Multiple Substations Research Articles

Cooperative energy interaction for neighboring multiple distribution substation areas considering demand response

With the growing integration of renewable energy into medium- and low-voltage distribution networks, the distribution substation area (DSA) has emerged, encompassing energy storage and loads. This paper introduces an energy interaction framework for multiple DSAs aimed at enhancing local renewable energy consumption. The energy interaction issue among various DSAs is modeled as a Nash bargaining problem to encourage energy exchanges. However, the variability in pricing and internal demand response may influence scheduling decisions, necessitating further investigation. To address price forecast errors, scenarios are developed using a stochastic programming approach to represent price uncertainties while adjusting the DSA’s load accordingly. Optimal power flow constraints are integrated into the model to bolster power system operation security. Additionally, the transmission capacity can impact scheduling outcomes and operational costs. The influence of transmission limitations on operational strategies is examined within the allowable capacity. To solve this issue, the bargaining model is divided into two subproblems, and an enhanced alternating direction multiplier method (ADMM) is used to maintain the privacy of DSAs. The simulation results obtained using the IEEE-33 bus system indicate that energy interaction among multiple DSAs significantly lowers operating costs and facilitates the integration of renewable energy.

Cryo-PRO facilitates whole blood cryopreservation for single-cell RNA sequencing of immune cells from clinical samples.

Single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) has enhanced our understanding of host immune mechanisms in small cohorts, particularly in diseases with complex and heterogeneous immune responses such as sepsis. However, PBMC isolation from blood requires technical expertise, training, and approximately two hours of onsite processing using Ficoll density gradient separation ('Ficoll') for scRNA-seq compatibility, precluding large-scale sample collection at most clinical sites. To minimize onsite processing, we developed Cryo-PRO (Cryopreservation with PBMC Recovery Offsite), a method of PBMC isolation from cryopreserved whole blood that allows immediate onsite sample cryopreservation and subsequent PBMC isolation in a central laboratory prior to sequencing. We compared scRNA-seq results from samples processed using Cryo-PRO versus standard onsite Ficoll separation in 23 patients with sepsis. Critical scRNA-seq outputs including cell substate fractions and marker genes were similar for each method across multiple cell types and substates, including an important monocyte substate enriched in patients with sepsis (Pearson correlation 0.78, p<0.001; 70% of top marker genes shared). Cryo-PRO reduced onsite sample processing time from >2 hours to <15 minutes and was reproducible across two enrollment sites, thus demonstrating potential for expanding scRNA-seq in multicenter studies of sepsis and other diseases.

19F-NMR Probing of Ion-Induced Conformational Changes in Detergent-Solubilized and Nanodisc-Reconstituted NCX_Mj.

Consecutive interactions of 3Na+ or 1Ca2+ with the Na+/Ca2+ exchanger (NCX) result in an alternative exposure (access) of the cytosolic and extracellular vestibules to opposite sides of the membrane, where ion-induced transitions between the outward-facing (OF) and inward-facing (IF) conformational states drive a transport cycle. Here, we investigate sub-state populations of apo and ion-bound species in the OF and IF states by analyzing detergent-solubilized and nanodisc-reconstituted preparations of NCX_Mj with 19F-NMR. The 19F probe was covalently attached to the cysteine residues at entry locations of the cytosolic and extracellular vestibules. Multiple sub-states of apo and ion-bound species were observed in nanodisc-reconstituted (but not in detergent-solubilized) NCX_Mj, meaning that the lipid-membrane environment preconditions multiple sub-state populations toward the OF/IF swapping. Most importantly, ion-induced sub-state redistributions occur within each major (OF or IF) state, where sub-state interconversions may precondition the OF/IF swapping. In contrast with large changes in population redistributions, the sum of sub-state populations within each inherent state (OF or IF) remains nearly unchanged upon ion addition. The present findings allow the further elucidation of structure-dynamic modules underlying ion-induced conformational changes that determine a functional asymmetry of ion access/translocation at opposite sides of the membrane and ion transport rates concurring physiological demands.

A Decentralized Coordinated Control Strategy for Multiple Traction Substations in MVdc Railway Power Supply System

A Decentralized Coordinated Control Strategy for Multiple Traction Substations in MVdc Railway Power Supply System

Mathematical Modeling of Multiple Capacitor Coupled Substations (CCS) Impact on Transmission Lines and Approaches for Ferroresonance Suppression

Mathematical Modeling of Multiple Capacitor Coupled Substations (CCS) Impact on Transmission Lines and Approaches for Ferroresonance Suppression

An enhanced CNN-LSTM based multi-stage framework for PV and load short-term forecasting: DSO scenarios

The importance of accurate forecasting in the electric sector has grown due to the increasing demand and adoption of high volume of Renewable Energy Sources (RES). Short-term forecasting (STF) using deep learning methods has shown potential for improving forecasting accuracy. However, the accuracy of these methods can be further enhanced by combining them to generate a hybrid model, selecting appropriate input features, generating new features, and optimizing model parameters. This paper proposes a novel multi-stage framework for PV and load STF that employs feature generation, feature selection, and optimal hyperparameter tuning preprocessing techniques. An enhanced hybrid CNN-LSTM deep learning model architecture is developed in the final stage of the proposed framework. The framework is assessed and compared to other leading-edge approaches across different DSO scenarios, including multiple single-phase residential loads, three-phase feeders, and secondary substation, demonstrating a significant reduction in forecasting errors.

Modeling and stability prediction for the static-power-converters interfaced flexible AC traction power supply system with power sharing scheme

The flexible traction power supply system (FTPSS) is a promising solution to solve the electric phase break and power quality problems existing in traditional traction power supply systems. To promote the balance of train power distribution among multiple substations, power sharing control is proposed by combining average power control and P-f and Q-V droops based on virtual power decoupling method. The active and reactive power is decoupled through introducing the impedance angle without knowing specific values of the line inductance and resistance. This system level control poses new challenges to the stability of the electric railway due to complex interactions between power electronic-based substations of the FTPSS. To address this issue, the frequency-domain model of the FTPSS with power sharing control is established. Then, the eigenvalue-based stability criterion is introduced to predict the stability of the interconnected system. In particular, to obtain how the power sharing control is sensitive to some controller/circuit parameters, a parameter-oriented stability analysis method is developed through assessing the influence of the key influential factors, including the time delay of wide-area communication, the controller parameters of the power sharing scheme, the circuit parameters, the length of the traction network and the train power requirement. The time-domain simulation and the downscaled prototype experiment are conducted to validate the effectiveness of the established model and the theoretical analysis. This lays the foundation for the design and stability analysis of the FTPSS.

Evaluating distribution network optimal structure with respect to solar hosting capacity

Optimal design of distribution networks has become an important topic for analysis due to the growing share of photovoltaics (PV). Low and medium voltage networks should undergo structural changes to accommodate widespread PV generation and optimal operation. In this paper, the impact of the network structure on the solar hosting capacity (HC) is analyzed with respect to the role of low and medium voltage networks in power delivery. A given set of load nodes is simulated with multiple feeding substations and varying peak power and number of PV plants. The slime mold algorithm is utilized for numerous topology generations and measured load time series represent regions ranging from rural to urban. The results reveal that networks should go through significant structural changes to cope with larger PV generation and even more so to increase the HC. On the other hand, voltage control measures, such as on-load tap changers, PV reactive power control and curtailment, provide a competitive solution to varying size of distribution networks in hosting solar power. Finally, the analysis in this study provides evidence to a possible need in the change of residential PV policies in order to sustain the current pace of adopting PV plants in Finland.

Urea induced unfolding of rai seed cystatin: Influence of glycerol as a chemical chaperone

Cystatin superfamily members, by virtue of their thiol protease regulatory properties, show involvement in myriad physiological processes important for survival and well-being. The current study involves urea-induced denaturation of a novel variant of the cystatin superfamily, rai seed cystatin (RSC), employing a variety of biophysical assays in order to characterize different folding intermediates generated on unfolding. Urea as a denaturant presented the passage of RSC through a series of events resulting in the loss of RSC functional capability, accompanied by changes in the archetype at secondary and tertiary structural levels, as evident from protease inhibitory, UV absorption, and intrinsic fluorescence assays, respectively. ANS fluorescence also revealed routing of RSC through discrete multiple sub-states thus presenting the generation of intermediate states somewhat close to the pre-molten globule and/or molten globule forms of RSC. Furthermore, far-UV circular dichroism analysis revealed a concentration-dependent gradual loss in typical -helical RSC peaks, indicating a nearly 50 % loss in secondary structural elements around 5 M urea treatment. The study also reports the possible role of glycerol in the refolding and/or reactivation of the urea unfolded RSC form. Glycerol presented itself as a potent structural stabilizer as it assisted in the refolding and reactivation of the unfolded RSC in a dosage-dependent manner, concomitantly paving the way for unravelling the mechanistic approach involved in the phenomenon, which can facilitate future studies.

Systematic protective scheme for mega‐city power systems against stray currents caused by metro systems

AbstractIn modern megacities, stray currents from metro systems intrude into multiple transformers' neutral points becoming a potential threat to the high‐capacity transformers. Neutral current anomalies are exacerbated in unprotected substations when we instal guards at single stations. This paper presents a system protection strategy for multiple substations affected by stray currents in modern megacities. The model, taking Shanghai as an example, includes the spatial distribution information of the urban electrical energy transmission structure, the power system, and the metro system. A Particle swarm algorithm is used to calculate the resistance values of the devices for each station. Further stability tests are performed to select the optimal protection solution. The results show that when protection is considered as a system, the protection runs well and the neutral current level remains below the unprotected level when the protection fails at a single station or multiple stations.

Genetic Perturbation Alters Functional Substates in Alkaline Phosphatase

Enzymes inherently exhibit molecule-to-molecule heterogeneity in their conformational and functional states, which is considered to be a key to the evolution of new functions. Single-molecule enzyme assays enable us to directly observe such multiple functional states or functional substates. Here, we quantitatively analyzed functional substates in the wild-type and 69 single-point mutants of Escherichia coli alkaline phosphatase by employing a high-throughput single-molecule assay with a femtoliter reactor array device. Interestingly, many mutant enzymes exhibited significantly heterogeneous functional substates with various types, while the wild-type enzyme showed a highly homogeneous substate. We identified a correlation between the degree of functional substates and the level of improvement in promiscuous activities. Our work provides much comprehensive evidence that the functional substates can be easily altered by mutations, and the evolution toward a new catalytic activity may involve the modulation of the functional substates.

Unified Power Quality Management for Traction Substation Groups Connected to Weak Power Grids

In remote areas, weak power grids, fewer grid access points, and power quality (PQ) problems dominated by excessive voltage unbalance (VU) and lower power factor (PF) have been prominent obstacles in single-phase 25 kV AC traction power supply systems. To achieve a long-distance power supply with a high PQ, a traction substation group connected to a weak remote power grid is introduced, where the electrical structure is composed of multiple slave traction substations using single-phase traction transformers (TTs), a master traction substation (MTS) using a combination of TTs and a power flow controller (PFC) adopting a modular multilevel converter (MMC). Then, a unified mathematical model of the proposed system suitable for different TT wiring types revealing the effect of asymmetrical grids on the PFC is established. The negative sequence current (NSC) caused by multiple traction stations at the point of common coupling (PCC) and the PF can be improved effectively based on power conservation theory. In addition, to reduce the compensation capacity, an optimization compensation strategy is proposed. Finally, the effectiveness of the proposed algorithm is verified by simulation and a case study. The installed capacity of the PFC is 18.5% lower than that of traditional compensation.

Modulation of GPCR Rhodopsin Function by Membrane Lipids and Water

G protein‐coupled receptors (GPCRs) are responsible for the transduction of signals across lipid membranes and are the largest family of targets (~35%) for currently approved drugs. They exist as dynamic conformational ensembles with multiple inactive and active conformational substates described by an energy landscape model. Consequently, understanding the modulation of conformational dynamics of GPCRs by soft matter such as membrane lipids and cellular water in the receptor’s environment is critical to understanding GPCR efficacy and selectivity. Here we show how membrane lipids and cellular water play crucial roles in shaping the energy landscape of GPCR activation, thus acting as allosteric modulators. We investigated ways in which the receptor hydration level and lipid bilayer composition influence the metarhodopsin equilibrium of the archetypical GPCR rhodopsin in native and POPC recombinant membranes after light activation. Using different polyethylene glycol (PEG) solutions, the osmotic pressure on rhodopsin was varied, while shifting of the metarhodopsin equilibrium was probed using UV‐Visible spectroscopy. Our results show a flood of ~80‐100 water molecules into the rhodopsin interior during photoactivation, forming a solvent‐swollen Meta‐II active state. Dehydrating conditions favor Meta‐I through the efflux of water from the protein interior yet simultaneously increase bilayer thickness, which should favor Meta‐II. Because the osmotic effect on the protein is more significant than the effect of the lipid bilayer, the overall equilibrium is generally shifted to Meta‐I. However, small osmolytes favored the Meta‐II state because they can penetrate the protein core, decreasing the osmotic effect on the protein. Furthermore, the metarhodopsin equilibrium was shifted towards the Meta‐I state in POPC recombinant membranes compared to the native membrane environment. Analysis of transducin C‐terminal peptide‐binding isotherms revealed that the G‐prottein binding affinity is significantly decreased when the lipid environment is changed from the native lipids to POPC lipids. The POPC lipid membrane has zero spontaneous curvature that shifts the equilibrium towards the more compact, inactive Meta‐I state. By contrast, the native lipid membrane environment possesses a negative spontaneous curvature that favors the more expanded state of Meta‐II. Our results delineate the crucial role of soft matter in regulating the metarhodopsin equilibrium in a membrane environment.

Shape shifting: The multiple conformational substates of the PTEN N-terminal PIP2 -binding domain.

The Phosphatase and TENsin homolog deleted on chromosome 10 (PTEN) is a chief regulator of a variety of cellular processes including cell proliferation, migration, growth, and death. It is also a major tumor suppressor gene that is frequently mutated or lost under cancerous conditions. PTEN encodes a dual‐specificity (lipid and protein) phosphatase that negatively regulates the PI3K/AKT/mTOR signaling pathway where the PIP2‐binding domain (PBD) regulates the lipid phosphatase function. Unfortunately, despite two decades of research, a full‐length structure of PTEN remains elusive, leaving open questions regarding PTEN's disordered regions that mediate protein stability, post‐translational modifications, protein–protein interactions, while also hindering the design of small molecules that can regulate PTEN's function. Here, we utilized a combination of crosslinking mass spectrometry, in silico predicted structural modeling (including AlphaFold2), molecular docking, molecular dynamics simulations, and residue interaction network modeling to obtain structural details and molecular insight into the behavior of the PBD of PTEN. Our study shows that the PBD exists in multiple conformations which suggests its ability to regulate PTEN's variety of functions. Studying how these specific conformational substates contribute to PTEN function is imperative to defining its function in disease pathogenesis, and to delineate ways to modulate its tumor suppressor activity.

Landscape-Based Protein Stability Analysis and Network Modeling of Multiple Conformational States of the SARS-CoV-2 Spike D614G Mutant: Conformational Plasticity and Frustration-Induced Allostery as Energetic Drivers of Highly Transmissible Spike Variants.

The structural and functional studies of the SARS-CoV-2 spike protein variants revealed an important role of the D614G mutation that is shared across many variants of concern (VOCs), suggesting the effect of this mutation on the enhanced virus infectivity and transmissibility. The recent structural and biophysical studies provided important evidence about multiple conformational substates of the D614G spike protein. The development of a plausible mechanistic model that can explain the experimental observations from a more unified thermodynamic perspective is an important objective of the current work. In this study, we employed efficient and accurate coarse-grained simulations of multiple structural substates of the D614G spike trimers together with the ensemble-based mutational frustration analysis to characterize the dynamics signatures of the conformational landscapes. By combining the local frustration profiling of the conformational states with residue-based mutational scanning of protein stability and network analysis of allosteric interactions and communications, we determine the patterns of mutational sensitivity in the functional regions and sites of variants. We found that the D614G mutation may induce a considerable conformational adaptability of the open states in the SARS-CoV-2 spike protein without compromising the folding stability and integrity of the spike protein. The results suggest that the D614G mutant may employ a hinge-shift mechanism in which the dynamic couplings between the site of mutation and the interprotomer hinge modulate the interdomain interactions, global mobility change, and the increased stability of the open form. This study proposes that mutation-induced modulation of the conformational flexibility and energetic frustration at the interprotomer interfaces may serve as an efficient mechanism for allosteric regulation of the SARS-CoV-2 spike proteins.

Hydration-water and membrane lipids modulate G-protein-coupled receptor activation

G-protein-coupled receptors (GPCRs) are responsible for transducing signals across lipid membranes in cells and are the largest family of targets (∼40%) for currently approved drugs. They exist as dynamic conformational ensembles with multiple inactive and active conformational substates described by an energy landscape model. We investigated ways in which the receptor hydration level and lipid bilayer composition influence the activation of the archetypical GPCR rhodopsin by quantifying the shift in the metarhodopsin equilibrium in native and POPC recombinant membranes by different polyethylene glycol osmolyte solutions.

Diversified Software Deployment for Long-Term Risk Mitigation in Cyber-Physical Power Systems

Since modern cyber-physical power systems are vulnerable to coordinated wide-area cyber attacks, it is necessary to mitigate the potential risk as much as possible. At the planning stage, the defender can utilize software diversity, which is a common phenomenon that the cyber software of different substations comes from different competing vendors. Therefore, different kinds of software may not be exposed to the same zero-day security loophole, preventing the attacker from taking charge of multiple substations at the same time. In this paper, the optimal scheme of software deployment considering long-term risk mitigation is studied. Firstly, the framework of diversity-based cyber defense against malicious attacks is formulated. Secondly, the risk index based on representative attack patterns is constructed, which is the objective to be minimized. Thirdly, considering that the deployment scheme is long-term stable while the operating mode varies with time, we construct a multiobjective nonlinear stochastic programming to mitigate the average risk of operating modes. Then the optimization problem is solved by the multiobjective genetic algorithm. Lastly, results of the IEEE 39-node CPPS and and the Virtual European Grid demonstrate that the proposed method can considerably reduce the attack risk.

Development of a Generalized Scaled-Down Realistic Substation Laboratory Model for Smart Grid Research and Education

This paper introduces a physical scaled-down realistic substation laboratory model development for translational research and education in smart grids. The development of a substation panel with four 3-<inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula> feeders of 415 V, 65 A rating is described in detail. The developed substation model can be configured to realize seven widely used substation bus bar arrangements. A programmable logic controller (PLC) is used to create interlock mechanisms for mimicking the actual substation operation practices. Provision is made to realize the gang and independent pole operation of circuit breakers, the manual and remote modes of operation, and different types of current transformer arrangements. The substation panel can host up to 10 commercial IEDs, and multiple substation panels can be cascaded to form a bigger station using the master-slave configuration of PLCs. All the potential transformer and current transformer measurements, circuit breaker, isolator, and earth switch status signals are made available for connecting field devices. The developed substation model can be used for advanced research on substation automation using IEC61850, validation of new protection strategies, implementation and testing of new algorithms (such as topology processing, state estimation) for energy management systems (EMS) like how they get implemented in the field.

Phase-Amplitude Coupling Features Accurately Classify Multiple Sub-States Within a Seizure Episode.

Epilepsy is frequently characterized by convulsive seizures, which are often followed by a postictal EEG suppression state (PGES). The ability to automatically detect and monitor seizure progression and postictal state can allow for early warning of seizure onset, timely intervention in seizures themselves, as well as identification of major complications in epilepsy such as status epilepticus and sudden unexpected death in epilepsy (SUDEP). To test whether it is possible to reliably differentiate these ictal and postictal states, we investigated 52 seizure records (both intracranial and scalp EEG) from 19 patients. Phase-amplitude cross-frequency coupling was calculated for each recording and used as an input to a convolutional neural network model, achieving the mean accuracy of 0.890.09 across all classes, with the worst class accuracy of 0.73 for one of the later ictal sub-states. When the trained model was applied to SUDEP patient data, it classified seizure recordings as primarily interictal and PGES-like state (70% and 26%, respectively), highlighting the fact that in SUDEP patients seizures primarily exist in postictal states and don't show the ictal sub-state evolution. These results suggest that using frequency coupling markers with a machine learning algorithm can reliably identify ictal and postictal sub-states, which can open up opportunities for novel monitoring and management approaches in epilepsy.

D614G mutation in the SARS-CoV-2 spike protein enhances viral fitness by desensitizing it to temperature-dependent denaturation

The D614G mutation in the spike protein of SARS-CoV-2 alters the fitness of the virus, leading to the dominant form observed in the COVID-19 pandemic. However, the molecular basis of the mechanism by which this mutation enhances fitness is not clear. Here we demonstrated by cryo-electron microscopy that the D614G mutation resulted in increased propensity of multiple receptor-binding domains (RBDs) in an upward conformation poised for host receptor binding. Multiple substates within the one RBD-up or two RBD-up conformational space were determined. According to negative staining electron microscopy, differential scanning calorimetry, and differential scanning fluorimetry, the most significant impact of the mutation lies in its ability to eliminate the unusual cold-induced unfolding characteristics and to significantly increase the thermal stability under physiological pH. The D614G spike variant also exhibited exceptional long-term stability when stored at 37 °C for up to 2 months. Our findings shed light on how the D614G mutation enhances the infectivity of SARS-CoV-2 through a stabilizing mutation and suggest an approach for better design of spike protein-based conjugates for vaccine development.