Meeting the goal of zero emissions in the energy sector by 2050 requires accurate prediction of energy consumption, which is increasingly important. However, conventional bottom-up model-based heat demand forecasting methods are not suitable for large-scale, high-resolution, and fast forecasting due to their complexity and the difficulty in obtaining model parameters. This paper presents an artificial neural network (ANN) model to predict hourly heat demand on a national level, which replaces the traditional bottom-up model based on extensive building simulations and computation. The ANN model significantly reduces prediction time and complexity by reducing the number of model input types through feature selection, making the model more realistic by removing non-essential inputs. The improved model can be trained using fewer meteorological data types and insufficient data, while accurately forecasting the hourly heat demand throughout the year within an acceptable error range. The model provides a framework to obtain accurate heat demand predictions for large-scale areas, which can be used as a reference for stakeholders, especially policymakers, to make informed decisions.

The identification of transition field factor boundary between streamer initiation dominated breakdown and streamer propagation dominated breakdown is important for understanding the breakdown mechanisms of transformer liquids and for the transformer insulation design in practice. Most previous studies focused on either very divergent field or nearly uniform field. This paper reports on breakdown voltage tests with three transformer liquids in moderately-uniform fields. The results show that the transition field factor boundary between streamer initiation dominated breakdown and streamer propagation dominated breakdown under negative lightning impulse is liquid dependent. It is 9.6 for a mineral oil, 7.3 for a GTL oil, and 42.0 for a synthetic ester. The difference of the transition field factor boundary helps explain the observed breakdown voltage distinction among the three transformer liquids. In addition, the characteristics of negative streamers leading to breakdown were also investigated in the moderately-uniform fields. Streamer mode transitions with gap distance were observed and clarified, which is from 1 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> mode streamer to 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> mode streamer in both the mineral oil and GTL oil, while it is the 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> mode streamer to fast streamer in the synthetic ester.

A large set of undrained compression triaxial tests was carried out on different types of cohesionless soils, from sands to silty sands and silts. Shear wave velocity measurements were also carried out. These tests exhibit distinct state transitions ranging from flow liquefaction to strain softening or strain hardening. With the purpose of defining a framework to assess soil liquefaction, it was found that the ratio between the shear wave velocity (VS0) and the peak undrained deviatoric stress (qpeak), VS0/qpeak, could be accurately used to define a boundary between liquefaction and strain hardening for sands and between strain softening and strain hardening for silty sands and silts. Since this ratio is a function of the tested material, the prediction of these boundaries can be made as a function of soil grading, namely via the coefficient of uniformity, CU. Despite not being regarded as a strong geomechanical parameter, CU is easily determined from a grain-size distribution test and has an empirically proven correlation with critical state parameters.

Multiple hybrid energy storage systems (HESSs) consisting of batteries and super-capacitors (SCs) are widely used in DC microgrids to compensate for the power mismatch. According to their specific energy and power characteristics, batteries and SCs are used to compensate low-frequency and high-frequency power mismatches, respectively. This paper proposes a decentralized power allocation strategy for dynamically forming multiple HESSs aided with a novel power buffer. The power buffer is a device combing a capacitor and a bidirectional DC-DC converter, it is used as an interface between the batteries and DC bus, allowing easy Plug-and-Play of different energy storage units and effective and efficient power allocation. First, the power buffer and SCs split the power mismatch into a low-frequency and high-frequency part with a modified I-V droop control. Then the power buffer transfers the low-frequency mismatch to the batteries for compensation based on their respective state-of-charges (SoCs), while the high-frequency part is dealt by the SCs directly. This new scheme further allows elimination of the DC bus voltage deviations. Finally, the real-time hardware-in-loop (HIL) tests of three case studies confirm the effectiveness of the proposed control strategy.

The use of inverters-based resources (IBRs) is rising rapidly in power networks due to increased renewable energy penetration. This requires revisiting of classical network operation standards. For instance, high transformer energization inrush current has been studied extensively under the classical network paradigm. Whereas this paper investigates transformers' energization techniques in the context of inverters dominated grids, where inverters with limited short-circuit current are expected to utilize their grid-forming capabilities for black-start. Common transformer energization techniques such as controlled switching and soft energization are first analyzed with a new perspective aiming to assess their feasibility when used with grid-forming inverters and existing network assets. Parameters influencing soft energization voltage ramp-up time ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$T_{ramp}$</tex-math></inline-formula> ) are investigated, and a new <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$T_{ramp}$</tex-math></inline-formula> estimation framework for transformer energization from IBRs is introduced. Due to the variability of available point-on-wave circuit breakers (CBs) in distribution networks, controlled energization using single-pole and three-pole CBs is investigated for various configurations and their application limits are identified. A comprehensive case study is then presented using a test network with multiple transformers to benchmark the performance and requirements of each technique when the network is energized from an IBR, followed by a set of practical recommendations.

The penetration of converter connected generation is increasing globally, bringing with it valid concerns over the stability of the modern electricity network. In terms of frequency stability, the provision of inertia and frequency support from converter interfaced generation has been the topic of significant research with a wide range of systems considered. One resource that has avoided significant attention is the GB rail electrical rolling stock. Everyday thousands of trains run on a strict schedule, travelling at high speeds with considerable mass all acting as one large energy store. The AC connected trains possess regenerative braking systems allowing for this energy to be harvested. With simple software modifications this energy can be extracted during large frequency events. This article investigates the power available for inertia and frequency response throughout a working day. A sensitivity analysis of parameters is conducted and the work looks to the future by considering increasing penetration of AC trains. A response between 300 – 850 MW is estimated for a one-minute frequency response. The calculated energy and response profile was then used to investigate the effect that the trains would have had on the 9 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> of August power cut that occurred in the UK in 2019.

To enhance the adaptability of low voltage (LV) networks and release additional network capacity towards enabling the wider uptake of low carbon technologies, SP Energy Networks’ (SPEN) LV Engine project aims to design and trial the first UK solid state transformer (SST) for deployment within secondary substations (11/0.4kV). This project aims to form the first LV direct current (LVDC) trial at a utility scale in the UK. The SST and the introduction of low voltage DC (LVDC) supplies will present fundamental changes in the operation of existing secondary substations and will introduce new LV fault profiles for the associated LVDC distribution networks. This paper presents the results of joint work between the University of Strathclyde, SPEN and WSP with the primary objectives of identifying suitable DC protection and fault discrimination approaches for LVDC networks with multiple feeders and DC loads. This work intends to reflect the challenges and potential solutions for LVDC protection.