In this paper, the optimum operation of a distribution network in the presence of renewable resources, and a new combined system of liquid carbon dioxide energy storage is investigated. A comprehensive structure is pr...
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In this paper, the optimum operation of a distribution network in the presence of renewable resources, and a new combined system of liquid carbon dioxide energy storage is investigated. A comprehensive structure is proposed for modeling and optimizing the combination of wind turbine and solar sources with the new energy storage system by considering their converters. Then, a multipurpose structure in the presence of these resources and the new storage resource is presented to overcome the uncertainty of the output power of renewable resources and improve the reliability of the grid. To this end, first, by considering the probabilistic nature of wind and solar resources, a relatively comprehensive modeling of the system is presented. Economic costs, including the cost of setting up units, cost of generation, and emission of these units, are presented as optimization problem. The effects of the storage system on the load curve are investigated and discussed. The proposed objective function is determined based on optimal load distribution and technical constraints. The multi-objective group teaching optimization algorithm is used to solve the microgrid optimal operation problem. The proposed model consid-ering three cases, is successfully implemented on a 33-bus RBTS distribution network. The results indicated that the total cost of the proposed system in the first, second, and third case is decreased by about 2.88%, 21.78% and 21.2% compared to the base case study. The cost reduction in the first case is due to the use of renewable energy sources, and this reduction in the second case is more due to the use of new storage. Finally, in the third case, due to the consideration of uncertainty and reliability index, compared to the second case, the amount of cost has increased slightly, but compared to the main case, there is a significant decrease, which indicates the superiority of the proposed model.
The teaching of the optimizationalgorithm is a new kind of swarm intelligence optimization technique, which is superior in optimizing many simple functions. Still, it is not evident in processing some complex problem...
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The teaching of the optimizationalgorithm is a new kind of swarm intelligence optimization technique, which is superior in optimizing many simple functions. Still, it is not evident in processing some complex problems (group and teaching classification). Achieving automatic matching and knowledge transfer in online courses is imperative in mathematics education. This study proposes a design scheme MTCBO-LR (multiobjective capability optimizer-logistic regression), based on multitask optimization, which enables precise knowledge transfer and data interaction among many educators. It incorporates the standard TLBO algorithm to optimize, provides a variety of learning tactics for students at different stages of mathematics instruction, and is capable of adaptively adjusting these strategies in response to actual teaching needs. Experimental results on various datasets reveal that the proposed method enhances searchability and group diversity in various optimization extremes and outperforms similar methods in resolving to multitask teaching problems.
With the emergence of the artificial intelligence era,all kinds of robots are traditionally used in agricultural ***,studies concerning the robot task assignment problem in the agriculture field,which is closely relat...
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With the emergence of the artificial intelligence era,all kinds of robots are traditionally used in agricultural ***,studies concerning the robot task assignment problem in the agriculture field,which is closely related to the cost and efficiency of a smart farm,are ***,a Multi-Weeding Robot Task Assignment(MWRTA)problem is addressed in this paper to minimize the maximum completion time and residual herbicide.A mathematical model is set up,and a Multi-Objective teaching-Learning-Based optimization(MOTLBO)algorithm is presented to solve the *** the MOTLBO algorithm,a heuristicbased initialization comprising an improved Nawaz Enscore,and Ham(NEH)heuristic and maximum loadbased heuristic is used to generate an initial population with a high level of quality and *** effective teaching-learning-based optimization process is designed with a dynamic grouping mechanism and a redefined individual updating rule.A multi-neighborhood-based local search strategy is provided to balance the exploitation and exploration of the ***,a comprehensive experiment is conducted to compare the proposed algorithm with several state-of-the-art algorithms in the *** results demonstrate the significant superiority of the proposed algorithm for solving the problem under consideration.
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