The UK has some of the worst performing residential buildings in the EU from an energy efficiency perspective. Natural gas remains a dominant feature of existing and new-build housing with strong historical, technical, and social barriers to change. Consequently, the residential sector is responsible for significant shares of national emissions and has a strong role to play under ambitious net zero targets.To assess this role, this work combines long-term system-wide optimisation modelling with heat and electricity network models of representative residential locations. The scenario framework investigates key heating alternatives across futures with dwindling carbon budgets but lower restrictions on residential investment options. Comparing frameworks offers insights into "real life" applicability of technology solutions consistent with system-wide decarbonisation pathways to 2050.Residential sector heat plays an increasing role in lowering emissions as targets tighten. Moving away from natural gas becomes unavoidable and long-term trajectories combine end-use electrification, at household or collective levels, with supply-side decarbonisation. This is preferable to alternative gases that continue to carry uncertain emission impacts, but requires significant local network reinforcement. This could be deferred where technically difficult using near-term hybrid approaches. Enabling this transition will rely on policies that support open and varied technology portfolios.

The European Single Market aims to promote trade and competition in electricity generation across the EU, with investment signals for new generation capacity and interconnection coming from zonal electricity prices reflecting scarcity value. However, a growing number of EU Member States have implemented national Capacity Mechanisms in order to ensure future security of supply within their own borders, which may distort the cross-border trade of energy. This local view of energy security is in response to internal technical and economic constraints and a perceived inability of cross-border electricity flows to be a reliable source of capacity at times of maximum stress, in favour of self-sufficiency. A number of routes are available to resolve this conflict through permitting cross-border participation of generators in local Capacity Mechanisms, but this requires resolution of a number of complicating factors, not least a means for properly allocating transmission capacity without introducing further distortions to the energy market. Alternative solutions could be enacted at an EU-level, such as through the alignment of Capacity Mechanisms to a common model, or the introduction of an EU-wide single Capacity Mechanism, but the current regulatory focus appears to remain on resolution of such issues at a national level.

During high wind speed shutdown (HWSS) events, the power outputs of wind power plants may be subject to high ramp rates, causing issues for the System Operator (SO) in predicting total wind output, allocating adequate reserve levels and minimising balancing costs. As the timing of these events is difficult to predict, it is proposed that individual turbines may be used as probabilistic early warning indicators of HWSS events across sites, and by extension to a wide geographical area. The shut-down history of two separate wind farms across Scotland is analysed to determine the likelihood and impact of such events. It is shown that in most cases, HWSS does not result in the full loss of availability. Factors such as turbine elevation and mean wind exposure are key indicators of the order of shut-down across a site. The suggestion that sites could be used as early warning indicators for the pattern of HWSS across a transmission zone is difficult to characterise and for the two wind farms studied, prediction was not consistent

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In this paper we examine potential improvements in how load and generation forecast uncertainty is captured when setting reserve levels in power systems with significant renewable generation penetration and discuss the merit of proposed new methods in this area. One important difference between methods is whether reserves are defined based on the marginal distribution of forecast errors, as calculated from historic data, or whether the conditional distribution, specific to the time at which reserves are being scheduled, is used. This paper is a review of published current practice in markets which are at the leading edge of this problem, summarizing their experiences, and aligning it with academic modeling work. We conclude that the ultimate goal for all markets expected to manage high levels of renewable generation should be a reserve setting mechanism which utilizes the best understanding of meteorological uncertainties combined with traditional models of uncertainty arising from forced outages.

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Energy system models which cover multiple vectors have become increasingly used to provide an evidence base for policy and commercial decisions in real-world energy systems undergoing change. In particular, such models are often used to derive 'optimal' pathways to decarbonisation considering the planning or operation of systems with multiple technology options. This paper explores how the concept of 'usefulness'the applicability and relevance of modelling outcomesmay be used to establish criteria for modelling design and practice at the outset, and looks at the difficulties that may be faced in achieving this. The application should inform the choice of modelling framework and the manner in which tractability should be addressed and results meaningfully presented. A process of continuous engagement is proposed which guides modelling work towards 'useful' outcomes, as well as mitigating the danger of results being more reflective of design choices than the properties of the real-world systems being modelled. Because of the difficulties in maintaining and auditing complex datasets spanning expertise from multiple sectors, there is a clear role for independent data curators to facilitate rigour in model parameterisation and to allow consistency between modelling efforts. Specialists from the different disciplines represented should be engaged to ensure that data have been interpreted and applied correctly. All modelling choices should be clearly documented along with advice on their possible implications in respect of use of the results.

In the optimisation of maintenance and vessel strategies for the operation of offshore wind plant, it is normally assumed that the off-taker of the power produced may directly control the dispatch of maintenance resources. However, in practice, services such as maintenance technicians and vessels are usually contracted from companies with larger arenas of operation, and so the organisational interfaces between these parties, and the different objective functions involved, need to be considered. This article looks at different current and future models for contracted maintenance, identifies interfaces and conflicts of interest, and constructs a quantified model demonstrating the potential impact on headline energy yields for a set of wind farms with a common contracted maintenance resource. The modelling illustrates that the performance of a site with contracted maintenance operations is not only dependent on the contracts held by that site but also on the effective competition in place with other sites for a centralised resource, and the performance of a site may be highly sensitive to the alignment of contractual incentives, relative travel distances, and the relative size of the site in terms of energy yield