• Energy Research

Coupling the electricity and heat sectors is receiving interest as a potential source of flexibility to help absorb surplus renewable electricity. The flexibility afforded by power-to-heat systems in dwellings has yet to be quantified in terms of time, energy and costs, and especially in cases where homeowners are heterogeneous prosumers. Flexibility quantification whilst accounting for prosumer heterogeneity is non-trivial. Therefore in this work a novel two-step optimization framework is proposed to quantify the potential of prosumers to absorb surplus renewable electricity through the integration of air source heat pumps and thermal energy storage. The first step is formulated as a multi-period mixed integer linear programming problem to determine the optimal energy system, and the quantity of surplus electricity absorbed. The second step is formulated as a linear programming problem to determine the price a prosumer will accept for absorbing surplus electricity, and thus the number of active prosumers in the market. A case study of 445 prosumers is presented to illustrate the approach. Results show that the number of active prosumers is affected by the quantity of absorbed electricity, frequency of requests, the price offered by aggregators and how prosumers determine the acceptable value of flexibility provided. This study is a step towards reducing the need for renewable curtailment and increasing pricing transparency in relation to demand-side response.

At a time when the UK government has its sights on zero-carbon housing, in part achieved by tightly sealed envelopes and mechanical heat recovery ventilation (MHRV), the issue of indoor air quality (IAQ) and its implications for health has moved up the agenda; this in parallel with anxiety about the rising energy consumed by appliances, which is offsetting savings on space heating, water heating and lighting. In this context, this paper reports particular findings of a 2008-2011 EPSRC-funded research project: Environmental Assessment of Domestic Laundering, which relate to passive indoor drying (PID). To assess PID impacts, the study draws on monitored data from 22 case studies out of a wider survey of 100 dwellings in Glasgow, including laboratory analysis of air samples, and enhanced parametric dynamic moisture modelling. The evidence indicates that PID is a serious concern in terms of IAQ – firstly, apparent association of PID with high concentrations of mould spores, taking due account of confounding variables; secondly, moisture levels likely to boost dust mite populations; thirdly, potentially harmful chemicals in fabric conditioners, in particular PID linked to the concentration of acetaldehyde, a water-soluble volatile organic compound (VOC). The implication of PID for increased energy consumption is also addressed briefly, a broad-brush comparison being made with tumble-drying in this regard. A further moisture addition associated with domestic laundering is steam ironing, which, like PID, occurs in a context of other moisture sources and typically poor ventilation regimes (air too moist and CO2 too high). The paper concludes with outline recommendations for reformative building standards and design guidance, the aim to prevent PID moisture diffusion within habitable rooms by linking ‘quarantined’ drying spaces to dependable ventilation supply and exhaust systems

In 2003, the UK government announced its aspiration for a 60% reduction in CO2 emissions by 2050 relative to 1990 levels. To achieve this radical target, action is required across all sectors of the economy to reduce energy demand significantly and to increase the supply of energy from zero or low carbon sources. Focusing on the domestic sector, where energy consumption is currently rising, technologies such as fuel cells, Stirling and internal combustion engine micro-CHP and heat pumps are often cited as the means to reduce carbon emissions. However, there is much uncertainty as to the potential environmental benefits (if any) of the aforementioned technologies when set against a picture of changing energy supply and demand. The paper describes an analysis in which the performance of the four different technologies mentioned above was compared against a common datum of energy supply from condensing gas boilers and grid electricity for a number of scenarios. The aim of the analysis was to determine if significant CO2 savings could be made and to determine the minimum thermodynamic performance criteria that these technologies must attain if they are to yield any environmental benefits. The main finding of the work is that air source heat pumps yield significantly more CO2 savings than any of the other technologies examined.

Across Europe domestic electricity consumption is on the rise. In an attempt to counter this increase, various initiatives have been introduced to promote the replacement of less energy-efficient appliances with more efficient ones. Whilst the likely aggregate effect of such measures over long time periods have been modelled extensively, little is known about the affect that a change to higher efficiency appliances will have on the electrical demand profile of individual households at higher temporal resolutions. To address this issue a means by which established approaches to detailed electrical demand modelling can be adapted to simulate the improvements in the efficiency of appliances is elaborated in this paper. A process is developed by which low-resolution empirical appliance demand data can be transformed to produce high-resolution electrical demand data for different periods in the year, factoring in improvements in appliance performance. The process is applied to simulate the effects a changeover to more energy-efficient appliances would have on the minute resolution demand profiles of a group of households. Results indicate that improving the energy-efficiency of appliances in households leads to a significant reduction in electrical energy requirements but does not appear to have a significant affect on the peak electrical demand.

Simulated dataset underpinning journal paper "Developing a statistical electric vehicle charging model and its application in the performance assessment of a sustainable urban charging hub"

Technological advances in real-time data collection, data transfer and ever-increasing computational power are bringing simulation-assisted control and on-line fault detection and diagnosis (FDD) closer to reality than was imagined when building energy management systems (BEMSs) were introduced in the 1970s. This paper describes the development and testing of a prototype simulation-assisted controller, in which a detailed simulation program is embedded in real-time control decision making. Results from an experiment in a full-scale environmental test facility demonstrate the feasibility of predictive control using a physically-based thermal simulation program.

Photovoltaic (PV) cells, when integrated within a building facade, offer the possibility of generating electric power and heat for local use or export. This paper reports on a project to investigate the practical operational efficiencies that might be delivered from such facades. The results from laboratory experiments and computer simulations are presented: the former were used to develop an empirical relationship between cell temperature and power output; the latter were undertaken to assess operational efficiencies under a range of climate conditions representative of the UK.

This paper reviews the cooperating solver approach to building simulation as encapsulated within the ESP-r system. The application of the approach to the core technical domains underpinning building simulation is discussed along with its extension to the additional, diverse domains needed to support broader and/or more detailed analysis. The implications for computational overhead through expanding the repertoire of ESP-r are also considered. The paper concludes with an appraisal of the ability of the cooperating solver approach to cater for anticipated future application demands.