A Distributed Load Scheduling Mechanism for Micro Grids

被引:0
|
作者
Monteiro, Janio [1 ,2 ]
Eduardo, Jorge [1 ]
Cardoso, Pedro J. S. [1 ,3 ]
Semiao, Jorge [1 ,2 ]
机构
[1] Univ Algarve, ISE, Faro, Portugal
[2] INESC ID, Lisbon, Portugal
[3] Univ Algarve, LARSys, Faro, Portugal
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Several protocols have recently been defined for smart grids that enable the communication between electric devices and energy management systems. While these protocols and architectures can already be applied in different fields of micro grids, it is still not clear how the distributed resources and constraints of such electrical grids can be managed in an optimum way. In order to achieve a reduction in electricity costs and maximizing investments made in renewable sources, an optimization mechanism should be used to perform load scheduling, considering different variables such as forecasted power generation curve from renewable sources, different tariffs' rates, electric circuit constraints, user restrictions and correspondent comfort levels. Given these considerations, this work defines and evaluates a distributed micro grid resource management architecture and protocol which is able to optimize load scheduling while considering all the mentioned restrictions and parameters. The proposed architecture was implemented on a multi-agent simulator and the performed tests show that significant reductions in electricity cost can be achieved using this methodology.
引用
收藏
页码:278 / 283
页数:6
相关论文
共 50 条
  • [1] Distributed Scheduling on Utility Grids
    Bansal, Sunita
    Hota, Chittaranjan
    [J]. ROMANIAN JOURNAL OF INFORMATION SCIENCE AND TECHNOLOGY, 2013, 16 (04): : 373 - 392
  • [2] Distributed Discrete Level Energy Scheduling for Residential Load Control in Smart Grids
    Chai, Chin Choy
    [J]. TENCON 2017 - 2017 IEEE REGION 10 CONFERENCE, 2017, : 1727 - 1732
  • [3] Distributed Deep Reinforcement Learning for Intelligent Load Scheduling in Residential Smart Grids
    Chung, Hwei-Ming
    Maharjan, Sabita
    Zhang, Yan
    Eliassen, Frank
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (04) : 2752 - 2763
  • [4] Adaptable Load Scheduling for Smart Grids
    Chai, Chin Choy
    Xiang, Liu
    [J]. TENCON 2017 - 2017 IEEE REGION 10 CONFERENCE, 2017, : 1721 - 1726
  • [5] DEMAND SIDE LOAD LEVELING USING DISTRIBUTED MICRO ENERGY AND STORAGE SYSTEMS WITH THE ESTABLISHMENT OF MICRO GRIDS
    Naveen, G.
    Kumar, Pramod B.
    Sudheer, M. L.
    [J]. 2013 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT ASIA), 2013,
  • [6] PLC based Load Shedding Mechanism using Battery SOC in Micro Grids
    Adarsh, T., V
    Suresh, H. L.
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON POWER, CONTROL, SIGNALS AND INSTRUMENTATION ENGINEERING (ICPCSI), 2017, : 1350 - 1351
  • [7] A Dynamic Replication Aware Load Balanced Scheduling for Data Grids in Distributed Environments of Internet of Things
    Bakhshad, Said
    Noor, Rafidah Md
    Akhunzada, Adnan
    Saba, Tanzila
    Bin Ahmedy, Ail
    Haroon, Faisal
    Nazir, Babar
    [J]. AD HOC & SENSOR WIRELESS NETWORKS, 2018, 40 (3-4) : 275 - 296
  • [8] Distributed generation and micro-grids
    Hoff, TE
    Wenger, HJ
    Herig, C
    Shaw, RE
    [J]. INTERNATIONAL ENERGY MARKETS, COMPETITION AND POLICY, CONFERENCE PROCEEDINGS, 1997, : 239 - 248
  • [9] Modeling and distributed gain scheduling strategy for load frequency control in smart grids with communication topology changes
    Liu, Shichao
    Liu, Xiaoping P.
    El Saddik, Abdulmotaleb
    [J]. ISA TRANSACTIONS, 2014, 53 (02) : 454 - 461
  • [10] Distributed Coordinated Optimal Scheduling of Interconnected Micro-energy Grids Considering Multi-energy Sharing
    Feng, Changsen
    Ren, Dongdong
    Shen, Jiajing
    Wen, Fushuan
    Zhang, Youbing
    [J]. Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2022, 46 (11): : 47 - 57