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A novel multi-objective Dynamic Programming optimization method: Performance management of a solar thermal power plant as a case study

机译:一种新颖的多目标动态规划优化方法:以太阳能热电厂的绩效管理为例

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摘要

Due to the intermittent nature of solar irradiance, solar power plants are usually equipped with energy storage systems. Suitable charge and discharge management of the storage systems can considerably help increase the reliability and profitability of the solar systems. In this regard, various optimization approaches, with their own strengths and limitations, have been employed by literature. Dynamic Programming (DP) is one of the fittest approaches for the wide range of engineering problems which exhibit the properties of overlapping sub-problems. DP is a simple, gradient-free, efficient, and deterministic optimization method that guarantees the optimal solution. However, this method has not been developed for multi-objective problems. This study develops a multi-objective DP method and employs it for the performance management of a solar power plant equipped with thermal energy storage system. "Daily electricity generation" and "daily revenue obtained from selling electricity" are considered to be the objective functions. The superiority of the developed method is shown through a comparison with one of the most commonly used multi-objective optimization approaches, NSGA-II. This comparison indicates that the multi-objective DP attains 3.0%-7.5% greater values of electricity generation and 3.1% -12.6% higher values of revenue than NSGA-II, for the different levels of solar radiation. (C) 2018 Elsevier Ltd. All rights reserved.
机译:由于太阳辐射的间歇性,太阳能发电厂通常配备有能量存储系统。对存储系统进行适当的充电和放电管理可以大大帮助提高太阳能系统的可靠性和盈利能力。在这方面,文献已经采用了各种具有自身优势和局限性的优化方法。动态编程(DP)是解决各种工程问题的最合适方法之一,这些工程问题表现出重叠的子问题的性质。 DP是一种简单,无梯度,高效且确定性的优化方法,可确保获得最佳解决方案。但是,尚未针对多目标问题开发此方法。本研究开发了一种多目标DP方法,并将其用于装备有热能存储系统的太阳能发电厂的性能管理。 “每日发电量”和“通过售电获得的每日收入”被视为目标函数。通过与最常用的多目标优化方法之一NSGA-II进行比较,表明了所开发方法的优越性。该比较表明,对于不同水平的太阳辐射,多目标DP的发电价值比NSGA-II高3.0%-7.5%,收入价值高3.1%-12.6%。 (C)2018 Elsevier Ltd.保留所有权利。

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