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Urban building energy modelling (UBEM) plays an essential role in the global climate action plans by analyzing the energy supply at urban or city scales and estimating the energy demand and the gas emission of different sectors. Moreover, policies and measures such as clean grid strategies, demand response programs, and dynamic pricing policies, that have been put in place as part of these plans rely heavily on the results of UBEM models to represent more realistic energy use and environmental impact at different temporal and spatial scales. However, the unsolved performance gap issue (i.e. discrepancy between the model predicted results and the actual performance) stands in the way of the effectiveness and the reliability of the developed models. One of the most acknowledged reasons behind such an issue is the uncertainty in modelling occupants' behaviours (OB) in this context. Therefore, many research efforts focused on investigating different modelling approaches to improve the level of details of occupant-related features in UBEM models. However, the capability of the developed models to be integrated into the currently available UBEM tools is still questionable. This caused many practitioners and UBEM users to rely on simple fixed schedules instead of examining stochastic models with a higher level of detail when needed. To this end, this paper aims to review the currently available OB models and compare them with respect to inputs, used algorithms, their expected outputs, as well as their integration capability into the commonly used UBEM tools. The results of this investigation can be used to develop guidelines for modelling OB aspects for the different applications of urban building energy simulation, as well as identify areas of improvement in the commonly used UBEM tools. [ABSTRACT FROM AUTHOR]

In 2019, the UK became the first major economy to pass laws to reduce its greenhouse gas emissions to net zero by 2050. Meeting this ambitious target not only requires a shift in energy supply from fossil fuels to low carbon energy sources, but also a reduction in energy demand through the roll-out of energy efficiency improvements to existing buildings. The UK has some of the oldest and most inefficient housing stock in Western Europe and the building sector is responsible for approximately half of energy consumption. The present work has a strong focus on exploring low carbon heat supply tehcnologies could be applied to existing housing stock, using the London Borough of Islington (LBI) as a case study. The applicability of low carbon energy efficiency measures to a range of different building archetype prominent within LBI is discussed and evaluated. The methodology implemented includes both qualitative and quantitative assessment of the opportunities and benefits, with a focus on applicability, cost, and carbon savings associated with two low carbon heat supply options. The overall evaluation approach presented in the paper is applicable to other urban areas in the UK and elsewhere. Key conclusion from the study and planned next steps are also discussed. [ABSTRACT FROM AUTHOR]

The climate crisis currently being faced by humanity is going to increase extreme weather events which are likely to make long-duration power outages for communities increase in frequency and duration. Microgrids are an important part of electrical resilience for connected communities during power outages. They also can have transactive potential to save energy on electric loads through coordinating distributed energy resources. Microgrids are expensive though. Making electric load coverage available nearly 100% of the time given known design basis threats and component failure statistics is one of the largest drivers of cost. Such high availability is non-negotiable for critical applications such as life saving equipment in a hospital but could perhaps be compromised for less critical loads. This paper documents an analysis that used the Microgrid Design Toolkit and EnergyPlus simulation results with two energy retrofit options exercised. The results show how increasing energy efficiency and reducing availability to 90% and 80% reduced the calculated price of a photovoltaic and battery storage microgrid in a New Mexico neighborhood by 63% and 70%, respectively. A microgrid with 80% availability with 48-hour islanded run-time capability is therefore suggested as a low-cost method for accelerating microgrid infrastructure penetration into the residential sector. Such an "underbuilt" microgrid will significantly increase resilience even though it will not guarantee energy security for the non-critical applications in residential households. This will in turn accelerate the growth of storage potential across communities providing greater grid flexibility. The results of the study also show how increased insulation applied to the proposed residential community can be less expensive than creating a larger microgrid that carries larger electric loads. The likelihood that energy retrofits are a better investment than a larger microgrid is inversely proportional to availability. Here, availability is a metric equal to the percentage of the demand load served by the microgrid during power outages, not including the startup period. [ABSTRACT FROM AUTHOR]