Abstract This paper proposes and develops the idea of using a community supercapacitor (SC) in an islanded DC multiple nano‐grids (MNG) system. In the proposed structure, the community SC works in tandem with the community/cloud battery energy storage system (CBESS) of the DC MNG. This combination forms a grid‐forming battery‐supercapacitor cloud hybrid energy storage system (CHESS), which is responsible for maintaining the voltage stability and power balance at the common DC bus of the MNG system. Also, to effectively utilize the SC capacity, this paper proposes a modified control structure for each DC nano‐grid enabling the local BESS units to coordinate with the community SC. Then, it is shown that, in the proposed grid‐forming CHESS technology, the output power of all the local and community BESS units has significantly smoother power variations leading to a higher battery lifetime. Additionally, it is shown that the proposed CHESS technology can improve the voltage stability of the system leading to higher voltage quality. Moreover, it is discussed analytically that the proposed CHESS technology requires less energy storage capacity for the community SC compared to its equivalent MNG with a distributed SC architecture. Finally, these results are verified by simulating two case‐study MNGs in MATLAB/Simulink.
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A distributed rule‐based power management strategy in a photovoltaic/hybrid energy storage based on an active compensation filtering technique
This paper proposes a distributed rule-based power management strategy for dynamic power balancing and power smoothing in a photovoltaic (PV)/battery-supercapacitor hybrid energy storage system. The system contains a PV system, a battery-supercapacitor hybrid energy storage system (HESS), and a group of loads. Firstly, an active compensation technique is proposed which improves the efficiency of the power smoothing filter. Then, a distributed supervisory control technique is employed that prevents the BESS and SC from SOC violation while maintaining the balance between generation and load. To this end, the system components are divided into three different reactive agents including an HESS agent, a PV agent, and a load agent. These agents react to the system changes by switching their operational mode upon satisfying a predefined rule. To analyse the hybrid dynamical behaviour of the agents and design the supervisory controllers, the agents are modelled in hybrid automata frameworks. It is shown that the proposed distributed approach reduces the complexity of the supervisory control system and increases its scalability compared to its equivalent centralized method. Finally, the performance of the proposed approach is validated using a test system simulated in MATLAB/Simulink.
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- Award ID(s):
- 1757207
- PAR ID:
- 10294205
- Date Published:
- Journal Name:
- IET Renewable Power Generation
- ISSN:
- 1752-1416
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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