Electric vehicle (EV) adoption is generating a rapidly increasing stream of retired lithium-ion batteries for second-life deployment. However, thermal safety concerns continue to limit their reuse. This paper reviews second-life battery (SLB) thermal safety and management and organizes existing work through a mechanism-to-deployment framework linking four domains: degradation mechanisms, cell screening, pack configuration, and monitoring. Evidence indicates that thermal risk depends on the degradation pathway rather than capacity fade. In fact, cells with comparable capacity can exhibit substantially different trigger temperatures depending on whether lithium plating or solid-electrolyte interphase (SEI) growth dominates. Therefore, capacity-based screening is insufficient because cells that satisfy capacity thresholds may still remain thermally unstable. The four domains are tightly coupled: the degradation pathway determines screening requirements; screening outcomes constrain pack design; pack topology influences fault escalation; and together these factors determine what monitoring can reliably detect. This review highlights three gaps and outlines future research directions in the field of SLB thermal safety and management: limited aged-cell thermal characterization by degradation pathway, insufficient diagnostic validation under industrial-throughput conditions, and the incomplete translation of screening outputs into design rules.
Production of electric energy or power. Powerplants. Central stations, Industrial electrochemistry
The single-stage transformerless photovoltaic (PV) topology is an attractive configuration as it offers high efficiency, low installation cost and smaller size. For such a configuration, the control algorithm should be designed to track the maximum power point, transform power from PV to grid, and reduce the common-mode voltage (CMV) simultaneously. However, the multi-objective handling problem will lead to degraded performance and slow response speed. In this paper, a model predictive control method with a revised switching states selection algorithm has been developed. The performance of the overall system can be enhanced under various conditions with improved efficiency. Furthermore, the CMV is greatly reduced and constrained to one sixth of the DC-link voltage. In addition, appropriate candidate region selection and pruning mechanism are employed to reduce the calculation burden of MPC. Finally, the performance of the proposed MPC method is verified by the control hardware-in-the-loop approach through OPAL real-time platform under various conditions.
Production of electric energy or power. Powerplants. Central stations
Changing the topography of electrodes by ultrafast laser ablation has shown great potential in enhancing electrochemical performance in lithium-ion batteries. The generation of microstructured channels within the electrodes creates shorter pathways for lithium-ion diffusion and mitigates strain from volume expansion during electrochemical cycling. The topography modification enables faster charging, improved rate capability, and the potential to combine high-power and high-energy properties. In this study, we present a preliminary exploration of this approach for sodium-ion battery technology, focusing on the impact of laser-generated channels on hard carbon electrodes in sodium-metal half-cells. The performance was analyzed by employing different conditions, including different electrolytes, separators, and electrodes with varying compaction degrees. To identify key factors contributing to rate capability improvements, we conducted a comparative analysis of laser-structured and unstructured electrodes using methods including scanning electron microscopy, laser-induced breakdown spectroscopy, and electrochemical cycling. Despite being based on a limited sample size, the data reveal promising trends and serve as a basis for further optimization. Our findings suggest that laser structuring can enhance rate capability, particularly under conditions of limited electrolyte wetting or increased electrode density. This highlights the potential of laser structuring to optimize electrode design for next-generation sodium-ion batteries and other post-lithium technologies.
Production of electric energy or power. Powerplants. Central stations, Industrial electrochemistry
Amol U. Pawar, Ignasia H. Mahardika, Young S. Son
et al.
ABSTRACT Achieving carbon neutrality is urgent due to the critical issue of climate change. To reach this goal, the development of new, breakthrough technologies is necessary and urgent. One such technology involves efficient carbon capture and its conversion into useful chemicals or fuels. However, achieving considerable amounts of efficiency in this field is a very challenging task. Even in natural photosynthesis occurring in plant leaves, the CO2 conversion efficiency into hydrocarbons cannot exceed a value of 1%. Nevertheless, recently few reports show comparable higher efficiency in CO2 to gaseous products such as carbon monoxide (CO), but it is hard to find selective liquid fuel products with a high value of solar to liquid fuel conversion efficiency. Herein, a NiFe‐assisted hybrid composite dark cathode is employed for the selective production of solar‐to‐liquid fuels, in conjunction with a BiVO4 photoanode. This process results in the generation of significant amounts of formaldehyde, ethanol, and methanol selectively. The primary objective of this study is to design and optimize a novel photoelectrochemical (PEC) system to produce solar‐to‐liquid fuels selectively. This study shows the enhancement of the solar‐to‐fuel conversion efficiency over 1.5% by employing a hybrid composite cathode composed of NiFe‐assisted reduced graphene oxide (rGO), poly(4‐vinyl)pyridine (PVP), and Nafion.
Production of electric energy or power. Powerplants. Central stations
Longjian Piao, Laurens de Vries, Mathijs de Weerdt
et al.
Future energy markets for low voltage AC and DC distribution systems will facilitate prosumer participation in the market. To comply with market regulations and grid constraints, a tailored market design reflecting (DC) operational requirements is needed. Our previous work identified a locational energy market design. However, its real-life implementation faces challenges due to uncertainties in system operation, prosumer preferences, and bidding strategies. This article tests the market design under uncertain scenarios. To this end, we develop an agent-based model that simulates typical electric vehicle user preferences and bidding strategies, influenced by varying degrees of range anxiety. The market design is tested in challenging scenarios with a high share of solar panels and electric vehicles, modelled using the high-resolution Pecan Street database. Simulations indicate that the proposed market design maintains both economic efficiency and system reliability under real-life uncertainties. This in turn indicates the practical feasibility of locational energy markets in helping to integrate renewable generation sources and bidirectional power flows.
Production of electric energy or power. Powerplants. Central stations
The on-load tap changer (OLTC), widely used as a voltage regulation device in power systems, requires regular assessment and maintenance to ensure reliable operation and avoid adverse impacts on the power system. These assessments encompass key parameters such as transition waveform, transition time, three-phase synchronization, and transition resistor, along with the operational status of the mechanical structure. However, the maintenance process, typically conducted offline, can diminish equipment efficiency. Moreover, the accuracy of some parameter measurements needs improvement. To bolster equipment reliability and refine detection methods for critical parameters, this study explores online detection techniques for key switching parameters of the OLTC body. This paper proposes a method to identify these key parameters in the switching circuit, using coordinate transformation as the core algorithm. We used a specific vacuum OLTC device for our research, conducted theoretical analyses, developed a simulation model to validate the proposed method for identifying OLTC switching parameters, and further built a test platform to verify the algorithm’s effectiveness. The results show a close alignment between simulation and actual measurement outcomes. Each switching process interval conforms to the manufacturer’s design specifications for the equipment, with the transition resistor parameter calculation accuracy ranging from approximately 95.39% to 100%. Similarly, the tap winding voltage calculation accuracy is between approximately 91.52% and 100%, satisfying engineering requirements and enterprise standard [1]. This method provides a basis for optimizing the measurement of working parameters in OLTC equipment and aims to offer ideas for the next step of prototype development.
Production of electric energy or power. Powerplants. Central stations
Peiyao Guo, Shahab Dehghan, Vladimir Terzija
et al.
With the increasing share of wind power in the energy sector, many countries start to cut back supporting policies for wind power and shift towards market-oriented schemes, challenging the profitability of wind farms. Energy storage offers a flexible solution to enhance their profitability. This work explores different wind-related storage investment modes, including 1) direct ownership, 2) cooperative, and 3) competitive modes in a market-based environment. For the direct ownership mode, a bilevel single-leader-single–follower Stackelberg game model is proposed, where wind farms invest in and operate storage facilities strategically to maximize their profits in the upper level, while the lower-level problem represents the system operator’ s market-clearing process. A cooperative game framework is presented for the cooperative mode, that wind farms and storage investors agree on a profit allocation rule, i.e., Shapley value or Nucleolus to collaborate in investing and bidding as a coalition. The competitive mode is interpreted as a multi-leader-single-follower Stackelberg game, describing an independent investor investing in and operating storage facilities in competition with wind farms. Case studies conducted on a 6-bus and the IEEE 30-bus test systems demonstrate that storage facilities directly invested in by wind farms are the best option for maximizing their profits, resulting in up to an 8.7% increase. The cooperative option provides a suboptimal increase of up to 3.1%, diversifying the costs and risks associated with storage investments. In contrast, the competitive mode can diminish wind farms’ profitability, with up to a 30.6% decrease in profits.
Production of electric energy or power. Powerplants. Central stations
. The widespread introduction of information technologies into all spheres of society, the crea-tion of a significant amount of confidential and critical data in digital form leads to an increase in the priority of information security tasks everywhere, including in the energy sector, which relates to the critical infrastructure of any state. The purpose of the work is to develop the men-tioned approach to ensure the possibility of increasing the efficiency of information security methods based on it. The goal was achieved through a detailed study of disturbances in the val-ues of formal parameters that uniquely determine the matrix that is assigned to the information security system under conditions of active attacks (disturbances) on the system. Singular num-bers and singular vectors of the matrix are considered as such parameters. The most important result of the work is the substantiation of the existence and establishment of interconnected re-gions of stabilization of disturbances of singular numbers and singular vectors of the system ma-trix, while the region of stabilization of singular numbers corresponds to the region of monoto-nous decrease in their disturbances with increasing numbers, while the stabilization of singular vectors corresponds to the region in which their disturbances are comparable with 90 degrees. It is shown that the stabilization process is determined by the mathematical properties of the pa-rameters under consideration. The significance of the obtained result lies in the possibility of using it to improve various information security systems that were built or studied using a gen-eral approach to analyzing their state, both theoretically and practically. The work provides ex-amples of such use.
Electrical engineering. Electronics. Nuclear engineering, Production of electric energy or power. Powerplants. Central stations
The Gaussian noise distribution is typically used in dynamic state estimation (DSE) but it is not always true in practice because of abnormal system inputs, impulsive noise and measurement outliers. In this paper, a new robust DSE approach based on a new robust Lp norm based estimator and the cubature Kalman filter (CKF) is developed for power systems with non-Gaussian noise statistics. The Lp norm based estimator is derived from the Lp norm formula and the quadratic formula in order to alleviate the impacts from bad data and outliers. The proposed Lp-CKF DSE approach exhibits good accuracy because a new estimation error covariance is obtained by using the influence function. The robustness of the proposed Lp-CKF DSE approach is verified by performing simulations on a generator in the IEEE 39-bus system.
Production of electric energy or power. Powerplants. Central stations
Mohammad Ebrahim Hajiabadi, Mahdi Samadi, Mohammad Hassan Nikkhah
et al.
Abstract One of the primary challenges faced by generation companies (GenCos), which operate multiple generation units within the electricity market, is the determination of the optimal bid price for these units to maximize profit. This paper proposes a novel approach to ascertain the optimal bid price direction for GenCos by leveraging the gradient vector of the profit function within the constraints of the electricity market. First, the Jacobian matrix of unit profits is computed using the electricity market structural decomposition method. This matrix highlights how the profit of generation units is affected by market input parameters, including the bid prices of the units. Then, the gradient vector of the GenCos' profit function and the optimal bid price direction are derived from the Jacobian matrix. The methodology is applied to a 24‐bus IEEE network, with results validated against those from a simulation method to confirm the efficacy of the proposed approach. The simulation results show that the highest and lowest profit changes with a step increase of 0.1$/MWh are observed for GenCo 4 and GenCo 6 with values of 60.28 and 2.20 $/h, respectively. The proposed approach can be effective in the changes of bid direction of the units of a GenCo to achieve the highest possible profit.
Distribution or transmission of electric power, Production of electric energy or power. Powerplants. Central stations
With the global surge in electric vehicle (EV) deployment, driven by enhanced environmental regulations and efforts to reduce transportation-related greenhouse gas emissions, managing the life cycle of Li-ion batteries becomes more critical than ever. A crucial step for battery reuse or recycling is the precise estimation of static capacity at retirement. Traditional methods are time-consuming, often taking several hours. To address this issue, a machine learning-based approach is introduced to estimate the static capacity of retired batteries rapidly and accurately. Partial discharge data at a 1 C rate over durations of 6, 3, and 1 min were analyzed using a machine learning algorithm that effectively handles temporally evolving data. The estimation performance of the methodology was evaluated using the mean absolute error (MAE), mean squared error (MSE), and root mean squared error (RMSE). The results showed reliable and fairly accurate estimation performance, even with data from shorter partial discharge durations. For the one-minute discharge data, the maximum RMSE was 2.525%, the minimum was 1.239%, and the average error was 1.661%. These findings indicate the successful implementation of rapidly assessing the static capacity of EV batteries with minimal error, potentially revitalizing the retired battery recycling industry.
Production of electric energy or power. Powerplants. Central stations, Industrial electrochemistry
Ting-Ting Duan, Sahanaa Büriechin, Hai-Ling Lao
et al.
In this minireview article, we examine the inconsistent results of thermal parameters derived from various models in high-energy collisions. Through a comprehensive literature review and based on the average transverse momentum or the root-mean-square transverse momentum, we propose model-independent parameters to address these inconsistencies. The relevant parameters include: the initial temperature, the effective temperature, the kinetic freeze-out temperature, and the average transverse velocity. Our findings indicate that these four parameters are larger in central collisions, within central rapidity regions, at higher energies, and in larger collision systems. As collision energy increases, excitation functions for all four parameters rise rapidly (slowly) within ranges below (above) approximately 7.7 GeV. At higher energies (>39) GeV, fluctuations occur in trends for these excitation functions, with only slight changes observed in their growth rates. Additionally, this work reveals a mass-dependent multi-temperature scenario pertaining to both initial states and kinetic freeze-out processes.