Airflow field and effective region for pollution discharge were predicted around a circular flanged exhaust opening, three different turbulent models were employed to simulate airflow field near the exhaust opening in...
Airflow field and effective region for pollution discharge were predicted around a circular flanged exhaust opening, three different turbulent models were employed to simulate airflow field near the exhaust opening indoor. Numerical results show that air velocity decreases gradually in radial direction and axis direction away from origin, and changes most dramatically at corner of the opening. The projection of velocity contour is similar to a semi-ellipse, but when the air velocity decreases, it gradually changes the hemisphere with larger outer radius. When the velocity is 2 m/s, the long axis of the semi-ellipse is 0.70 times the diameter of the exhaust port and the short axis is 0.45 times the diameter of the exhaust port. When the velocity is 0.3m/s, the diameter of the outlet is 1.60 times of that of the long axis and 1.55 times of that of the short axis. The effective area of pollutant emission is similar to the equivalent surface with velocity of 0.3m/s, and its shape is semi-elliptic.
With the development of distributed generation technology and the requirement of power system flexibility, the research on multiple flexible resource optimization is carried out. Based on the traditional optimal confi...
With the development of distributed generation technology and the requirement of power system flexibility, the research on multiple flexible resource optimization is carried out. Based on the traditional optimal configuration of wind-solar-hydro-storage system, this paper takes electric vehicle into consideration. Firstly, the model of each flexible resource is established. Then, a comprehensive evaluation index system is built. Taking the flexible resources in a city on the eastern coast of China as a case, multi-objective grey wolf optimization algorithm and entropy weight method are applied to do the optimization and evaluation. The simulation result shows that in the optimal configuration, not only the renewable resources can be effectively utilized, but also the requirement of load in different period can be meet. Moreover, the total investment can be greatly reduced. In addition, the participation of electric vehicles can not only improve the performance of the hybrid system, but also increase the income of EV holders.
The operation of the power grid will be affected inevitably with the increasing scale of wind farm due to the inherent randomness and uncertainty, so the accurate wind speed forecasting is critical for the stability o...
The operation of the power grid will be affected inevitably with the increasing scale of wind farm due to the inherent randomness and uncertainty, so the accurate wind speed forecasting is critical for the stability of the grid operation. Typically, the traditional forecasting method does not take into account the frequency characteristics of wind speed, which cannot reflect the nature of the wind speed signal changes result from the low generality ability of the model structure. AdaBoost neural network in combination with the multi-resolution and multi-scale decomposition of wind speed is proposed to design the model structure in order to improve the forecasting accuracy and generality ability. The experimental evaluation using the data from a real wind farm in Jiangsu province is given to demonstrate the proposed strategy can improve the robust and accuracy of the forecasted variable.
For Double-Fed Induction Generator (DFIG) wind farm systems with Static Synchronous Compensator (STATCOM), by optimizing multiple proportional integral (PI) controllers parameters of DFIG and STATCOM, the performance ...
For Double-Fed Induction Generator (DFIG) wind farm systems with Static Synchronous Compensator (STATCOM), by optimizing multiple proportional integral (PI) controllers parameters of DFIG and STATCOM, the performance of the wind power system is significantly improved and the voltage of point of common coupling (PCC) is quickly restored when a low voltage due to a grid fault. Chaos orthogonal particle swarm optimization is proposed to make the integral time absolute error (ITAE) of active power of DFIG, DC-link voltage of converter of DFIG and voltage of PCC minimum. The orthogonal method is used to get the range of parameters and identify the weight relations between different indicators. And then the chaos algorithm is used to initialize the algorithm. Finally, the particle swarm optimization (PSO) can effectively improve the efficiency of the optimization. Based on MATLAB/Simulink, the simulations of wind farm containing STATCOM incorporated into the infinite system under different conditions both show that the application optimized PI controllers have good dynamic performance, which validates the effectiveness of the optimization algorithm.
A microgrid system in the stand-alone mode with photovoltaic, wind turbine, microturbine, fuel cell and energy storage unit is studied. Mathematical models of different distributed power supply and energy storage devi...
A microgrid system in the stand-alone mode with photovoltaic, wind turbine, microturbine, fuel cell and energy storage unit is studied. Mathematical models of different distributed power supply and energy storage devices are established. The load demand of the system, the price of purchasing and selling electricity when interacting with the power grid and other constraints are considered. An economic model for optimizing stand-alone operation cost is established. According to the characteristics of the model, an improved genetic algorithm is selected to optimize the nonlinear system. The algorithm has better stability in solving the optimization problem of large state space dimension. The case study show that the proposed economic model is reasonable and the algorithm is effective.
Nowadays, the demand for energy is expanding, the fossil resources are on the verge of exhaustion, and the ecological environment is getting worse and worse. In this form, this paper studies the economic optimal dispa...
Nowadays, the demand for energy is expanding, the fossil resources are on the verge of exhaustion, and the ecological environment is getting worse and worse. In this form, this paper studies the economic optimal dispatch of microgrid under the background of energy saving and emission reduction. Firstly, the mathematical model of microgrid composed of distributed power, energy storage devices and loads is established. Secondly, under the background of energy saving and emission reduction, the objective function of multi-objective optimal operation of microgrid is established considering both economic and environmental aspects. Finally, the improved Genetic Algorithm is used to solve the objective function. The results of optimization can reduce microgrid system generation cost.
Water jet flow characteristics in double-side wall confined space is investigated, two-dimensional particle image velocimetry is performed on confined plane and unconfined plane, and using Proper orthogonal decomposit...
Water jet flow characteristics in double-side wall confined space is investigated, two-dimensional particle image velocimetry is performed on confined plane and unconfined plane, and using Proper orthogonal decomposition to perform dimensionality analysis, extract large-scale coherent structure and reconstruct flow field. Results illustrate that velocity and vorticity fluctuation distribution, mainly reflected in low-order modes, is seriously affected on account of a symmetrical double-wall existence; Reconstruction instantaneous velocity field by the first m modes saving 70% of turbulent kinetic energy, indicating that reconstructed velocity fluctuation fields can truly reflect original fields.
With the continuous development of electric vehicle charging facilities, the impact of electric vehicles on the power grid is growing. Considering the automatic demand response technology of smart grid, charging pile ...
With the continuous development of electric vehicle charging facilities, the impact of electric vehicles on the power grid is growing. Considering the automatic demand response technology of smart grid, charging pile operators participate in the demand response plan and guide users to charge according to the price signal or incentive mechanism, which can ensure the safety of the power grid and reduce the negative effects of electric vehicles on the grid influence. Based on the theory of demand side response elasticity, this paper analyzes the whole process of electric vehicle users' participation in demand response and its influencing factors, classifies electric vehicle users based on demand response, and then quantitatively analyzes users' demand response from the perspective of electricity price elasticity and consumption psychology. Finally, the demand side response model with user participation is established. The application of the model can effectively improve the enthusiasm of electric vehicle users to participate in demand side response, and reduce the negative impact of electric vehicles on the power grid.
In article numberhttps://***/10.1002/advs.201901371, Jun Zou and co‐workers employ origami structure to design vacuum‐powered silicone rubber artificial muscles, which can perform multiple motions. Artificial muscle...
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In article number
https://***/10.1002/advs.201901371
, Jun Zou and co‐workers employ origami structure to design vacuum‐powered silicone rubber artificial muscles, which can perform multiple motions. Artificial muscles can be used for rapid reconfiguration of different soft robots, just like “building bricks.” The robots allow simpler, less expensive, modular units to be reconfigured into a group depending on the task that needs to be completed.
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