Comparison between PID and PSO-PID controllers in analysing the load frequency control in interconnected microgrids in a deregulated environment

被引:1
作者
Singh, Ranjit [1 ]
Ramesh, L. [1 ]
机构
[1] Dr MGR Educ & Res Inst, Dept Elect & Elect Engn, Chennai, Tamil Nadu, India
关键词
MGs; microgrids; frequency error; LFC; load frequency control; tie-line power; PID proportional integral derivative; controller; PSO; particle swarm optimisation; SYSTEMS; AC;
D O I
10.1504/IJGEI.2024.135249
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper focuses on analysing the frequency error in interconnected microgrids and reducing the generation cost, which is considered one of the objective functions. The Simulink model shows the connection between two microgrids, i.e., microgrid 1 comprises thermal, hydro and gas power plants, whereas microgrid 2 comprises thermal, nuclear and gas power plants. The change in the tie-line power is also considered while simulating the model. The paper's main aim is to reduce the variations in frequency in each microgrid to ensure the steady flow of power among the connected microgrids along with the tie-line power. Also, the robustness of PID and PSO-PID Controllers are compared and analysed. The particle swarm optimisation algorithm codes tune the controller's gains in MATLAB. The model is simulated using MATLAB 2014b, and necessary graphs are obtained, which show the frequency error reduction time in both the microgrids.
引用
收藏
页码:112 / 136
页数:26
相关论文
共 54 条
  • [1] Effect of corrugated beds on characteristics of submerged hydraulic jump
    Ahmed, Hossam Mohamed Ali
    El Gendy, Mohamed
    Mirdan, Ahmed Mohamed Hassan
    Ali, Abdel Azim Mohamed
    Haleem, Fahmy Salah Fahmy Abdel
    [J]. AIN SHAMS ENGINEERING JOURNAL, 2014, 5 (04) : 1033 - 1042
  • [2] A Benchmark Test System for Networked Microgrids
    Alam, Mahamad Nabab
    Chakrabarti, Saikat
    Liang, Xiaodong
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 16 (10) : 6217 - 6230
  • [3] Optimal Load Frequency Control of Island Microgrids via a PID Controller in the Presence of Wind Turbine and PV
    Alayi, Reza
    Zishan, Farhad
    Seyednouri, Seyed Reza
    Kumar, Ravinder
    Ahmadi, Mohammad Hossein
    Sharifpur, Mohsen
    [J]. SUSTAINABILITY, 2021, 13 (19)
  • [4] An Optimal Adaptive Control Strategy for Energy Balancing in Smart Microgrid Using Dynamic Pricing
    Albogamy, Fahad R.
    Zakria, Muhammad
    Khan, Taimoor Ahmad
    Murawwat, Sadia
    Hafeez, Ghulam
    Khan, Imran
    Ali, Faheem
    Khan, Sheraz
    [J]. IEEE ACCESS, 2022, 10 : 37396 - 37411
  • [5] Minimizing downstream scour due to submerged hydraulic jump using corrugated aprons
    Ali, Hossam Mohamed
    El Gendy, Mohamed Mohamed
    Mirdan, Ahmed Mohamed Hassan
    Ali, Abdel Azim Mohamed
    Abdelhaleem, Fahmy Salah Fahmy
    [J]. AIN SHAMS ENGINEERING JOURNAL, 2014, 5 (04) : 1059 - 1069
  • [6] Reinforcement Learning Techniques for Optimal Power Control in Grid-Connected Microgrids: A Comprehensive Review
    Arwa, Erick O.
    Folly, Komla A.
    [J]. IEEE ACCESS, 2020, 8 : 208992 - 209007
  • [7] Ashour E.H., 2021, Water and Energy International, V64, P6
  • [8] Optimizing hyperparameters of deep reinforcement learning for autonomous driving based on whale optimization algorithm
    Ashraf, Nesma M.
    Mostafa, Reham R.
    Sakr, Rasha H.
    Rashad, M. Z.
    [J]. PLOS ONE, 2021, 16 (06):
  • [9] Babaei M., 2022, Distributed Generation Alternative Energy Journal, V37, P1755
  • [10] Distributed Robust Hierarchical Power Sharing Control of Grid-Connected Spatially Concentrated AC Microgrid
    Cai, He
    Hu, Guoqiang
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2019, 27 (03) : 1012 - 1022