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The UK net‐zero target requires the integration of significant renewable energy resources into the electrical grid. This, together with the projected growth in electricity demand imposes practical challenges on the power transfer capability of existing transmission feeders. For environmental and planning reasons, construction of new overhead lines is problematic, and where possible upgrading of existing substations and lines is preferred. This paper investigates the feasibility of transforming an existing three‐phase (3Φ) double‐circuit 400 kV line into a six‐phase (6Φ) feeder for a simulated future GB scenario. Results indicate a 6Φ feeder, operating at a 'phase‐adjacent phase' voltage of 400 kV can effectively solve the constraints of boundaries in transmission networks. When considering the various operating contingencies, associated with an important UK network boundary and its expected near‐future winter‐peak power transfer requirements, the thermal overload issues are mitigated by transforming a feeder from 3Φ to 6Φ. The paper demonstrates upgrading to 6Φ technology is a potential solution to certain future boundary constraints and in these cases avoids the need to build new underground or overhead AC/DC lines. [ABSTRACT FROM AUTHOR]

The ongoing electrification of road transportation sector, which is expected to continue to strongly increase over the next years, will result in the connection of a significant number of electric vehicle (EV) chargers in LV and MV distribution networks, particularly in residential applications with on‐board ("slow") EV chargers. In order to evaluate loading limits of existing distribution networks for the maximum number of EV chargers that can be safely connected (commonly denoted as a network EV "hosting capacity", HC), this paper introduces a general approach to determine one commonly used network design parameter (after‐diversity maximum demand, ADMD) and one new parameter (maximum daily energy demand, MDED), which are both obtained from the load profiles of maximum per‐hour demands for uncontrolled residential EV charging. The presented approach uses actual EV charging data from the UK as the inputs in Monte Carlo simulations to generate daily EV charging profiles for arbitrary numbers of EVs, enabling to identify related ADMD, MDED and per‐hour maximum demand values, as well as their seasonal variations. The assessed ADMD, MDED and hourly maximum EV charging demands for uncontrolled EV charging are then combined with available UK residential daily load profiles before the EVs are connected ("pre‐EV demands"), where their combined coincidental and noncoincidental maximum demands are evaluated against the static thermal rating (STR) and dynamic thermal rating (DTR) loading limits of network components (transformers and overhead lines), taking into account relevant weather/ambient conditions. This is denoted as a network HC for uncontrolled EV charging. Finally, evaluating the resulting per‐hour maximum demand values against the STR and DTR loading limits and MDED values allows to select one particular scheduling method for controlled EV charging, which gives the absolute maximum number of EVs that can be safely connected in the considered network, that is, maximum network HC for fully controlled EV charging. The presented approach is illustrated on the example of the IEEE 33‐bus test network (modelled using typical UK network components), for the pre‐EV residential demands taken from the recordings at a UK MV substation, and for ambient data taken from a UK Met Office weather station. Obtained results allow to evaluate the range of network EV HC values for uncontrolled and controlled EV charging, that is, lower and upper HC limits, which can be correlated with the commonly used allocations of the firm and non‐firm network HC, respectively. [ABSTRACT FROM AUTHOR]