• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Energy Informatics >Comparative study of algorithms for optimized control of industrial energy supply systems
【24h】

Comparative study of algorithms for optimized control of industrial energy supply systems

机译：工业能源系统优化控制算法的比较研究

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Both rising and more volatile energy prices are strong incentives for manufacturing companies to become more energy-efficient and flexible. A promising approach is the intelligent control of Industrial Energy Supply Systems (IESS), which provide various energy services to industrial production facilities and machines. Due to the high complexity of such systems widespread conventional control approaches often lead to suboptimal operating behavior and limited flexibility. Rising digitization in industrial production sites offers the opportunity to implement new advanced control algorithms e. g. based on Mixed Integer Linear Programming (MILP) or Deep Reinforcement Learning (DRL) to optimize the operational strategies of IESS.This paper presents a comparative study of different controllers for optimized operation strategies. For this purpose, a framework is used that allows for a standardized comparison of rule-, model- and data-based controllers by connecting them to dynamic simulation models of IESS of varying complexity. The results indicate that controllers based on DRL and MILP have a huge potential to reduce energy-related cost of up to 50% for less complex and around 6% for more complex systems. In some cases however, both algorithms still show unfavorable operating behavior in terms of non-direct costs such as temperature and switching restrictions, depending on the complexity and general conditions of the systems.
机译：崛起和更挥发的能源价格都是制造公司变得更加节能灵活的强烈激励。一个有希望的方法是工业能源供应系统（IESS）的智能控制，为工业生产设施和机器提供各种能源服务。由于这种系统的高度复杂性，广泛的传统控制方法通常导致次优的操作行为和有限的灵活性。工业生产网站的数字化升高提供了实现新的先进控制算法e的机会。 G。基于混合整数线性规划（MILP）或深增强学习（DRL）来优化IESS的运营策略。本文提出了不同控制器的优化运行策略的比较研究。为此目的，使用框架，其允许通过将它们连接到不同复杂性的IESS的动态仿真模型来标准化比较规则，模型和数据控制器。结果表明，基于DRL和MILP的控制器具有巨大的潜力，可以降低能量相关的成本，以便更易于复杂，更复杂的系统约为6％。然而，在某些情况下，两种算法仍然在非直接成本（如温度和切换限制）方面都表现出不利的操作行为，具体取决于系统的复杂性和一般条件。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号