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The electric spring (ES) is a kind of electric device used for energy buffering, based on voltage and power management. ES transfers the voltage (or energy) fluctuation in the main bus to the non‐critical load (NCL), stabilises the main voltage for critical load, and actively adjusts the power consumption of the NCL to achieve regulation goals of distribution network with wide voltage operational range of NCL. With lots of intermittent and fluctuating renewable energy resources into the energy Internet, the smart load integrated with the ES will play a greater role in the optimal operation of the distribution network. Here, the power flow optimal model of distribution network with the ES is proposed. Under different load levels, the flexible regulation of ES can reduce the overall voltage drop and optimise the operation of distribution network. The benefits of ES for the optimisation of distribution network are verified based on an improved IEEE 33‐node case. Numerical results show that the ES relieves the voltage drop of the distribution network and improves the reliability of distribution network based on the interaction between the ES and NCL. The overall energy efficiency and reliability of the distribution network system are improved.

AbstractIn the study of urban development, it is very important to evaluate the influence of production factors reasonably and efficiently for the region to achieve efficient development. The principal aim of this investigation is to amalgamate the conventional measurement model characterized by robust interpretability with the non-parametric model characterized by limited interpretability, thereby enhancing the precision of research outcomes. Towards this objective, the study employs an optimized directional distance function integrated with a global Malmquist–Luenberger index to formulate a comprehensive total factor productivity measurement framework. In elucidating the homogeneous attributes of regions, departing from prior methodologies reliant on manual or direct algorithmic partitioning, this paper employs the K-means clustering algorithm for index discernment, abstracting the concept of K-means clustering centroids to encapsulate regional homogeneity, thereby delineating results through the visualization of regional development potential maps and the evolution of centroid-based clustering trend maps. The findings of the investigation illuminate common patterns of change across disparate regions, proposing a strategy for leveraging regional resource endowments towards a cohesive framework, thereby transcending constraints imposed by production efficiency limitations. Amidst the backdrop of the COVID-19 pandemic, this study draws upon provincial-level data spanning from 2000 to 2018 in China. The conclusive analytical outcomes underscore the pivotal role of energy factors in regional development efficiency, particularly within high-potential development regions, followed by the capital and labor factors. Concurrently, the study discerns a discernible hierarchical pattern among areas of development potential, which exhibits correlation with factor mobility dynamics.

The concept of virtual power plants (VPP) was introduced over 20 years ago but is still actively researched. The majority of research now focuses on analyzing case studies of such installations. In this article, the investigation is based on a VPP in Poland, which contains hydropower plants (HPP) and energy storage systems (ESS). For specific analysis, the power quality (PQ) issues were selected. The used data contain 26 weeks of multipoint, synchronic measurements of power quality levels in four related points. The investigation is concerned with the application of a global index to a single-point assessment as well as an area-related assessment approach. Moreover, the problem of flagged data is discussed. Finally, the assessment of VPP’s impact on PQ level is conducted.

AbstractIt is not known whether dietary guidelines proposing a limited intake of animal protein are compatible with the adoption of circular food systems. Using a resource-allocation model, we compared the effects of circularity on the supply of animal-source nutrients in Europe with the nutritional requirements of the EAT-Lancet reference diet. We found the two to be compatible in terms of total animal-source proteins but not specific animal-source foods; in particular, the EAT-Lancet guidelines recommend larger quantities of poultry meat over beef and pork, while a circular food system produces mainly milk, dairy-beef and pork. Compared with the EAT-Lancet reference diet, greenhouse gas emissions were reduced by up to 31% and arable land use reduced by up to 42%. Careful consideration of the feasible substitutability between animal-source foods is needed to define potential roles of animal products in circular human diets.

With the development of smart devices and information technology, it is possible for users to optimize their usage of electrical equipment through the home energy management system (HEMS). To solve the problems of daily optimal scheduling and emergency demand response (DR) in an uncertain environment, this paper provides an opportunity constraint programming model for the random variables contained in the constraint conditions. Considering the probability distribution of the random variables, a home energy management method for DR based on chance-constrained programming is proposed. Different confidence levels are set to reflect the influence mechanism of random variables on constraint conditions. An improved particle swarm optimization algorithm is used to solve the problem. Finally, the demand response characteristics in daily and emergency situations are analyzed by simulation examples, and the effectiveness of the method is verified.

Polymer extrusion is an energy intensive process whereby the simultaneous action of viscous shear and thermal conduction are used to convert solid polymer to a melt which can be formed into a shape. To optimise efficiency, a homogeneous melt is required with minimum consumption of process energy. In this work, in-process monitoring techniques have been used to characterise the thermal dynamics of the single screw extrusion process with real-time quantification of energy consumption. Thermocouple grid sensors were used to measure radial melt temperatures across the melt flow at the entrance to the extruder die. Moreover, an infrared sensor flush mounted at the end of the extruder barrel was used to measure non-invasive melt temperature profiles across the width of the screw channel in the metering section of the extruder screw. Both techniques were found to provide useful information concerning the thermal dynamics of the extrusion process; in particular this application of infrared thermometry could prove useful for industrial extrusion process monitoring applications. Extruder screw geometry and extrusion variables should ideally be tailored to suit the properties of individual polymers but in practise this is rarely achieved due the lack of understanding. Here, LDPE, LLDPE, three grades of HDPE, PS, PP and PET were extruded using three geometries of extruder screws at several set temperatures and screw rotation speeds. Extrusion data showed that polymer rheology had a significant effect on the thermal efficiency on the extrusion process. In particular, melt viscosity was found to have a significant effect on specific energy consumption and thermal homogeneity of the melt. Extruder screw geometry, set extrusion temperature and screw rotation speed were also found to have a direct effect on energy consumption and melt consistency. Single flighted extruder screws exhibited poorer temperature homogeneity and larger fluctuations than a barrier flighted screw with a spiral mixer. These results highlighted the importance of careful selection of processing conditions and extruder screw geometry on melt homogeneity and process efficiency. Extruder scale was found to have a significant influence on thermal characteristics due to changes in surface area of the screw, barrel and heaters which consequently affect the effectiveness of the melting process and extrusion process energy demand. In this thesis, the thermal and energy characteristics of two single screw extruders were compared to examine the effect of extruder scale and processing conditions on measured melt temperature and energy consumption. Extrusion thermal dynamics were shown to be highly dependent upon extruder scale whilst specific energy consumption compared more favourably, enabling prediction of a process window from lab to industrial scale within which energy efficiency can be optimised. Overall, this detailed experimental study has helped to improve understanding of the single screw extrusion process, in terms of thermal stability and energy consumption. It is hoped that the findings will allow those working in this field to make more informed decisions regarding set conditions, screw geometry and extruder scale, in order to improve the efficiency of the extrusion process. Engineering and Physical Sciences Research Council

The natatorium’s ventilation problem receives much concern because of its large wet load. The outdoor humidity ratio in transition season is the basic design parameter of the ventilation calculation, directly affecting the rationality of architectural design. At present, the ventilation-curve (V-C) method is the most widely used method to determine the outdoor humidity ratio in the transition season in China. However, due to failing to reflect non-guaranteed hours, the rationality of this value is difficult to assess by employing this approach. This paper presents a new method, the typical transition season method (TTS), for determining the outdoor humidity ratio in the transition season of a natatorium. The TTS method selects the transition season based on the typical meteorological year (TMY) data and calculates the outdoor humidity ratio with multiple non-guaranteed hours. This can well-represent the local perennial climate characteristics and clearly reflect the non-guaranteed hours. In this study, through selecting six typical representative cities in China, the evaluation of the outdoor humidity ratio is achieved through calculating ventilation volume and air change rate, verifying the rationality of this method. The results show that the humidity ratio obtained by the V-C method is lower than that obtained by the TTS method at about 2 g/kg without guarantee of 200 h humidity ratio, and even that the maximum difference is 6.64 g/kg. Meanwhile, the validation results of the ventilation calculation show that the humidity ratio determined by the V-C method cannot meet the minimum design requirements in five cities, while the humidity ratio obtained by the TTS method cannot meet the requirements in only one city.

Peer-to-peer (P2P) energy trading has attracted a lot of attention and the number of electric vehicles (EVs) has increased in the past couple of years. Toward sustainable mobility, EVs meet the standard development goals (SDGs) for attaining a sustainable future in the transport sector. This development and increasing number of EVs creates an opportunity for prosumers to trade electricity. Considering this opportunity, this review article aims to provide an in-depth analysis of P2P energy trading of EVs using blockchain in centralized and decentralized networks, which enables prosumers to exchange energy directly with one another. The paper is aimed to provide the reader with a state-of-the-art review on the P2P energy trading for EVs, considering different blockchain algorithms that are practically implemented or still in the research phase. Moreover, the paper presents blockchain applications, current trends, and future challenges of EVs’ energy trading. P2P energy trading for EVs using blockchain algorithms can be successfully implemented considering real-time scenarios and economically benefits smart sustainable societies.