location, location: domestic small-scale wind field trial report

The Energy Saving Trust’s work in small-scale domestic wind dates back to 2005. A report compiled for the DTI1 concluded that ‘with the appropriate support, small wind could supply four per cent of the UK electricity requirement and reduce domestic CO2 emissions by six per cent’. Subsequently, our reports ‘Microwind Electricity Generation in the UK Residential Sector’ and ‘Generating the Future’, both completed in 2007, provided further predictions of the potential market for small wind turbines in the UK by 2050. These projections were based on modelled data and were produced before actual performance data from small-scale wind turbines was widely available. As such, it was difficult at the time to determine the accuracy of such future projections. Since these reports were published, the UK market for domestic small-scale wind has developed rapidly

Field study on thermal comfort in a UK primary school

This paper presents findings from a field survey in a naturally ventilated primary school building in Southampton, UK. The study included thermal comfort surveys and simultaneous measurements of indoor environmental variables. Approximately 230 pupils aged 7-11 in all 8 classrooms of the school were surveyed in repeated survey runs outside the heating season, from April to July 2011. In total 1314 responses were gathered. The survey involved questions on the thermal sensation and preference of the pupils. This paper investigates the children’s thermal sensation trends, their perception of overall comfort and tiredness. Furthermore, it compares the survey results to predictions achieved with current adult-based comfort standards, namely ISO 7730 and EN 15251. The results suggest that children have a different thermal perception than adults. Possible explanations are discussed in relation to the particularities and specific character of school environments

Do the constants used in adaptive comfort algorithms reflect the observed responses of children in junior school classrooms?

This paper compares the values used for the Griffiths constant (G=0.5) and the running mean constant (?=0.8) in adaptive comfort algorithms with the values calculated from thermal comfort field surveys in two naturally ventilated junior schools in Southampton, UK. The surveys were conducted outside the heating season in 2011 and 2012 respectively, including both questionnaire surveys and environmental monitoring. A total of 2693 pupil responses were used for this analysis. The data was examined in two steps: first, each survey set; obtained over a 1-day visit to the school; was examined in order to derive the relationship between indoor temperature change and comfort vote with minimum impact of adaptation. Second, the dataset was investigated for the prolonged periods of the surveys, in relation to weather experienced by the pupils in order to estimate their time for adaptation to outdoor temperature changes. The paper gives an insight into the response of pupils to internal and external temperature changes, immediate and over prolonged periods, in comparison to adults

Investigating the principal adaptive comfort relationships for young children

Thermal comfort surveys in school classrooms suggest that children have different thermal preferences to adults. This implies a need to revisit the current adult-based thermal comfort models. This paper investigates the principal adaptive comfort relationships that form the basis of adaptive comfort theory, using 2693 pupil thermal sensation responses and measured classroom temperatures from surveys in two naturally ventilated school buildings. The data were examined in two steps. Firstly, each survey set, obtained over one-day visits to the schools, was examined in order to derive the relationship between indoor temperature change and comfort vote with minimum impact of adaptation. Secondly, the data set was investigated over the entire survey period in relation to the weather experienced by the pupils in order to estimate their time for adaptation to outdoor temperature changes. The analysis shows that the basic adaptive comfort relationships are valid for children. However, a difference was found for the correlation coefficients of the comfort temperature to the outdoor running mean temperature between the schools, and a mismatch between their adaptive comfort equations. It is proposed that the difference in the consistency of the weather during the tests is the main reason for this discrepancy