MACE - Multiagent Control for Energy Infrastructures

被引:0
|
作者
Beer, Sebastian
Troeschel, Martin
机构
[1] 26121 Oldenburg
关键词
Multiagent Systems; Distributed Energy Resources; Energy Infrastructures; Supply-Demand-Matching; DACS Methodology;
D O I
10.1007/978-3-540-88351-7_43
中图分类号
F [经济];
学科分类号
02 ;
摘要
Considering future energy supply infrastructures, distributed energy resources like micro-combined heat and power or photovoltaic plants are expected to increasingly pervade the public power grid. For supply companies, such decentralised power generation capacities provide the beneficial potential to cover demand peak loads of electrical power on level of the public grid by means of a systematic operation of the distributed components. The following work presents MACE, an agent-based control system for distributed energy resources in low voltage power grids. To level the global load progression of a given cluster, agents coordinate power generation and consumption of the underlying households by means of supply-demand-matching. In conclusion, an evaluation based on different simulation scenarios shows that the described technique is suitable for covering peak loads on level of the public grid.
引用
收藏
页码:579 / 592
页数:14
相关论文
共 50 条
  • [31] Opportunities for multiagent systems and multiagent reinforcement learning in traffic control
    Bazzan, Ana L. C.
    AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2009, 18 (03) : 342 - 375
  • [32] Policy control in multiagent system
    Ariuna, D
    Shigeyoshi, W
    Proceedings of the IASTED International Conference on Computational Intelligence, 2005, : 292 - 297
  • [33] HIERARCHICAL CONTROL IN A MULTIAGENT SYSTEM
    Damba, Ariuna
    Watanabe, Shigeyoshi
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2008, 4 (12): : 3091 - 3100
  • [34] Temperate Infrastructures and Thermal Control
    Ruiz, Rafico
    THRESHOLDS, 2023, (51) : 140 - 149
  • [35] Minimum-Energy Distributed Consensus Control of Multiagent Systems: A Network Approximation Approach
    Chen, Fei
    Chen, Jie
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2020, 65 (03) : 1144 - 1159
  • [36] Finite-Time Distributed Energy-to-Peak Control for Uncertain Multiagent Systems
    Qu Chenggang
    Cao Xibin
    Karimi, Hamid Reza
    Zhang Zhuo
    Zhang Zexu
    ABSTRACT AND APPLIED ANALYSIS, 2014,
  • [37] Multiagent control system for residential energy management under real time pricing environment
    Rasheed, Muhammad Babar
    Javaid, Nadeem
    Hussain, Sardar Mehboob
    Akbar, Mariam
    Khan, Zahoor Ali
    2017 IEEE 31ST INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS (AINA), 2017, : 120 - 125
  • [38] Energy-conserving event-triggered control for multiagent systems with limited resources
    Xie, Xiong
    Sheng, Tao
    Chen, Xiaoqian
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2024, 361 (15):
  • [39] Multiagent robotics: toward energy autonomy
    Trung Dung Ngo
    Raposo, Hector
    Schioler, Henrik
    ARTIFICIAL LIFE AND ROBOTICS, 2008, 12 (1-2) : 47 - 52
  • [40] Innovation and legacy in energy knowledge infrastructures
    Hirsch, Shana
    Ribes, David
    ENERGY RESEARCH & SOCIAL SCIENCE, 2021, 80