In association with the development of intermittent renewable energy generation (REG), dynamic multiobjective dispatch faces more challenges for power system operation due to significant REG uncertainty. To tackle the problems, a day‐ahead, optimal dispatch problem incorporating energy storage (ES) is formulated and solved based on a robust multiobjective optimization method. In the proposed model, dynamic multistage ES and generator dispatch patterns are optimized to reduce the cost and emissions. Specifically, strong constraints of the charging/discharging behaviors of the ES in the space‐time domain are considered to prolong its lifetime. Additionally, an adaptive robust model based on minimax multiobjective optimization is formulated to find optimal dispatch solutions adapted to uncertain REG changes. Moreover, an effective optimization algorithm, namely, the hybrid multiobjective Particle Swarm Optimization and Teaching Learning Based Optimization (PSO‐TLBO), is employed to seek an optimal Pareto front of the proposed dispatch model. This approach has been tested on power system integrated with wind power and ES. Numerical results reveal that the robust multiobjective dispatch model successfully meets the demands of obtaining solutions when wind power uncertainty is considered. Meanwhile, the comparison results demonstrate the competitive performance of the PSO‐TLBO method in solving the proposed dispatch problems.

In recent years, the performance of polluted suspension insulators operating in coastal foggy regions has attracted attention because of the occurrence of flashover. Surface wetting by salt fog accretion increases the surface conductivity and degrades the flashover performance of insulators. Normally, the effect of conductivity under fog condition and pre-contamination on the flashover of polluted insulators are analyzed separately. However, this does not reveal the flashover behavior in salt fog, which requires further research. This paper describes salt fog experiments with an AC test voltage conducted using polluted suspension insulators in a 110-kV power system. The electrical strength performance of sample insulators with salt fog treatments is analyzed, and the effects of salt deposit density (SDD) and the conductivity of fog water (CFW) on the flashover of three types of suspension insulators are studied. The concept of additional SDD is proposed to quantify analyze the effects of salt fog. The results show that there is less dependence on CFW at higher pollution levels than at lower pollution levels. That is, the effect of CFW on U50 can be neglected for SDD>0.15 mg/cm2, whereas CFW has a strong effect on U50 for SDD<0.15 mg/cm2. CFW has a greater influence on the critical flashover voltage of ceramic insulators than on that of silicone rubber insulator. A model for calculating the critical flashover voltage of insulators is proposed by considering the combined effect of CFW and pre-polluting SDD.

A new control strategy is proposed to suppress earthquake-induced vibrations on uncertain building structures. The control strategy embeds fuzzy logic in a fractional-order (FO) proportional derivative (FOPD) controller. A new improved FO particle swarm optimization (IFOPSO) algorithm is derived to adjust the initial parameters of the FOPD controller. An original fuzzy logic-FOPD (FFOPD) controller is then designed by combining the advantages of the fuzzy logic and FOPD control, to deal with large displacements on structures under earthquake excitation. Simulation experiments are carried out on uncertain building structures subjected to the effects of different kinds of seismic signals, illustrating the validity and feasibility of the proposed method.

The phenomenon of transformer dc bias (TDB) will saturate the transformer core, resulting in the local overheating, accelerating the ageing of insulating material, and even affecting the transformer safe operation. Therefore, it is of great significance to carry out the TDB detection and suppression. In this article, first, according to the distortion characteristics of the transformer excitation current under TDB. This article presents a method for measuring the bias voltage content of the transformer in the ac/dc environment to detect TDB. Second, the value of TDB is calculated by measuring the voltage difference before and after the dc bias, so as to obtain the degree of TDB. The feasibility of this scheme is verified by multigroup simulations of single-phase transformer (SPT) and three-phase transformer (TPT). Finally, the SPT and TPT simulated experiments of TDB are designed, and one kind of TDB suppression is carried out based on a hybrid transformer model. The experimental results are in good agreement with the simulation results, which can provide certain reference for TDB control in the dc transmission and ac/dc distribution networks.

The increasing integration of distributed generations brings great challenges to the power grid. In this paper, a distributed photovoltaic (PV) integration methodology in distribution network is established for large-scale PV penetration. Firstly, a PV integration model was formulated with the aim of maximizing PV integration capacity and enhancing the voltage profile. Specially, the PV large-scale integration model for county-wide promotion is proposed by considering various typical integration scenarios. Additionally, a novel improved multi-objective Teaching-Learning based optimization (TLBO) algorithm, namely, IM-TLBO, was proposed to seek an optimal Pareto front of the PV integration model. The IM-TLBO algorithm innovatively incorporates the elite reverse learning search strategy to enhance exploration in the solution space. Moreover, the differentiated teaching guided by optimal individual and central location is employed to improve the efficiency of the “teaching” process. Meanwhile, a cyclic crowded sort deletion based on crowding distance is developed to enhance the diversity of elite individuals and the distribution characteristics of the Pareto Frontier. Finally, the performance of IM-TLBO is tested in benchmark functions. Also, a simulation case in IEEE 33 bus system is performed to verify the proposed PV integration method. It is observed that the proposed method in this paper can not only realize the overall optimal integration of roof distributed PV, but also improve voltage profile. The results of IM-TLBO are compared to other classical algorithms, and it is shown that IM-TLBO outperformed them in terms of convergence, distribution and diversity.