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دانلود رایکان مقاله انگلیسی ISI با موضوع سیستم مدل سازی پیشرفته برای بهینه سازی طرح مزرعه بادی و سایزبندی توربین بادی

عنوان فارسی مقاله:

سیستم مدل سازی پیشرفته برای بهینه سازی طرح مزرعه بادی و سایزبندی توربین بادی با استفاده از الگوریتم جستجوی الگوی توسعه یافته چند سطحی

عنوان انگلیسی مقاله:

An advanced modeling system for optimization of wind farm layout and wind turbine sizing using a multi-level extended pattern search algorithm

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بخشی از مقاله انگلیسی :

4. Multi-agent system methodology

A multi-agent system (MAS) is a collaboration of semiautonomous software agents, loosely simulating the function of a human design team. Each agent represents a single purpose or specialty just as a single design engineer would have unique training or experience. Individually, agents work internally to meet their own particular goals and job function. However, if given the means to communicate effectively within a group, a MAS can interconnect and collectively work towards a balance between the global optimum and their individual objectives. The agents in the current system, which are both autonomous and capable of collaboration, are called collaborative agents [33]. The solutions acquired by collaborative agents may be superior to the sum of the capabilities of the individual agents involved [34]. The cooperation of agents representing strategies and capabilities grouped together in multi-agent systems has been shown to be very successful in solving engineering design problems in previous systems, such as in A-Teams [35], A-Design [36], and blackboard systems [37]. In the current work, an individual agent represents a single turbine. The agent is equipped with memory capability for its current location, previous location, current and most recent previous geometric parameters, and current upstream and downstream turbines. An initial number of agents are created, with additional individual turbine agents are added to determine layouts with the optimal number of turbines. The EPS performs on one agent at a time, with each agent concurrently selecting its new potential locations, potential new hub height, and rotor radius. Then, each agent calculates the global objective, and determines whether to take a potential move or to take on new sizing. Once an agent has completed a single round of the EPS-MAS, a new agent begins. The order in which the agents perform the EPS-MAS is randomized, which is one of the beneficial extensions of the EPS-MAS.