Search

To avoid possible conflicts between the maintenance scheduling and the unit commitment for hydro-thermal power systems under the traditional non-collaborative optimization mode,a collaborative maintenance scheduling and unit commitment model for hydro-thermal systems is proposed,in which the total cost of the system and the adjustment cost of maintenance scheduling as an objective are minimized with considering the coupling characteristics of cascade hydropower. Furthermore,the model is transformed into a mixed integer linear programming (MILP) model. To improve the solution of the MILP model,the objective scaling ensemble approach is proposed,including two stages. In the first stage,the coefficients of integer variables in the objective are scaled and the integer variables that may take 0 are probed. In the second stage,the reduced MILP model is solved after determining and fixing the integer variables with a value of 0. Finally,a 6-unit hydro-thermal power system and an actual provincial 86-unit hydro-thermal power system are taken as test systems. The results show that the proposed model can obtain a more economical and reasonable maintenance scheduling and unit commitment scheme compared with the non-collaborative optimization mode,thus effectively improving the solution speed by the objective scaling ensemble approach.

[Introduction] Aiming at allocating renewable energy consumption responsibility weight problem among market subjects, an allocation method based on evolutionary game and stochastic optimization is proposed. [Method] First of all, each market subject was taken as a limited rational individual participate in the weakly linked evolutionary game, and the absorption weight undertaking scheme that minimizes its own cost in the evolutionary equilibriumwas obtained and the selection strategy tendency of each market subject under the probability interval of different rewards and punishments adopted by the government was obtained. Then, after getting the probability interval of different reward and punishment measures taken by the government, a stochastic optimization model was used to get the specific scheme of absorbing weight which couldminimize the cost of each subject in each probability interval. [Result] The effectiveness and practicability of the proposed method is verified by calculating the data of 170 market entities in a provincial power grid. [Conclusion] A new method and idea on the weight distribution method of renewable energy absorption responsibility is provided, and feasible suggestions for the government to strengthen the enthusiasm of market subjects in the absorption of renewable energyare put forward in this paper.

Building height is important information in disaster management and damage assessment. It is also a key parameter in studies such as population modeling and urbanization. Relatively few studies have been conducted on extracting building height in rural areas using imagery from China's Gaofen-7 satellite (GF-7). In this study, we developed a method combining photogrammetry and deep learning to extract building height using GF-7 data in the rural area of Pingquan in northern China. The deep learning model DELaMa was proposed for digital surface model (DSM) editing based on the Large Mask Inpainting (LaMa) architecture. It not only preserves topographic details but also reasonably predicts the topography inside the building mask. The percentile value of the normalized digital surface model (nDSM) in the building footprint was taken as the building height. The extracted building heights in the study area are highly consistent with the reference building heights measured from the ICESat-2 LiDAR point cloud, with an R2 of 0.83, an MAE of 1.81 m and an RMSE of 2.13 m for all validation buildings. Overall, the proposed method in this paper helps to promote the use of satellite data in large-scale building height surveys, especially in rural areas. [ABSTRACT FROM AUTHOR]

Maglev vehicles apply the entire vehicle load uniformly onto bridges through levitation forces. In assessing the dynamic characteristics of the maglev train–bridge coupling system, it is reasonable to simplify the distributed levitation force as a concentrated force. This article theoretically derives the analytical response of bridge dynamics under the action of a single constant force and conducts numerical simulations for a moving single constant force and a series of equally spaced constant forces passing over simply supported beams and two-span continuous beams, respectively. The topic of discussion is the response of bridge dynamics when different degrees of force concentration are involved. High-precision displacement and acceleration sensors were utilized to conduct tests on the Shanghai maglev line to verify the accuracy of the simulation results. The results indicate that when simplifying the distributed levitation force into a concentrated force model, a frequency ratio can be used to analyze the conditions for resonance between the train and the bridge and to calculate the critical speed of the train; the levitation distribution force of a high-speed maglev vehicle can be simplified into four groups of concentrated forces based on the number of levitation frames to achieve sufficient accuracy, with the dynamic response of the bridge being close to that under distributed loads. [ABSTRACT FROM AUTHOR]