Abstract:Abstract-In this paper, a distributed multiagent based algorithm is proposed to achieve SoC balance for DES in the DC microgrid by means of voltage scheduling. Reference voltage given is adjusted instead of droop gain. Dynamic average consensus algorithm is explored in each agent to get the required information for scheduling voltage autonomously. State-space analysis on a single energy storage unit and simulation verification shows that the proposed method has two advantages. Firstly, modifying the reference … Show more
“…Fourth, it presents a lower sensitivity respect to secondary control level parameters over the system dynamics due to the larger stability margin of the primary controller. The advantages and disadvantages of the proposed strategy compared with the conventional power-sharing control [8]- [13] and the previous droop-based coordinated SoC control [30]- [36] are summarized in Table III.…”
Section: Experimental Results With the Proposed Coordinated Secondmentioning
confidence: 99%
“…The primary control can regulate the output voltage of each DG unit based on the commands sent from a high-level controller. Several coordinated control strategies for SoC balancing in an MG have been established by combining communication technology and hierarchical control [30]- [36]. A coordinated SoC control for distributed ESSs by using adaptive droop control in DC MGs has been proposed in [30].…”
Section: Introductionmentioning
confidence: 99%
“…Another research direction was taken by using fuzzy logic-based control strategy as presented in [33]- [35] for a DC MG by modifying the droop gains. Alternatively, a distributed multi-agentbased algorithm was proposed in [36] to achieve SoC balancing by using voltage scheduling.…”
--A coordinated secondary control approach based on an autonomous current-sharing control strategy for balancing the discharge rates of energy storage systems (ESSs) in islanded AC microgrids is proposed in this paper. The coordinated secondary controller can regulate the power outputs of distributed generation (DG) units according to their states-of-charge (SoCs) and ESS capacities by adjusting the virtual resistances of the paralleled voltage-controlled inverters. Compared with existing controllers, the proposed control strategy not only effectively prevents operation failure caused by overcurrent incidents and unintentional outages in DG units, but also aims to provide a fast transient response and an accurate output-current-sharing performance. A complete root locus analysis is given in order to achieve system stability and parameter sensitivity. Experimental results are presented to show the performance of the whole system and to verify the effectiveness of the proposed controller.
“…Fourth, it presents a lower sensitivity respect to secondary control level parameters over the system dynamics due to the larger stability margin of the primary controller. The advantages and disadvantages of the proposed strategy compared with the conventional power-sharing control [8]- [13] and the previous droop-based coordinated SoC control [30]- [36] are summarized in Table III.…”
Section: Experimental Results With the Proposed Coordinated Secondmentioning
confidence: 99%
“…The primary control can regulate the output voltage of each DG unit based on the commands sent from a high-level controller. Several coordinated control strategies for SoC balancing in an MG have been established by combining communication technology and hierarchical control [30]- [36]. A coordinated SoC control for distributed ESSs by using adaptive droop control in DC MGs has been proposed in [30].…”
Section: Introductionmentioning
confidence: 99%
“…Another research direction was taken by using fuzzy logic-based control strategy as presented in [33]- [35] for a DC MG by modifying the droop gains. Alternatively, a distributed multi-agentbased algorithm was proposed in [36] to achieve SoC balancing by using voltage scheduling.…”
--A coordinated secondary control approach based on an autonomous current-sharing control strategy for balancing the discharge rates of energy storage systems (ESSs) in islanded AC microgrids is proposed in this paper. The coordinated secondary controller can regulate the power outputs of distributed generation (DG) units according to their states-of-charge (SoCs) and ESS capacities by adjusting the virtual resistances of the paralleled voltage-controlled inverters. Compared with existing controllers, the proposed control strategy not only effectively prevents operation failure caused by overcurrent incidents and unintentional outages in DG units, but also aims to provide a fast transient response and an accurate output-current-sharing performance. A complete root locus analysis is given in order to achieve system stability and parameter sensitivity. Experimental results are presented to show the performance of the whole system and to verify the effectiveness of the proposed controller.
“…In [13], a distributed multi-agent based algorithm is proposed to realize SoC balancing by means of voltage scheduling. Reference [14] proposes a sliding mode control strategy based on multi-agent system to improve the converge speed of the existing SoC balancing strategies.…”
A decentralized battery energy storage system (DBESS) is used for stabilizing power fluctuation in DC microgrids. Different state of charge (SoC) among various battery energy storage units (BESU) during operation will reduce batteries' service life. A hierarchical distributed control method is proposed in this paper for SoC balancing and power control according to dispatching center requirement in DBESS. A consensus algorithm with pinning node is employed to allocate power among BESUs in the secondary control whereas in the primary control, the local controller of BESU adjusts output power according to the reference power from secondary control. Part of BESUs are selected to be pinning node for accepting command from dispatching center while other BESUs as following nodes which exchange output power and SoC information with the adjacent nodes through communication network. After calculating reference power of each BESU by adopting consensus algorithm, the power sharing in DBESS is achieved according to their respective SoC of BESUs. Meanwhile, the total output power of DBESS follows the varying requirements of dispatching center. The stability of DBESS is also improved because of having no center controller. The feasibility of the proposed control strategy is validated by simulation results.
“…Multi -agent systems is only one method among a lot that are being studied. In [27] the multi-agent approach is implemented and its design is described to simulate in Simulink the operation of a distributed smart grid under transient conditions, while in [28] the same method has been used to control the distributed energy storage in DC microgrids. It is quite interesting, that while multi agent control has been applied a lot in microgrid simulations regarding the voltage and frequency dynamic responses, it has not been applied in power management level.…”
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