Department of Mathematics and Statistics, International Islamic University, Islamabad, Pakistan.
Department of Software, Korea National University of Transportation, Chungju, 27469, Korea.
Sci Rep. 2023 Jan 30;13(1):1707. doi: 10.1038/s41598-023-27387-9.
Energy storage is a way of storing energy to reduce imbalances between demand and energy production. The ability to store electricity and use it later is one of the keys to reaching large quantities of renewable energy on the grid. There are several methods to store energy such as mechanical, electrical, chemical, electrochemical, and thermal energy. Regarding their operation, storage, and cost, the choice of these energy storage techniques appears to be interesting. This issue becomes very serious when there involves uncertainty. To consider this kind of uncertain information, a picture fuzzy soft set is found to be a more appropriate parameterization tool to deal with imprecise data. Based on the advanced structure of picture fuzzy soft set, here in this article, firstly, we have developed the notions of basic operational laws for picture fuzzy soft numbers. Then based on these developed operational laws, we have established the notions of picture fuzzy soft power average [Formula: see text], weighted picture fuzzy soft power average [Formula: see text] and ordered weighted picture fuzzy soft power average [Formula: see text] aggregation operators. Moreover, we have introduced the notions for picture fuzzy soft power geometric [Formula: see text], weighted picture fuzzy soft power geometric [Formula: see text] and ordered weighted picture fuzzy soft power geometric [Formula: see text] aggregation operators. Furthermore, we have established the application of picture fuzzy soft power aggregation operators for the selection of thermal energy storage techniques. For this, we have developed a decision-making approach along with an explanatory example to show the effective use of the developed theory. Furthermore, a comparative analysis of the introduced work shows the advancement of developed notions.
储能是一种存储能源的方式，旨在减少能源生产与需求之间的不平衡。存储和随后使用电力的能力是实现电网中大量可再生能源的关键之一。有几种方法可以存储能源，例如机械、电气、化学、电化学和热能。考虑到它们的操作、存储和成本，这些储能技术的选择似乎很有趣。当涉及到不确定性时，这个问题就变得非常严重。为了考虑这种不确定信息，发现图像模糊软集是处理不精确数据的更合适的参数化工具。基于图像模糊软集的先进结构，本文首先发展了图像模糊软数的基本运算定律的概念。然后，基于这些发展的运算定律，我们建立了图像模糊软幂平均[公式：见文本]、加权图像模糊软幂平均[公式：见文本]和有序加权图像模糊软幂平均[公式：见文本]聚合算子的概念。此外，我们引入了图像模糊软幂几何[公式：见文本]、加权图像模糊软幂几何[公式：见文本]和有序加权图像模糊软幂几何[公式：见文本]聚合算子的概念。此外，我们建立了图像模糊软幂聚合算子在热能存储技术选择中的应用。为此，我们开发了一种决策方法，并附有一个解释性示例，以展示所开发理论的有效应用。此外，对所引入工作的比较分析表明了所发展概念的先进性。
