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Regarding stochastic disturbance in power system brought by grid-connected distributed generation(DG), generally considering operational effectiveness, aiming at economy, power quality and environmental efficiency, the optimization model of stochastic chance-constrained programming is built, while using hybrid intelligent algorithm, which simulates the uncertainty functions based on support vector machine(SVM) and solves the model by multi-objective particle swarm optimization (MOPSO), then the Pareto noninferior decision set is obtained. Simulation results show that the planning model can fully take into account randomness, grid-connected probability distribution of DG, and improve the efficiency of the algorithm, then verify the rationality and validity of the proposed approach. Moreover, the introduction of Pareto front gives fully choices to operators and possesses more engineering value.

As one of the significant measures to realize energy transition, the proportion of new energy in energy supply side becomes increasingly high. However, the fluctuation and randomness of new energy output bring great challenges to the conventional generation expansion planning (GEP). Under the framework of combining investment decision and operation analysis, a novel GEP method for integrating large-scale new energy generation was proposed, which mainly includes: adopting a monthly time resolution in investment decision-making stage to consider the seasonal fluctuation and rapid construction characteristic of new energy; adding an ultra-short-term operation model to operation analysis stage, which can be used to evaluate the system adjustment capacity during typical periods with sharp changes of net load (such as morning peak period and evening sunset period) and reflect the value of flexible resources in line with the operation of new energy; furthermore, through the coordinated iteration and rolling correction between investment decision and multi-time scale operation assessment, the optimized planning scheme with comprehensive benefits of economy, environment, reliability and flexibility was obtained. Finally, to provide a reference for future research, the key problems that can be further studied are discussed.

Abstract Theoretical and experimental investigations to date have assumed that bridge stay cables can be modelled as ideal circular cylinders and that their aerodynamic coefficients are invariant with wind angle-of-attack. On the other hand it has been demonstrated that bridge cables are characterised by local alterations of their inherent surface roughness and shape. Small deviations from ideal circularity result in significant changes in the static drag and lift coefficients with Reynolds number. The present study focuses on the wind-induced response of a full-scale yawed bridge cable section model, for varying Reynolds numbers and wind angles-of-attack. Using passive-dynamic wind tunnel tests, it is shown that the in-plane aerodynamic damping of a bridge cable section, and the overall dynamic response, is strongly affected by changes in the wind angle-of-attack. Using the drag and lift coefficients, determined in static conditions for an identical cable model as the one used for passive-dynamic tests, the in-plane aerodynamic damping is evaluated by employing a one-degree-of-freedom (1 DOF) quasi-steady analytical model. Similarly, it is shown that regions of instability associated with the occurrence of negative aerodynamic damping are strongly dependent on the wind angle-of-attack.

This article establishes a new family of methods to perform temperature interpolation of nuclear interactions cross sections, reaction rates, or cross sections times the energy. One of these quantities at temperature T is approximated as a linear combination of quantities at reference temperatures (Tj). The problem is formalized in a cross section independent fashion by considering the kernels of the different operators that convert cross section related quantities from a temperature T0 to a higher temperature T namely the Doppler broadening operation. Doppler broadening interpolation of nuclear cross sections is thus here performed by reconstructing the kernel of the operation at a given temperature T by means of linear combination of kernels at reference temperatures (Tj). The choice of the L2 metric yields optimal linear interpolation coefficients in the form of the solutions of a linear algebraic system inversion. The optimization of the choice of reference temperatures (Tj) is then undertaken so as to best reconstruct, in the L sense, the kernels over a given temperature range [Tmin,Tmax]. The performance of these kernel reconstruction methods is then assessed in light of previous temperature interpolation methods by testing them upon isotope 238U. Temperature-optimized free Doppler kernel reconstruction significantly outperforms all previous interpolation-based methods, achieving 0.1% relative error on temperature interpolation of 238U total cross section over the temperature range [300K,3000K] with only 9 reference temperatures. Developed cross section independent methods to perform temperature interpolation as L2 kernel reconstruction optimization problems.A cross section is approximated as a linear combination of reference temperatures cross sections.L2 norm is physically justified, yielding formulae for optimal interpolation coefficients.Optimal reference temperature grids are developed.Kernel reconstruction significantly outperforms previous temperature interpolation methods.

The weighted sum of gray gases (WSGG) method has been used extensively for radiation modeling of non gray medium gases. The radiative transfer equation (RTE) for each gray gas can be solved using the Discrete Ordinate (DO) model, which is sufficiently accurate over wide range of optical thickness, but it is computationally expensive. The P1 approximation is an efficient alternative to solve the RTE, but applicable to optically thick medium only. In the present work, a hybrid solution methodology to solve RTE in a non gray medium using WSGG model is proposed. Results for the case of four gray gases are presented. The philosophy is to achieve the optimum performance using combination of the P1 and DO model with respect to the optical thickness of the gray gases being solved with minimal loss in accuracy. In this approach, the transparent and/or optically thin gases are solved using the DO model while the P1 approximation is used for the optically thick gases. This combination reduces the total number of radiation intensity equation to be solved very significantly. A study of accuracy and computational cost for the hybrid solution methodology has been done for a variety of test cases in order of increasing complexity. It has been found that the hybrid solution methodology, in which RTE for two gray gases are solved by DO model and the remaining two gray gases by P1 approximation, provided similar accuracy with significant speedup compared to the conventional approach in which RTE for all gray gases are solved with DO model. Another variant of the hybrid approach, in which DO model is used only for the transparent gas, is also considered and found to be sufficiently accurate for most of the cases.

Due to the uncertainty and fluctuation of distributed generation (DG) and load, the operation of active distribution network (ADN) is affected by multi-dimension factors which are described by massive operation scenarios. Efficient and accurate screening of severely restricted scenarios (SRSs) has become a new challenge in ADN planning. In this paper, a novel bi-level coordinated planning model which combines the short-time-scale operation problem with the long-time-scale planning problem is proposed. At the upper level, the demand response (DR) resource, an effective non-component planning resource characterized by low capacity price, high energy price, and short contract term, is co-optimized with the configuration of lines and energy storage systems (ESSs) to achieve the economic trade-off between the investment cost and the operation cost under SRSs. At the lower level, with the planning scheme obtained from the upper level, massive operation problems are optimized to minimize the daily operation cost; and the SRSs are provided to the upper level through a shadow-price-based scenario screening method, which simulates the planning information (i.e., the restricted degrees of operation scenarios) feedback process from ADN operators to ADN planners. Case studies on a 62-node distribution system in Jianshan New District, Zhejiang Province, China, illustrate the effectiveness of the proposed bi-level coordinated planning model considering DR resources and SRSs.

This paper presents Gravitational search algorithm (GSA) optimization techniques for the optimal location of Flexible AC Transmission System (FACTS) devices in the power system network to attain minimum transmission active power loss, the optimal value of control variables, and optimal bus voltage. These proposed methods are legitimate in the IEEE-30 test bus system. Here, the proposed GSA algorithm is adapted for minimization of active power losses and it is also improving bus voltage. After using facts devices, from the obtained results power system loadability improved within range and at different loading condition in the power system networks all generators capable to dispatch a significant amount of active power. By incorporating facts devices, we proposed active power loss reduced and also maintained the bus voltage of the power system network at different loading condition. Hence, for Loadability enhancement in the power system, this gives a better optimal solution.