Hasil untuk "Production of electric energy or power. Powerplants. Central stations"

Yangyang Lu, Hongjing Ma, Jie Ren et al.

Fatih Çakıl, Necati Aksoy

Amal C. Sunny, Kashem M. Muttaqi, Danny Sutanto

Yuan Zhao, Jiaqin Hu, Kaigui Xie et al.

The reliability evaluation of composite generation and transmission systems (CSRE) is essential for power system planning and operation but often faces significant computational challenges. To accelerate CSRE, the Gaussian mixture model (GMM), known for its ability to model arbitrary probability densities, has been incorporated into the Cross-Entropy Method (CEM) to estimate the importance sampling probability density function (IS-PDF) of continuous random variables, such as correlated wind speeds and system load. However, the classical CEM produces a non-closed-form solution for the GMM-based IS-PDF, resulting in an alternating parameter updating procedure for the GMM parameter set and larger pre-simulation cost. To address this issue and enhance the simulation speed of CEM-based CSRE, an improved CEM with a highly efficient closed-form parameter updating mechanism is proposed. By developing an equivalent variant of the GMM that belongs to the exponential family, a closed-form solution is derived, eliminating the need for alternating updates. The improved CEM achieves higher efficiency and simplifies the modeling of the GMM-based IS-PDF. Numerical tests are conducted to validate the performance and advantages of the proposed method.

Feixiang Peng, Wanghao Wu, Duanchao Li et al.

With the rapid development of new power systems and electric vehicles (EVs), the mismatch between renewable energy generation and power load is increasing seriously. An appropriate charging strategy for EVs can alleviate the load fluctuation in the power system. In practice, the feasibility of dispatching results is highly related to the EVs’ willingness. However, the willingness factor, reflecting the behavior preference of end users, is hard to build. In this paper, a charging dispatching strategy for EVs considering user willingness and status quo bias (SQB) is proposed to optimize the charging behavior and improve the operational efficiency of the power grid. A user willingness response model is proposed, considering the impact of charging prices and state of charge (SOC). The charging willingness and SQB are used to build user charging satisfaction, reflecting users’ needs and preferences more accurately. Load regulation and renewable energy curtailment are considered in grid dispatching satisfaction building. Thus, a multi-objective optimization model can be established to balance user charging and grid dispatching satisfaction. The results indicate that the proposed dispatching strategy, considering user willingness and SQB, improves user charging satisfaction, optimizes the load dispatching of the grid, and reduces operating costs.

Qian Chen, Jie Su, Xiaojun Bian et al.

The detection and cultivation of circulating tumor cells (CTCs) play a crucial role in monitoring tumor recurrence, metastasis, early disease diagnosis, and assessing the effectiveness of drug treatments. This study specifically focused on investigating human breast cancer cells MCF-7 by utilizing framework nucleic acids (FNAs) as bio-probe scaffold in conjunction with fishbone structures and three-dimensional (3D) microcavity structures within microchannels. These components collectively formed an integrated nano-micro interface system designed for a comprehensive examination of CTC detection and cell culture. The study involved the assessment and comparison of rigid 3D FNAs with distinct side lengths of 7, 13, and 26 bases. This approach not only allowed for precise regulation of the DNA biosensor interface through the manipulation of probe spacing, facilitating optimal probe-cell interactions within the microfluidic channel. Consequently, this approach significantly enhances capture efficiency and lowers the CTC detection limit to 5 cells/mL. Moreover, this research successfully observed cell proliferation and individual cell biological behavior within the 3D microcavity structure. The findings indicated that the overall cell population's proliferation was like that in static culture conditions. Although the proliferation cycle of individual cells was notably extended, cell mobility within the microcavity demonstrated their robust biological activity. These significant outcomes not only offer a practical approach for early tumor detection but also provide a valuable pathway for comprehending mechanisms of tumor development and advancement and guiding personalized treatment strategies effectively.

Wenlong Liao, Jiannong Fang, Birgitte Bak-Jensen et al.

Machine learning models (e.g., neural networks) achieve high accuracy in wind power forecasting, but they are usually regarded as black boxes that lack interpretability. To address this issue, the paper proposes a glass-box model that combines high accuracy with transparency for wind power forecasting. Specifically, the core is to sum up the feature effects by constructing shape functions, which effectively map the intricate non-linear relationships between wind power output and input features. Furthermore, the forecasting model is enriched by incorporating interaction terms that adeptly capture interdependencies and synergies among the input features. The additive nature of the proposed glass-box model ensures its interpretability. Simulation results show that the proposed glass-box model effectively interprets the results of wind power forecasting from both global and instance perspectives. Besides, it outperforms most benchmark models and exhibits comparable performance to the best-performing neural networks. This dual strength of transparency and high accuracy positions the proposed glass-box model as a compelling choice for reliable wind power forecasting.

Wanxin Feng, Yong Yang, Kaixin Wu et al.

Zuhair Abdalmenem, Ahmed M. Benaya, Eiman ElGhanam et al.

Jingbo Wang, Harshal D. Kaushik, Jie Zhang

Валерій Станіславович Ноздренков, Михайло Васильович Петровський, Віталій Васильович Волохін et al.

В умовах постійного розвитку розподілених джерел електроенергії з’явилась необхідність інтегрування їх у загальну електромережу. Але процес інтегрування повинен враховувати не тільки параметри керування розподіленим джерелом живлення, а й враховувати паралельну роботу декількох таких джерел та параметри енергосистеми у цілому. На самому високому рівні керування потрібно також враховувати економічні показники, які формуються енергоринком. Для здійснення інтегрування можуть ефективно використовуватися спеціальні прилади – керовані інвертори. Найбільш складною задачею є вибір системи управління для керованих інверторів. Існує багато різноманітних систем управління, наприклад, пропорційно-інтегральні, Deadbeat регулятори тощо. Метою даної роботи є побудова інформаційної моделі управління розподіленими джерелами живлення. Для контролю активної та реактивної потужності використовується метод контролю за струмом. Перевагою контролю за струмом є стійкість до варіації параметрів інвертора та зовнішньої мережі, відмінні динамічні показники та більша точність контролю. Запропонований варіант побудови системи автоматичного керування використовує стратегію Internal model control та враховує обмеження на керуючу змінну. Перевагами системи з Internal model control регулятором у порівнянні зі звичним пропорційно-інтегральним регулятором є використання потужного методу керування на основі моделі об’єкту, можливість впливати на нечутливість системи окремим параметром налаштувань, підвищена швидкодія при майже повній відсутності перерегулювання, полегшена процедура налаштування. Така система пропонується для використання в об’єктах, де висуваються жорсткі вимоги до мінімізації перерегулювання та швидкості відпрацювання збурень і завдань. Для моделювання результатів роботи використано програмний комплекс PSCAD.

Wenting Wang, Aimin An

Accurate and real-time identification of market power abuse is a key task in the management of electricity market violations. However, there are few effective monitoring methods for extremely imbalanced datasets and progressively increasing amounts of data in actual market transactions. To address the aforementioned problems, this paper proposes an improved support vector machine by considering the index system, which can not only realize identification automatically but also minimize the credit risk of power market transactions. Firstly, the dataset is composed of an indicator system for measuring market power abuses. Secondly, a comprehensive algorithm for identifying offending data is proposed, which combines the K-Nearest Bound Neighbor and the distance between the means of two classes methods to overcome the shortcomings of traditional support vector machines with long training time due to the high dimensionality and progressively increasing amounts of data in actual market transactions, and the Cost-sensitive Support Vector Machine to tackle the problem of inefficient identification due to few tags in transaction data. Finally, five different features of constructed datasets and a power market synthetic dataset are tested, and results indicate that the proposed method can ensure high classification accuracy while significantly improving recognition speed and recall for violation data, which is more suitable for Chinese electricity market data and provide a dynamic detection method to identify market power abuse precisely and quickly.

Mohd Rizwan Khalid, Al Hamd Khan, Ahmad Hamdan et al.

Siyuan Zheng, Longdong Wu, Yeyun Xiang et al.

Xuecheng Chen, Rudolf Holze

Wetting the surface area of an electrode material as completely as possible is desirable to achieve optimum specific capacity of an electrode material. Keeping this surface area utilized even at high current densities and even when inside pores is required for high capacitance retention. The addition of surfactants at very small concentrations to aqueous supercapacitor electrolyte solutions has been suggested as a way to improve performance in terms of capacitance, capacitance retention at increased current density and stability. Effects are pronounced with carbon materials used in electrochemical double-layer capacitors; they are also observed with redox materials. The causes of the observed improvements and mode of operation of the added surfactants seem to need further investigation; they are inconclusive beyond the obvious statement of increased wetting. Reported examples and the current state of understanding are reviewed.

Alexandrea Washington, Ji Su, Kwang J. Kim

Electroactive polymer (EAP) actuators are an example of a novel soft material device that can be used for several applications including artificial muscles and lenses. The field of EAPs can be broken down into a few fields; however, the field that will be discussed in this study is that of Soft Electrohydraulic (SEH or EH) actuators. The device that will specifically be studied is the Hydraulically Amplified Self-Healing Electrostatic (HASEL) actuator. The design of the HASEL actuator is simple. There are two compliant films that house a dielectric liquid, and with the application of a voltage potential, there is an output displacement and force. However, the actuation mechanism is more complex, thus there is a need to understand theoretically and experimentally how the actuator works. This study analytically describes the electrode closure and the experimental testing of the actuators. Then, dimensional analysis techniques are used to determine what factors are contributing to the function of the actuator. For this study, eight dimensionless Π groups were found based on the derived analytical equation. These Π groups were determined based on the input voltage, density, viscosity, and elastic modulus of the materials; these were chosen because of their major contribution to the experimental data. The Π groups that are of particular importance are related to the characteristic length, which is directly related to the displacement of the fluid, the fluid velocity, the fluid pressure, and the dielectric constant. From this study, relationships between the output force, the electrostatic contributions, and other parameters were determined. All in all, this type of analysis can provide guidance on the development of high-performance HASEL actuators.

Hanyu Yang, Canbing Li, Ruanming Huang et al.

Increasing intermittent renewable energy sources (RESs) intensifies the imbalance between demand and generation, entailing the diversification of the deployment of electrical energy storage systems (ESSs). A large-scale biogas plant (LBP) installed with heating devices and biogas energy storage (BES) usually exhibits a storage-like characteristic of accommodating an increasing penetration level of RES in rural areas, which is addressed in this paper. By utilizing the temperature-sensitive characteristic of anaerobic digestion that enables the LBP to exhibit a storage-like characteristic, this paper proposes a bi-level energy trading model incorporating LBP and demand response aggregator (DRA) simultaneously. In this model, social welfare is maximized at the upper level while the profit of DRA is maximized at the lower level. Compared with cases only with DRA, the results show that the proposed model with the LBP improves the on-site accommodation capacity of photovoltaic (PV) generation up to 6.3%, 18.1%, and 18.9% at 30%, 40%, and 50% PV penetration levels, respectively, with a better economic performance. This nonlinear bi-level problem is finally recast by a single-level mathematical program with equilibrium constraints (MPEC) using Karush-Kuhn-Tucker (KKT) conditions and solved by the Cplex solver. The effectiveness of the proposed model is validated using a 33-bus test system and a sensitivity analysis is provided for analyzing what parameter influences the accommodation capacity most.

Gui Zhao, Xing He, Guo Chen et al.

Xin Jiang, Lantian Zhao, Yu Cheng et al.

Levent Ögretmen, Matthias Rowold, Marvin Ochsenius et al.

In motion planning for autonomous racing, the challenge arises in planning smooth trajectories close to the handling limits of the vehicle with a sufficient planning horizon. Graph-based trajectory planning methods can find the global discrete-optimal solution, but they suffer from the curse of dimensionality. Therefore, to achieve low computation times despite a long planning horizon, coarse discretization and simple edges that are efficient to generate must be used. However, the resulting rough trajectories cannot reach the handling limits of the vehicle and are also difficult to track by the controller, which can lead to unstable driving behavior. In this paper, we show that the initial edges connecting the vehicle’s estimated state with the actual graph are crucial for vehicle stability and race performance. We therefore propose a sampling-based approach that relies on jerk-optimal curves to generate these initial edges. The concept is introduced using a layer-based graph, but it can be applied to other graph structures as well. We describe the integration of the curves within the graph and the required adaptation to racing scenarios. Our approach enables stable driving at the handling limits and fully autonomous operation on the race track. While simulations show the comparison of our concept with an alternative approach based on uniform acceleration, we also present experimental results of a dynamic overtake with speeds up to 74 m/s on a full-size vehicle.