• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE transactions on industrial informatics >Low-Carbon Community Adaptive Energy Management Optimization Toward Smart Services
【24h】

Low-Carbon Community Adaptive Energy Management Optimization Toward Smart Services

机译：低碳群落适应能源管理优化智能服务

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

With the rapid development of society and the economy and the increasing seriousness of environmental problems, renewable energy and high-quality energy services in low-carbon communities have become popular research topics. However, a large number of volatile distributed generation power systems in the community are connected to the grid. It is difficult to stabilize and efficiently interact with fragmented and isolated energy management systems, and it is difficult to meet energy management needs in terms of low-carbon emissions, stability, and intelligence. Therefore, by considering operation costs, pollution control costs, energy stability, and plug-in hybrid electric vehicles, this article proposes a regional energy supply model called community energy Internet and builds a low-carbon community energy adaptive management model for smart services. Then, to address energy supply instability, an adaptive feedback control mechanism developed based on model predictive control is introduced to adapt to the changing environment. Finally, a long short-term memory-recurrent neural network-based Tabu search is introduced to prevent the multiobjective particle swarm optimization algorithm from easily falling into a local optimum. The simulation results show that the proposed model can effectively realize the optimal allocation of energy, which solves the problem of fragmented energy islands caused by distributed power access. This method has quality of service benefits for users, such as cost, time, and stability, and realizes wide interconnections, high intelligence, and low-carbon efficiency of community energy management.
机译：随着社会的快速发展和经济的发展和环境问题的严重性，低碳社区的可再生能源和高质量的能源服务成为流行的研究主题。然而，社区中的大量易失性分布生成电力系统连接到网格。难以稳定和有效地与碎片和隔离能量管理系统相互作用，并且难以满足低碳排放，稳定和智能的能源管理需求。因此，通过考虑运营成本，污染控制成本，能源稳定和插入式混合动力汽车，提出了一种称为社区能源互联网的区域能源供应模型，并为智能服务建立低碳社区能量适应性管理模型。然后，为了解决能量供应不稳定，引入了基于模型预测控制开发的自适应反馈控制机制，以适应变化的环境。最后，引入了长期短期内存复发性神经网络的禁忌搜索，以防止多目标粒子群优化算法易于落入局部最佳。仿真结果表明，该模型可以有效地实现能量的最佳分配，这解决了分布式电力接入引起的碎片能量岛的问题。该方法具有服务质量，为用户提供服务效益，例如成本，时间和稳定性，实现广泛的互联，高智能和社区能源管理的低碳效率。

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