elitist nondominated sorting genetic algorithm (NSGA-II) is adopted and improved for multiobjective optimal reactive power flow (ORPF) problem. Multiobjective ORPF, formulated as a multiobjective mixed integer nonline...
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elitist nondominated sorting genetic algorithm (NSGA-II) is adopted and improved for multiobjective optimal reactive power flow (ORPF) problem. Multiobjective ORPF, formulated as a multiobjective mixed integer nonlinear optimization problem, minimizes real power loss and improves voltage profile of power grid by determining reactive power control variables. NSGA-II-based ORPF is tested on standard IEEE 30-bus test system and compared with four other state-of-the-art multiobjective evolutionary algorithms (MOEAs). Pareto front and outer solutions achieved by the five MOEAs are analyzed and compared. NSGA-II obtains the best control strategy for ORPF, but it suffers from the lower convergence speed at the early stage of the optimization. Several problem-specific local search strategies (LSSs) are incorporated into NSGA-II to promote algorithm's exploiting capability and then to speed up its convergence. This enhanced version of NSGA-II (ENSGA) is examined on IEEE 30 system. Experimental results show that the use of LSSs clearly improved the performance of NSGA-II. ENSGA shows the best search efficiency and is proved to be one of the efficient potential candidates in solving reactive power optimization in the real-time operation systems.
Industrial information integration can help companies develop supply chain systems and is a good framework for vehicle routing problem. To address the problems of excessive energy consumption, environmental pollution ...
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Industrial information integration can help companies develop supply chain systems and is a good framework for vehicle routing problem. To address the problems of excessive energy consumption, environmental pollution caused by carbon dioxide emission, and timeliness in the transportation process, a multi-objective vehicle routing optimization model was proposed to minimise transportation, carbon emission, and time window penalty costs. In the proposed model, an elitist nondominated sorting genetic algorithm was used to obtain the Pareto optimal solution. Furthermore, the optimal distribution path was selected by using multi-objective grey target decision making according to entropy value. Finally, a real distribution case was analysed, and the calculated optimal path was compared with the actual path of the case to verify the feasibility of the proposed model and algorithm. The results showed that the proposed model and algorithm can be effectively used to reduce the target cost.
Range extended electric vehicles (REEVs), transition vehicles between combustion engine vehicles and electric vehicles, have been widely used due to their advantages of low fuel consumption and low emissions. By optim...
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Range extended electric vehicles (REEVs), transition vehicles between combustion engine vehicles and electric vehicles, have been widely used due to their advantages of low fuel consumption and low emissions. By optimizing power management and after-treatment system control strategies, it is possible to achieve lower fuel consumption and emissions. This study proposes an integrated control method based on optimization strategies for the auxiliary power unit (APU) on/off system and energy man-agement optimization for extended hybrid electric vehicles. The elitist nondominated sorting genetic algorithm (NSGA-II) optimization method is used to determine the control parameters. In addition, considering the frequent start and stop characteristics of the APU caused by the optimization strategy, closed-loop control of the urea injection is established to solve the ammonia leakage problem. Due to their high computational efficiency, the proposed energy management and urea injection algorithms can be easily implemented in real time. The actual operating emissions of engines under the different strategies are tested on a semi-physical simulation platform, focusing on the analysis and comparison of NOx emissions. The conclusion has certain reference significance for vehicle production. (c) 2021 Elsevier Ltd. All rights reserved.
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