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Sizing a stand-alone solar-wind-hydrogen energy system using weather forecasting and a hybrid search optimization algorithm
摘要： Due to increasing energy demand and fossil fuel costs in island and remote areas, renewable energy resources are becoming increasingly attractive. The hybridization of these resources can help overcome their variability and intermittency and improve e?ciency. Many independent hybrid renewable energy systems are used in remote and island areas for which weather data often is unavailable. To increase the accuracy of size optimization of such systems, more accurate weather data is needed and the use of weather forecasting data is helpful. In this article, a new hybrid optimization algorithm is proposed for the optimal sizing of a stand-alone hybrid solar and wind energy system based on three algorithms: chaotic search, harmony search and simulated annealing. To improve the accuracy of the size optimization algorithm results, weather forecasting is used along with arti?cial neural networks for solar radiation, ambient temperature, and wind speed forecasting. The main objective function of minimizing the total life cycle cost is used to assess the feasibility of the hybrid renewable energy system accounting for system reliability. The reliability of the system is assessed by the loss of power supply probability parameter. The new method is tested for the electrical load of the city of Khorasan, Iran. The results are compared with those obtained by the proposed algorithm (harmony search and simulated annealing-based arti?cial neural networks). The simulation results demonstrate the advantages of utilizing the hybrid optimization algorithm with weather forecasting data for a stand-alone hybrid renewable energy system.
关键词： Optimization,Stand-alone hybrid solar and wind energy system,Hybrid algorithm,Weather forecasting
更新于2025-09-10 09:29:36
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Computational Speedups Using Small Quantum Devices
摘要： Suppose we have a small quantum computer with only M qubits. Can such a device genuinely speed up certain algorithms, even when the problem size is much larger than M? Here we answer this question to the affirmative. We present a hybrid quantum-classical algorithm to solve 3-satisfiability problems involving n ? M variables that significantly speeds up its fully classical counterpart. This question may be relevant in view of the current quest to build small quantum computers.
关键词： quantum computing,hybrid algorithm,computational speedup,3-satisfiability
更新于2025-09-04 15:30:14
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Hybrid global maximum power point tracking algorithm under partial shading condition
摘要： This paper presents a hybrid global maximum power point tracking (MPPT) algorithm under partial shading conditions, which consists of five methods, including the global scanning method, the filtering method, the binary searching method, the three-point method, and the anti-restarting method. By making full use of the advantages of these methods, the proposed algorithm is able to improve tracking speed and efficiency, decrease oscillation, and avoid restarting. Among which, the global scanning method is used to find all the local intervals, the filtering method is used to reduce the search area, the binary searching method is used to reduce the search time, the three-point method is used to track the global maximum power point dynamically, and the anti-restarting method is used to prevent restarting the algorithm. To verify the proposed algorithm, experiments have been carried out in a standard environment, dynamic solar irradiation, and dynamic temperature, respectively. The performance of the proposed algorithm is verified by comparing it with a perturb and observe (P&O) based global scanning MPPT method and a modified P&O with checking MPPT method using computer simulations.
关键词： MPPT,global maximum power point tracking,photovoltaic systems,partial shading condition,hybrid algorithm,solar energy
更新于2025-09-04 15:30:14