Community energy storage business case – Final report

Executive Summary This study explores the potential for energy storage to contribute to the delivery of resilient, low carbon and cost effective community-scale energy systems in order to provide insights for a range of stakeholders, including project developers, investors, policy makers and community organisations. The work involves an integra ted analysis of a number of candidate community-scale energy business models comprising both electrical and thermal energy storage, and ~he roles of key stakeholders involved in financing, delivering and operating such projects. It also includes the results of techno-economic modelling carried out for a range of technical platforms comprising embedded energy generation technologies utilised together with electrical and thermal energy storage systems. The insights provided are intended to underpin decision making in policy development, investment planning and project delivery as part of the UK's journey towards a cost-effective low-carbon energy infrastructure. The aims of the work covered in this study were: • To identify stakeholders in the community energy storage sector, and consider stakeholder roles, benefi ts and barriers • To evaluate potential business models, usin,g relevant recent studies as well as stakeholder input • To assess storage and re lated technologies in the near, medium and long terms, and identify candidate energy storage platforms at both device and system levels through a system-of-systems approach • To examine relevant markets for energy storage, and assess potential value streams applicable to community-scale projects • To carry out a financial feasibility and risk analysis study for specific community-scale scenarios The key findings of the work are summarised below

The feasibility of renewable energy sources for pumping clean water in sub-saharan Africa: a case study for Central Nigeria

With less than 6 mm of rain from November through February every year, the central regions of Nigeria are in acute need of safe and consistent water supplies for drinking and other domestic or agricultural uses. Borehole supplies are capable of meeting a significant proportion of water needs, but ongoing fuel costs to power a generator and pump add a heavy burden to already disadvantaged communities. In this study, a techno-economic analysis is carried out in order to assess the feasibility of renewable energy sources and technologies to substitute for fossil-fuel powered pumping platforms. The results indicate that there is sufficient solar resource throughout these regions to facilitate relatively cost effective water pumping solutions, as well as a potentially effective wind resource depending on the exact location of the pumping station. Although systems based on these resources have high capital costs compared to petrol or diesel-based platforms, over a 20-year project life, the analysis indicates that ongoing fuel costs for a fossil-fuel-based system greatly outweigh the increased up-front costs of renewable alternatives. In conclusion, the results indicate that if the water demand at a particular site exceeds the capabilities of a hand pump, a renewable energy-powered pumping system is an attractive option, both economically and logistically in comparison to fossil-fuel-powered alternatives

Towards low carbon homes – a simulation analysis of building-integrated air-source heat pump systems

A comparative transient simulation analysis for domestic buildings with a floor-embedded heating system coupled to a modern air source heat-pump (ASHP) has been carried out using the TRNSYS numerical modeling environment for various UK locations. The effects of heat-pump control during off-peak electricity tariff periods in conjunction with varying building fabric characteristics were analysed and the results show that for the locations investigated, running costs and CO2 emissions were lower for the ASHP platform than for a comparative gas boiler heating system. It was also found that by utilizing the thermal mass of a concrete floor slab or by integrating external insulation, acceptable comfort levels during the heating season were maintained when operating the ASHP solely during off-peak tariff periods. A thinner concrete floor slab containing phase change material (PCM) provided a slightly improved comfort level during winter and also reduced overheating during summer in buildings with a high level of insulation. Finally, when utilising a floor-embedded PCM material, it was found that the thermal properties of the PCM material must be carefully matched with case-specific building fabric thermal performance parameters in order to ensure effective internal environmental control

A techno-economic analysis of small-scale, biomass-fuelled combined heat and power for community housing

This paper presents the results of a techno-economic study into the feasibility of a number of biomass-fuelled CHP (BCHP) systems when operated in a community housing/mixed use context. Six systems comprising differing technologies have been analysed, with the assumption that the systems operate within an ESCO (energy services company) supply scenario. Actual demand data was obtained for a representative community housing scheme, along with technical performance and cost data on the various biomass CHP systems. Subsequently, an economic modelling tool was developed and a number of operational scenarios were analysed to determine the viability of specific systems and the sensitivity of the results to a range of technical and economic parameters. The impact of thermal storage was also considered in order to optimise heat usage as far as possible. The results indicate that within specific realistic ESCO operating scenarios, biomass CHP can demonstrate positive net present values without the need for capital subsidies. Optimal system design and implementation is critical for profitable operation and it is found that the best economic performance occurs for high load factors when the maximum quantity of both electricity and heat sold on-site is maximised. The results are also found to be very sensitive to a number of the model inputs

The feasibility of biomass CHP as an energy and CO2 source for commercial glasshouses

A techno-economic modelling tool has been developed to examine the feasibility of biomass combined heat and power (CHP) technologies to provide the energy and CO2 demands of commercial horticultural glasshouses. Using the UK as a case study, energy and CO2 demands of candidate glasshouse installations on an hourly basis are established using both measured and benchmark datasets. Modelled electrical and thermal generation profiles for a number of commercially available small-scale biomass CHP systems of rated outputs of 0.1–5 MWe are also derived, and the results of their application within the modelling tool to carry out multi-parametric techno-economic analyses for various operational scenarios are presented. The impacts of both capital grant and generation tariff-based support mechanisms upon economic feasibility are investigated, along with that of variations in feedstock fuel prices. Net CO2 reductions accruing from the implementation of biomass CHP are also assessed. Finally, technical options, marginal costs and sale tariffs for CO2 recovery and supply are evaluated for specific scenarios. The results indicate that feasibility is very sensitive to the relationship between specific biomass CHP power:heat ratios and their match with glasshouse temporal electrical and thermal energy demand profiles, along with economic factors such as specific levels of capital and tariff-based support. With the utilisation of currently available financial support mechanisms, biomass CHP offers significant promise for realising economically viable significant CO2 emission reductions in this sector

Probabilistic analysis of solar photovoltaic self-consumption using Bayesian Network Models

In order to assess the systemic value and impacts of multiple PV systems in urban areas, detailed analysis of on-site electricity consumption and of solar PV yield at relatively high temporal resolution is required, together with an understanding of the impacts of stochastic variations in consumption and PV generation. In this study, measured and simulated time series data for consumption and PV generation at 5 and 1 minute resolution for a large number of domestic PV systems are analysed, and a statistical evaluation of self-consumption carried out. The results show a significant variability of annual PV self-consumption across the sample population, with typical median annual self-consumption of 31% and inter-quartile range of 22-44%. 10% of the dwellings exceed a self-consumption of 60% with 10% achieving 14% or less. The results have been used to construct a Bayesian Network model capable of probabilistically analysing self-consumption given consumption and PV generation. This model provides a basis for rapid detailed analysis of the techno-economic characteristics and socio-economic impacts of PV in a range of built environment contexts, from single building to district scales

Evaluating the contribution of PV to social, economic and environmental aspects of community renewable energy projects

For the purpose of the sustainability assessment of distributed renewable energy resources it is desirable to better understand the social, economic and environmental impacts (SEE) resulting from their deployment. Often only one, or at most two, of these knowledge domains is considered, partly due to the difficulty of devising an integrated assessment methodology. An approach based on probabilistic graphical models (PGM), has been developed which helps address this problem. Data for several UK urban census areas have been systematically collected and processed in order to furnish a PGM with the probabilistic data required in order to simultaneously make inferences about the SEE impacts of domestic solar PV, deployed to high penetrations. Results show that an integrated probabilistic assessment contributes to transdisciplinary knowledge, providing decision makers with a tool to facilitate deliberative and systematic evidence-based policy making incorporating diverse stakeholder perspectives

The feasibility of solar water-pumping in a rural village of Malawi

Though Malawi has achieved and exceeded the Millennium Development Goals (MDGs) water target, over half of the people in the rural areas collect water from boreholes or rivers. In spite of boreholes qualifying as improved water sources, studies show that the drinking water from these sources was contaminated and likely to cause disease. Other potable water problems include long distance to collect water and gender disparity in that the majority who collect water are women. As for hand-pumps, they are manually straining and most of them break and are not repaired sometimes even for minor faults; which makes the people resort to collect water from their previous contaminated water sources. Electric-powered pumps can play a significant role in the provision of potable water either by increasing the depth of well or by purifying water obtained from shallow wells or rivers. With no grid electricity in most of the rural areas, vulnerability to oil prices, depletion of fossil fuels, and high maintenance cost of diesel systems; Renewable Energy Technologies provide a viable option. A techno-economic feasibility study was carried out for a case study village: Nlukla Village, Chiradzulu District in Malawi. Results show that with the favourable sunlight conditions a solar water pumping system is a viable option for the area. The study is ongoing and future studies include working towards addressing the issue of high initial costs and how to make the system sustainable

Evaluating self-consumption for domestic solar PV: simulation using highly resolved generation and demand data for varying occupant archetypes

A detailed study of the on-site consumption of domestic solar PV generated electricity has been undertaken in order to gain an insight in to the relationships between annual consumption, generation and grid injection and to explore the effect of factors such as orientation and occupant behaviour on self-consumption (SC). Both empirical and simulated generation and export time series data for a large number of PV systems were analysed, and the degree to which SC is predicted by absolute generation and consumption and its variability have been quantified. SC is seen to be generally less than 50%, and the results illustrate the value of probabilistic models for predicting the socioeconomic impacts of domestic PV. As such, the results are significant for evaluating both socioeconomic impacts and distribution network loadflow implications

Probabilistic evaluation of UK domestic solar photovoltaic systems: An integrated geographical information system PV estimation tool

It is shown how key predictor parameters for the spatial estimation of PV yield, self -consumption and thereby economic and social indicators can be extracted from a GIS system and introduced into a Bayesian Network model. This model endogenises the uncertainties and incorporates spatial variability inherent in these parameters. Empirical monthly and annual yield measurements obtained from over 600 PV installations have been obtained and compared with estimated yields obtained by two key solar tools used for performance estimation in the UK – these are PVGIS and the UK Government’s Standard Assessment Procedure (SAP) for domestic buildings. Mean bias estimates and root mean square error estimations were obtained for each tool and the results used to construct an uncertainty distribution in PV yield prediction given key input parameters such as system rating, orientation and tilt. This uncertainty was used to furnish a probabilistic graphical model with a prior distribution for PV yield estimation. This was integrated into a Geographical Information (GIS) system furnished with roof and building stock parameters including roof attributes obtained from lidar data. Elements held in a vector layer of the GIS system can be selected and the resultant distributions of input parameters automatically fed to the model to yield a posterior distribution of the PV yield. The model is able to propagate the yield uncertainty to other probabilistic models, including ones which predict the internal rate of return and self -consumption. The latter is in turn predicted by empirical marginal distributions of domestic electricity consumption. Thus with a given posterior distributions of PV yield, new posterior distributions for the internal rate of return, self-consumption and carbon emission savings are automatically calculated. By integration with GIS this novel approach allows the spatial analysis of the uncertainty pertaining to representative risk factors for PV adoption in the UK, and facilitate the estimation by installers, investors, and local authorities in a manner which endogenises uncertainty