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Research on corona discharge, shared by physics, chemistry and electrical engineering, has not arrested yet. As a dissipative process, the development of corona increases the resistive losses of transmission lines and enhances the line capacitance locally. Introducing additional losses and propagation delay, along the line, non-linearity and non-uniformity of the line parameters; therefore, corona should not be neglected. The present work is meant to provide the reader with comprehensive information on the corona macroscopic phenomenology and development, referring to the most relevant contributions in the literature on this subject. The models proposed in the literature for the simulation of the corona development are reviewed in detail, and sensitivity curves are provided to highlight their dependence on the input parameters.

The hygrothermal behaviour of an internally insulated historic wall is still hard to predict, mainly because the physical characteristics of the materials composing the historic wall are unknown. In this study, the hygrothermal assessment of an internally thermal insulated masonry wall of an historic palace located in Ferrara, in Italy, is shown. In situ non-destructive monitoring method is combined with a hygrothermal simulation tool, aiming to better analyse and discuss future refurbishment scenarios. In this context, the original U-value of the wall (not refurbished) is decreased from 1.44 W/m2K to 0.26 W/m2K (10 cm stone wool). Under the site specific conditions of this wall, not reached by the sun or rain, it was verified that even in the absence of vapour barrier, no frost damage is likely to occur and the condensation risk is very limited. Authors proposed further discussion based on simulation. The results showed that the introduction of a second gypsum board to the studied technology compensated such absence, while the reduction of the insulation material thickness provides a reduction of RH peaks in the interstitial area by 1%; this second solution proved to be more efficient, providing a 3% RH reduction and the avoidance of further thermal losses.

The global energy crisis has spurred increased investments in energy efficiency and clean energy initiatives; however, the results have fallen short of expected effectiveness. Concurrently, population growth and urbanisation drive a persistent surge in energy demands, especially within the residential sector, significant to overall building energy consumption. Current research focuses on residents’ responses to one-shot investments for energy efficiency or clean sources. The renovation wave, involving a massive number of existing buildings, calls for the mobilisation of huge investments that can be hard to afford in the short run. Sustainable behavioural change is complementarily rising as a key asset for maximising the overall estimated energy saving potential. Despite significant efforts to analyse household energy use and promote behavioural transformations, the literature remains gaping about future users, particularly the younger generation, as future leaders of sustainable development who exhibit a more responsible approach towards climate-related issues but also a strong dependency on digital-based solutions, which may influence energy use patterns and living habits, also impacting relations among peers and overall societal sustainability and energy efficiency. This article proposes a systematic literature review to analyse the variables affecting young people’s energy behaviour at home. The aim is to investigate the engines and gaps between strategies or tools for behaviour change and the expected effects, then find potential methods to address that barrier to identify a more promising approach, encouraging the younger generation to translate towards more sustainable energy behaviours.

Coal will continue to be the main energy source in China for the immediate future, although the environmental pollution and ecological impacts of each stage in the full life cycle of coal mining, transportation, and combustion generate large quantities of external costs. The Late Permian coals in southwestern (SW) China usually contain high amounts of fluorine (F), arsenic (As), and ash, which together with high-F clays cause abnormally high levels of endemic fluorosis, As poisoning, and lung cancer in areas where coal is mined and burned. In this paper, we estimate the external costs of the life cycle of coal. The results show that the externalities of coal in SW China are estimated at USD 73.5 billion or 284.3 USD/t, which would have accounted for 6.5 % of the provincial GDP in this area in 2018. The external cost of human health accounts for 87.2% of the total external costs, of which endemic skeletal fluorosis diseases and related lung cancers have the most important impact. Our study provides a more precise estimate of externalities compared with its counterparts in other provinces in China. Therefore, several policy recommendations would be proposed to internalize the external cost.

The rapid increase in the penetration of photovoltaic (PV) power plants results in an increased risk of grid failure, primarily due to the intermittent nature of the plant. To overcome this problem, the flexible power point tracking (FPPT) algorithm has been proposed in the literature over the maximum power point tracking (MPPT) algorithm. These algorithms regulate the PV power to a certain value instead of continuously monitoring the maximum power point (MPP). The proposed work carries out a detailed comparative study of various constant power generation (CPG) control strategies. The control strategies are categorized in terms of current-, voltage-, and power-based tracking capabilities. The comparative analysis of various reported CPG/FPPT techniques was carried out. This analysis was based on some key performance indices, such as the type of control strategy, irradiance pattern, variation in G, region of operation, speed of tracking, steady-state power oscillations, drift severity scenario, partial shading scenario, implementation complexity, stability, fast dynamic response, robustness, reactive power, cost, and tracking efficiency. Among existing FPPT algorithms, model-based control has a superior performance in terms of tracking speed and low steady-state power oscillations, with a maximum tracking efficiency of 98.57%.

Oscillating water column (OWC) devices, either fixed or floating, are the most common wave energy converter (WEC) devices. In this work, the fluid dynamic interaction between waves and a U-shaped OWC breakwater embedding a Wells turbine has been investigated through unsteady Computational Fluid Dynamic (CFD) simulations. The full-scale plant installed in the harbor of Civitavecchia (Italy) was numerically modeled. A two-dimensional domain was adopted to simulate the unsteady flow, both outside and inside the U-OWC device, including the air chamber and the oscillating flow inside the conduit hosting the Wells turbine. For the numerical simulation of the damping effect induced by the Wells turbine connected to the air chamber, a porous medium was placed in the computational domain, representing the conduit hosting the turbine. Several simulations were carried out considering periodic waves with different periods and amplitudes, getting a deep insight into the energy conversion process from wave to the turbine power output. For this purpose, the three main steps of the overall energy conversion process have been examined. Firstly, from the wave power to the power of the water oscillating flow inside the U-duct. Secondly, from the power of the oscillating water flow to the air pneumatic power. Finally, from the air pneumatic power to the Wells turbine power output. Results show that the U-OWC can capture up to 66% of the incoming wave power, in the case of a wave period close to the eigenperiod of the plant. However, only two-thirds of the captured energy flux is available to the turbine, being partially dissipated due to the losses in the U-duct and the air chamber. Finally, the overall time-average turbine power output is evaluated showing that it is strongly influenced by a suitable choice of the turbine characteristics (mainly geometry and rotational speed).

Mismatching operating conditions affect the energetic performance of PhotoVoltaic (PV) systems because they decrease their efficiency and reliability. The two different approaches used to overcome this problem are Distributed Maximum Power Point Tracking (DMPPT) architecture and reconfigurable PV array architecture. These techniques can be considered not only as alternatives but can be combined to reach better performance. To this aim, the present paper presents a new algorithm, based on the joint action of the DMPPT and reconfiguration approaches, applied to a reconfigurable Series-Parallel-Series architecture, which is suitable for domestic PV application. The core of the algorithm is a deterministic cluster analysis based on the shape of the current vs. voltage characteristic of a single PV module combined with its DC/DC converter to perform the DMPPT function. Experimental results are provided to validate the effectiveness of the proposed algorithm and to demonstrate evidence of its major advantages: robustness, simplicity of implementation and time-saving.

Reducing office buildings’ energy consumption can contribute significantly towards carbon reduction commitments since it represents ∼40% of total energy consumption. Major components of this are lighting, electrical equipment, heating, and central cooling systems. Solid evidence demonstrates that individual occupants’ behaviors impact these energy consumption components. In this work, we propose the methodology of using virtual choreographies to identify and prioritize behavior-change interventions for office users based on the potential impact of specific behaviors on energy consumption. We studied the energy-related office behaviors of individuals by combining three sources of data: direct observations, electricity meters, and computer logs. Data show that there are behaviors with significant consumption impact but with little potential for behavioral change, while other behaviors have substantial potential for lowering energy consumption via behavioral change.