Identification of transformer overload and new energy planning for enterprises based on load forecasting.

The new energy system constructed by energy storage and photovoltaic power generation system can effectively solve the problem of transformer overload operation in some enterprises. It can not only reduce the cost of electricity, but also realize low-carbon emission reduction. However, due to its low return on investment, the willingness of enterprises to install new energy is not high. In this paper, we first establish a load forecasting model to users whose transformers are overloaded or about to be overloaded, which are potential customers with new energy installation needs. Then, Optimal configuration models of PV and energy storage systems based on nonlinear programming are developed for these potential customers. The optimal installed capacity of the PV energy storage and the optimal charging and discharging strategy for the energy storage system can be obtained. This optimization strategy ensures that the electricity consumption of the enterprise does not exceed the rated capacity, and effectively reduces the enterprise's basic tariff and electricity price to achieve cost reduction and efficiency. Finally, taking a building materials production factory as an example, we obtain the optimal plan for the new energy capacity, as well as the economic benefits of the plan and the specific strategy of energy storage charging and discharging for this factory.

Optimizing microgrid performance: Strategic integration of electric vehicle charging with renewable energy and storage systems for total operation cost and emissions minimization.

At present, renewable energy sources (RESs) and electric vehicles (EVs) are presented as viable solutions to reduce operation costs and lessen the negative environmental effects of microgrids (µGs). Thus, the rising demand for EV charging and storage systems coupled with the growing penetration of various RESs has generated new obstacles to the efficient operation and administration of these µGs. In this regard, this paper introduces a multi-objective optimization model for minimizing the total operation cost of the µG and its emissions, considering the effect of battery storage system (BSS) and EV charging station load. A day-ahead scheduling model is proposed for optimal energy management (EM) of the µG investigated, which comprises photovoltaics (PVs), fuel cells (FCs), wind turbines (WTs), BSSs, and EV charging stations, with shed light on the viability and benefits of connecting BSS with EV charging stations in the µG. Analyzing three case studies depending on the objective function-Case 1: execute EM to minimize total operation cost and maximize the profits of BSS, Case 2: execute EM to minimize total emission from the µG, and Case 3: execute EM to minimize total operation cost, maximize the profits of BSS, and minimize total emissions from the µG. The main aim of the presented optimization strategy is to achieve the best possible balance between reducing expenses and lessening the environmental impact of greenhouse gas emissions. The krill herd algorithm (KHA) is used to find the optimal solutions while considering various nonlinear constraints. To demonstrate the validity and effectiveness of the proposed solution, the study utilizes the KHA and compares the obtained results with those achieved by other optimization methods. It was demonstrated that such integration significantly enhances the µG's operational efficiency, reduces operating costs, and minimizes environmental impact. The findings underscore the viability of combining EV charging infrastructure with renewable energy to meet the increasing energy demand sustainably. The novelty of this work lies in its multi-objective optimization approach, the integration of EV charging and BSS in µGs, the comparison with other optimization methods, and the emphasis on sustainability and addressing energy demand through the utilization of renewable energy and EVs.

What drives the relationship between digitalization and energy demand? Exploring heterogeneity in German manufacturing firms.

The growing use of information and communication technologies (ICT) has the potential to increase productivity and improve energy efficiency. However, digital technologies also consume energy, resulting in a complex relationship between digitalization and energy demand and an uncertain net effect. To steer digital transformation towards sustainability, it is crucial to understand the conditions under which digital technologies increase or decrease firm-level energy consumption. This study examines the drivers of this relationship, focusing on German manufacturing firms and leveraging comprehensive administrative panel data from 2009 to 2017, analyzed using the Generalized Random Forest algorithm. Our results reveal that the relationship between digitalization and energy use at the firm level is heterogeneous. However, we find that digitalization more frequently increases energy use, mainly driven by a rise in electricity consumption. This increase is lower in energy-intensive industries and higher in markets with low competition. Smaller firms in structurally weak regions show higher energy consumption growth than larger firms in economically stronger regions. Our study contributes to the literature by using a non-parametric method to identify specific firm-level and external characteristics that influence the impact of digital technologies on energy demand, highlighting the need for carefully designed digitalization policies to achieve climate goals.

Understanding Osaka mutation polymorphic Aß fibril response to static and oscillating electric fields: insights from computational modeling.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder, impacting millions of individuals worldwide. Among its defining characteristics is the accumulation of senile plaques within the brain's gray matter, formed through the self-assembly of misfolded proteins contributing to the progressive symptoms of AD. This study investigates a polymorphic Aß fibril under static and oscillating electric fields using molecular dynamics simulation. Specifically, we utilized a polymorphic fibrillar complex composed of two intertwined pentamer-strands of the Aß1-40 peptide with the Osaka mutation (E22Δ), known for its toxicity and stable structure. Our findings demonstrate that a 0.3 and 0.4 V/nm electric field combined with a 0.20 GHz frequency effectively disrupts the polymorphic conformation of Aß fibrils. Furthermore, we elucidate the molecular mechanisms underlying this disruption, providing insights into the potential therapeutic use of oscillating electric fields for AD. This research offers valuable insights into novel therapeutic approaches for combating AD pathology.

Carbon Fiber-Mediated Electrospinning Scaffolds Can Conduct Electricity for Repairing Defective Tendon.

Partial or complete rupture of the tendon can damage the collagen structure, resulting in the disruption of the electrical signal pathway. It is a great challenge to reconstruct the original electrical signal pathway of the tendon and promote the regeneration and functional recovery of defective tendon. In this study, carbon fiber-mediated electrospinning scaffolds were fabricated by wrapping conductive, high-strength, loose single-bundle carbon fibers with nanofiber membranes. Due to the presence of nanofiber membranes, the maximum tensile force of the scaffolds was 2.4 times higher than that of carbon fibers, while providing excellent temporal and spatial prerequisites for tenocytes to adapt to electrical stimulation to accelerate proliferation and expression. The diameter of the carbon fiber monofilaments used in this study was 5.07 ± 1.20 µm, which matched the diameter of tendon collagen, allowing for quickly establishing the connection between the tendon tissue and the scaffold, and better promoting the recovery of the electrical signal pathway. In a rabbit Achilles tendon defect repair model, the carbon fiber-mediated electrospinning scaffold was almost filled with collagen fibers compared to a nonconductive polyethylene glycol terephthalate scaffold. Transcriptome sequencing revealed that fibromodulin and tenomodulin expression were upregulated, and their related proteoglycans and glycosaminoglycan binding proteins pathways were enhanced, which could regulate the TGF-ß signaling pathway and optimize the extracellular matrix assembly, thus promoting tendon repair. Therefore, the scaffold in this study makes up for the shortage of conductive scaffolds for repairing tendon defects, revealing the potential impact of conductivity on the signaling pathway of tendon repair and providing a new approach for future clinical studies.

High power density redox-mediated Shewanella microbial flow fuel cells.

Microbial fuel cells utilize exoelectrogenic microorganisms to directly convert organic matter into electricity, offering a compelling approach for simultaneous power generation and wastewater treatment. However, conventional microbial fuel cells typically require thick biofilms for sufficient metabolic electron production rate, which inevitably compromises mass and charge transport, posing a fundamental tradeoff that limits the achievable power density (<1 mW cm-2). Herein, we report a concept for redox-mediated microbial flow fuel cells that utilizes artificial redox mediators in a flowing medium to efficiently transfer metabolic electrons from planktonic bacteria to electrodes. This approach effectively overcomes mass and charge transport limitations, substantially reducing internal resistance. The biofilm-free microbial flow fuel cell thus breaks the inherent tradeoff in dense biofilms, resulting in a maximum current density surpassing 40 mA cm-2 and a highest power density exceeding 10 mW cm-2, approximately one order of magnitude higher than those of state-of-the-art microbial fuel cells.

Modulation of pulsed electric field induced oxidative processes in protein solutions by pro- and antioxidants sensed by biochemiluminescence.

Technologies based on pulsed electric field (PEF) are increasingly pervasive in medical and industrial applications. However, the detailed understanding of how PEF acts on biosamples including proteins at the molecular level is missing. There are indications that PEF might act on biomolecules via electrogenerated reactive oxygen species (ROS). However, it is unclear how this action is modulated by the pro- and antioxidants, which are naturally present components of biosamples. This knowledge gap is often due to insufficient sensitivity of the conventionally utilized detection assays. To overcome this limitation, here we employed an endogenous (bio)chemiluminescence sensing platform, which enables sensitive detection of PEF-generated ROS and oxidative processes in proteins, to inspect effects of pro-and antioxidants. Taking bovine serum albumin (BSA) as a model protein, we found that the chemiluminescence signal arising from its solution is greatly enhanced in the presence of H 2 O 2 as a prooxidant, especially during PEF treatment. In contrast, the chemiluminescence signal decreases in the presence of antioxidant enzymes (catalase, superoxide dismutase), indicating the involvement of both H 2 O 2 and electrogenerated superoxide anion in oxidation-reporting chemiluminescence signal before, during, and after PEF treatment. We also performed additional biochemical and biophysical assays, which confirmed that BSA underwent structural changes after H 2 O 2 treatment, with PEF having only a minor effect. We proposed a scheme describing the reactions leading from interfacial charge transfer at the anode by which ROS are generated to the actual photon emission. Results of our work help to elucidate the mechanisms of action of PEF on proteins via electrogenerated reactive oxygen species and open up new avenues for the application of PEF technology. The developed chemiluminescence technique enables label-free, in-situ and non-destructive sensing of interactions between ROS and proteins. The technique may be applied to study oxidative damage of other classes of biomolecules such as lipids, nucleic acids or carbohydrates.

Energy regeneration: A study on dynamic capacitance adjustment technology in piezoelectric shock absorbers for electric vehicles under varied road conditions.

This study investigates the performance of dynamic capacitance regulation technology in electric vehicle piezoelectric shock absorbers for energy recovery under varying road conditions. By simulating a quarter-vehicle suspension system, this paper comprehensively analyzes the energy recovery efficiency of piezoelectric shock absorbers on gravel, speed bumps, and bumpy road conditions, comparing the performance differences between traditional fixed capacitance and dynamic capacitance. The results demonstrate that dynamic capacitance regulation technology can automatically adjust the capacitance value in response to instantaneous voltage changes, thereby enhancing energy recovery efficiency under various road conditions. This technology not only improves the energy conversion efficiency of piezoelectric shock absorbers but also strengthens the system's adaptability to different vibration frequencies and amplitudes. Further simulation evidence confirms that piezoelectric shock absorbers, under dynamic capacitance regulation, achieve better energy recovery performance across diverse road conditions, offering new insights into improving the energy efficiency and sustainability of electric vehicles. The novelty of this research lies in the first application of dynamic capacitance regulation technology to the energy recovery system of electric vehicle piezoelectric shock absorbers, providing a new theoretical foundation and technical reference for optimizing electric vehicle energy recovery systems.

Pre-anoxic electro-stimulation enhanced simultaneous nitrification-denitrification in single-stage electrolysis-integrated sequencing batch biofilm reactor.

Simultaneous nitrification-denitrification (SND) is a promising nitrogen removal process. However, total nitrogen (TN) removal is limited due to unsatisfactory denitrification. This study demonstrated that short-time (1 h) pre-anoxic electro-stimulation significantly enhanced SND efficiency in the aerobic phase by promoting the proliferation of mixotrophic and heterotrophic denitrifiers. SND and TN removal efficiencies at the optimal electric current (EC) (0.02 A) were 85.6 % and 93.9 %, which were 39.1 % and 17.2 % higher than control. Microbial community analysis indicated that the abundance of mixotrophic and heterotrophic denitrifiers significantly increased. H2 generated in the electro-stimulation process induced the proliferation of mixotrophic denitrifiers. The weak EC (0.02 A) promoted the activity and growth of heterotrophic denitrifiers by accelerating electron transfer. They concurrently mediated heterotrophic denitrification to enhance SND efficiency. PICRUSt2 analysis revealed that the abundance of denitrifying genes dramatically surged. This study provides new insights into applying electrolysis to achieve advanced SND while minimizing electricity consumption.

Baffled flow constructed wetland-microbial fuel cell coupling systems for combined secondary and tertiary wastewater treatment with simultaneous bioelectricity generation.

Baffled flow constructed wetland-microbial fuel cell (BFCW-MFC) coupling systems were constructed with baffles embedded in cathode chamber. The performance of BFCW-MFCs operated at different hydraulic retention times (HRTs) was evaluated. At the representative HRT of 48 h, embedding 1 or 2 baffles (i.e., BFCW-MFC1 and BFCW-MFC2) produced 32.9 % (29.5 mW/m3) and 53.2 % (34.0 mW/m3) more power density than control system (22.2 mW/m3), respectively. Comparable organics biodegradation efficiencies were observed in BFCW-MFCs at the same HRTs. BFCW-MFC1 and BFCW-MFC2 had higher ammonium and total nitrogen removal efficiency. All systems had decreased nitrogen removal performance as shortening HRT from 72 to 12 h. Multiple nitrogen removal processes were involved, including ammonium oxidation, anammox, and heterotrophic and autotrophic denitrification. The predominant bacteria on electrodes were identified for analyzing bioelectricity generation and wastewater treatment processes. Generally, simultaneous wastewater treatment and bioelectricity generation were obtained in BFCW-MFCs, and embedding 1 or 2 baffles was preferable.