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Ant Lion optimizer applied to economic emission load dispatch problems turning off the engines

机译:蚂蚁狮优化器应用于关闭发动机的经济排放负荷分配问题

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A problem that is much studied today is the economic emission load dispatch (EELD) that seeks to minimize the total cost of fuel consumption and carbon emission. This problem is different from the economic load dispatch (ELD) that only seeks to minimize costs. In this work is applied a new optimization tool to solve this problem, the ant lion optimizer (ALO). Two functions are being used in this multi-objective metaheuristic algorithm, the cost function and emission function with their respective restrictions. Many materials and methods have been elaborated to fix the economic emission load dispatch, among them are as follows: differential evolution method, gradient method and Newton's method. The results for this case study, with the two application of ant lion, one with all generators on and another with the less efficient generators turned off, and in both cases the demand being met, were outstanding having a reduction of 9.21% in the total fuel cost, comparing to classical methods that distribute the generation of power among all generators, including the least efficient ones. This method helps the plant operators in the decision making of preventive maintenance of machines that are not working in. Besides solving the problem of the EELD this work also takes into account the shutdown of less efficient generators to meet the demand.
机译:当今,一个需要大量研究的问题是经济排放负荷分配(EELD),其目的是使燃料消耗和碳排放的总成本最小化。此问题不同于仅试图使成本最小化的经济负荷分配(ELD)。在这项工作中,应用了一种新的优化工具蚂蚁优化器(ALO)来解决此问题。在此多目标元启发式算法中使用了两个函数,分别是代价函数和发射函数,它们分别具有限制。为了固定经济排放负荷的分配,已经详细阐述了许多材料和方法,其中包括:差分演化法,梯度法和牛顿法。该案例研究的结果是,在两次使用蚁狮的情况下,一个使用了所有发电机,而另一个使用了效率较低的发电机,并且在两种情况下都满足了需求,该结果非常显着,减少了9.21%与传统方法相比,该方法可节省燃料成本,而经典方法是在所有发电机(包括效率最低的发电机)之间分配发电量。这种方法可帮助工厂操作人员做出预防性措施,以预防不工作的机器。除解决EELD问题外,这项工作还考虑了关闭效率较低的发电机以满足需求。

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