Research on the Integrated Development Mode of Pastoral Agriculture

As an emerging thing different from traditional agriculture, the pastoral complex covers a wide range. This paper mainly designs the agricultural landscape under the concept of the pastoral complex to create a more attractive park, attract more tourists to travel and consume here, develop the local economy, improve local income, and promote the implementation of the rural revitalization strategy in the local area. This paper combines theory with practice, broadens the application methods and theoretical framework of the design of rural complexes, has specific reference value for the research of the design of rural complexes, is conducive to the construction of rural landscapes and the protection of rural ecology, arouses people’s re-examination of the construction of rural landscape, and has specific theoretical and practical significance for the development of rural landscape and the implementation of rural revitalization strategy

Ultra-short-term power load forecasting method based on stochastic configuration networks and empirical mode decomposition

Ultra-short-term power load forecasting (USTPLF) can provide strong support and guarantee the decisions on unit start-up, shutdown, and power adjustment. The ultra-short-term power load (USTPL) has strong non-smoothness and nonlinearity, and the time-series characteristics of the load data themselves are difficult to explore. Therefore, to fully exploit the intrinsic features of the USTPL, a stochastic configuration networks (SCNs) USTPLF method based on K-means clustering (K-means) and empirical mode decomposition (EMD) is proposed. First, the load data are decomposed into several intrinsic mode functions (i.e., IMFs) and residuals (i.e., Res) by EMD. Second, the IMFs are classified by K-means, and the IMF components of the same class are summed. Third, the SCNs is used to forecast the electric load on the basis of the classified data. Lastly, on the basis of the real load of Shenzhen City, the proposed method is applied for emulation authentication. The result verifies the efficiency of the proposed measure

Virtual Inertia Adaptive Control of a Doubly Fed Induction Generator (DFIG) Wind Power System with Hydrogen Energy Storage

This paper presents a doubly fed induction generator (DFIG) wind power system with hydrogen energy storage, with a focus on its virtual inertia adaptive control. Conventionally, a synchronous generator has a large inertia from its rotating rotor, and thus its kinetic energy can be used to damp out fluctuations from the grid. However, DFIGs do not provide such a mechanism as their rotor is disconnected with the power grid, owing to the use of back-to-back power converters between the two. In this paper, a hydrogen energy storage system is utilized to provide a virtual inertia so as to dampen the disturbances and support the grid’s stability. An analytical model is developed based on experimental data and test results show that: (1) the proposed method is effective in supporting the grid frequency; (2) the maximum power point tracking is achieved by implementing this proposed system; and, (3) the DFIG efficiency is improved. The developed system is technically viable and can be applied to medium and large wind power systems. The hydrogen energy storage is a clean and environmental-friendly technology, and can increase the renewable energy penetration in the power network

Effect of carbon-coated Al2O3 powder on structure and properties of low-carbon MgO-C refractory composites

In this study, low-carbon MgO-C refractory composites with addition of uncoated (UA) and carbon-coated Al2O3 (CCA) powders were prepared. The effect of heat-treatment temperature on apparent porosity, cold modulus of rupture and thermal expansion was investigated. The results indicated that the CCA was present in the form of porous agglomerates of 400–800 µm in diameter in MgO-C matrix. The formation of spinel started at 1100 °C and 1250 °C in UA-MgO-C and CCA-MgO-C specimens, respectively. In the specimen CCA-MgOC, cyclic spinel was formed on the outer layer of CCA agglomerates, and the dense spinel layer hindered the diffusion of Mg(g) to the interior of the agglomerates, resulting in alumina residues at 1550 °C. The specimen CCA-MgO-C showed better mechanical properties and reduced porosity. Additionally, the average coefficient of thermal expansion of CCA-MgO-C was significantly lower than that of UA-MgO-C. Thus, CCA powder could improve the volume stability of the low-carbon MgO-C refractory composites

Autonomous Trajectory Planning by Convex Optimization

The objective of this dissertation is to use second-order cone programming (SOCP) for autonomous trajectory planning of optimal control problems arisen from aerospace applications. Rendezvous and proximity operations (RPO) of spacecraft in any general orbit include various constraints on acquisition of docking axis point, approach corridor, plume impingement inhibition, relative velocity, and rate of change of thrust. By a lossless relaxation technique, this highly constrained RPO problem (non-convex) is transformed into a relaxed problem the solution of which is proven to be the same as that of the original problem. Then a novel successive approximation method, forming a sequence of subproblems with linear and time-varying dynamics, is applied to solve the relaxed problem. Each subproblem is a SOCP problem which can be solved by state-of-the-art primal-dual interior point method. Constraints on collision avoidance, or more generally concave inequality state constraints, from any aerospace application also make a problem non-convex. A successive linearization method is employed to linearize the concave inequality constraints. It is proven that the successive solutions from this method globally converge to the solution of the original problem and the converged solution has no conservativeness. Further non-convex constraints include nonlinear terminal constraints which are handled by first approximated with first-order expansions, and then compensated with second-order corrections to improve the robustness of the approach. The effectiveness of the methodology proposed in this dissertation is supported by various applications in highly constrained RPO, finite-thrust orbital transfers, and optimal launch ascent.</p

A Modern Approach to Analyzing the Flowing Pressures of a Two-Phase CBM and Water Column in Producing Wellbores

A modern methodology is presented for the system analysis of flowing pressures in order to forecast the dynamic behavior and solve the forthcoming problems that emerge in two-phase coalbed methane (CBM) wellbores. The proposed methodology involves a numerical integration technique to calculate flowing pressures and pressure drops of CBM and water flow from the bottom hole to the well head. The methodology is validated against full-scale measured data in coalfields. The relationships developed match CBM reservoir behavior and wellbore conditions along the annulus with an overall accuracy of 1.13%. The computation of flowing pressures involves a liquid holdup and kinetic energy term with flow rate increments, a compressibility factor with depth increments, and a friction factor with Reynolds number. The flowing pressures of a two-phase column fully reflect the dynamic flowing performance due to the combined action of the water level, CBM, and water flow rates. The effect of CBM and water column pressures is more obvious than that of CBM column pressures. The pressure ratios of CBM and the water column to the bottom hole decline rapidly with the increase of the dynamic water level. CBM and water flow rates can be improved with increases in CBM and water column pressure for two-phase producing wellbores. The decrease of flowing pressures and increased increment of the pressure drop for the two-phase column are beneficial to CBM desorption and result in the increased CBM and water production. It will control the falling speed of the dynamic water level above CBM and the water column and enhance CBM reservoir productivity. The increases of CBM and water column pressure from 34.6 kPa to 922 kPa and the decreases of pressure in the bottom hole from 2.252 MPa to 1.328 MPa lead to the increases of the CBM flow rate from 3327 m3/d to 6721 m3/d