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This paper describes the analysis of an AD plant that is novel in that it is located in an urban environment, built on a micro-scale, fed on food and catering waste, and operates as a purposeful system. The plant was built in 2013 and continues to operate to date, processing urban food waste and generating biogas for use in a community café. The plant was monitored for a period of 319 days during 2014, during which the operational parameters, biological stability and energy requirements of the plant were assessed. The plant processed 4574 kg of food waste during this time, producing 1008 m 3 of biogas at average 60.6 % methane. The results showed that the plant was capable of stable operation despite large fluctuations in the rate and type of feed. Another innovative aspect of the plant was that it was equipped with a pre-digester tank and automated feeding, which reduced the effect of 2 feedstock variations on the digestion process. Towards the end of the testing period, a rise in the concentration of volatile fatty acids and ammonia was detected in the digestate, indicating biological instability, and this was successfully remedied by adding trace elements. The energy balance and coefficient of performance (COP) of the system were calculated, which concluded that the system used 49% less heat energy by being housed in a greenhouse, achieved a net positive energy balance and potential COP of 3.16 and 5.55 based on electrical and heat energy, respectively. Greenhouse gas emissions analysis concluded that the most important contribution of the plant to the mitigation of greenhouse gases was the avoidance of on-site fossil fuel use, followed by the diversion of food waste from landfill and that the plant could result in carbon reduction of 2.95 kg CO2eq kWh -1 electricity production or 0.741 kg CO2eq kg -1 waste treated. Highlights A micro-scale AD plant was built and operated reliably in London, UK  The system produced 0.596 m 3 CH4 kg -1 VS from locally-collected mixed organic waste  GHG reduction of the system was 0.741 kg CO2eq kg -1 waste treated cf. landfilling  The system advantageously included a pre-digestion tank to buffer the feed variations  Biological ammonia inhibition was mitigated by trace element supplementation

This work describes the design optimisation and techno-economic analysis of an offgrid Integrated Renewable Energy System (IRES) designed to meet the electrical demand of a rural village location in West Bengal -India with an overall electrical requirement equivalent to 22 MWh year -1 . The investigation involved the modelling of seven scenarios, each containing a different combination of electricity generation (anaerobic digestion with biogas combined heat and power (CHP) and photovoltaics) and storage elements (Vanadium redox batteries, water electrolyser and hydrogen storage with fuel cell). Microgrid modelling software HOMER was combined with additional modelling of anaerobic digestion, to scale each component in each scenario considering the systems' ability to give a good quality electricity supply to a rural community. The integrated system which contained all of the possible elements including except hydrogen production and storage presented the lowest capital ($US 71k) and energy cost ($US 0.289 kWh -1 ) compared to the scenarios with a single energy source. The biogas CHP was able to meet the electrical load peaks and variations and produced 61% of the total electricity in the optimised system, while the photovoltaics met the daytime load and allowed the charging of the battery which was subsequently used to meet base load at night. KeywordsIntegrated renewable energy system, micro-grid, photovoltaic, anaerobic digestion, hydrogen fuel cell, rural electrification.

This work proposes a novel and rigorous substrate characterisation methodology to be used with ADM1 to simulate the anaerobic digestion of solid organic waste. The proposed method uses data from both direct substrate analysis and the methane production from laboratory scale anaerobic digestion experiments and involves assessment of four substrate fractionation models. The models partition the organic matter into a mixture of particulate and soluble fractions with the decision on the most suitable model being made on quality of fit between experimental and simulated data and the uncertainty of the calibrated parameters. The method was tested using samples of domestic green and food waste and using experimental data from both short batch tests and longer semi-continuous trials. The results showed that in general an increased fractionation model complexity led to better fit but with increased uncertainty. When using batch test data the most suitable model for green waste included one particulate and one soluble fraction, whereas for food waste two particulate fractions were needed. With richer semi-continuous datasets, the parameter estimation resulted in less uncertainty therefore allowing the description of the substrate with a more complex model. The resulting substrate characterisations and fractionation models obtained from batch test data, for both waste samples, were used to validate the method using semi-continuous experimental data and showed good prediction of methane production, biogas composition, total and volatile solids, ammonia and alkalinity.

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