Adaptive Multiagent Primary Secondary Control for Accurate Synchronized Charge-Discharge Scenarios of Battery Distributed Energy Storage Systems in DC Autonomous Microgrid

Al-Saadi, Mudhafar; Al‐Greer, Maher

doi:10.1109/upec55022.2022.9917579

Cited by 6 publications

(11 citation statements)

References 17 publications

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“…Hence, the real-time balance of the voltage at this point was maintained at Vmg, as presented in (15). In accordance, a real-time secondary control reference was achieved (Vref_sec_i) to request an extra charge or discharge upon the compensation of the requested correction to fulfill the mandatory balanced power-flow policy [15,37].…”

Section: The Decentralized Secondary Correctionmentioning

confidence: 99%

“…The compensation of the DC infrastructure influence on the control process holds vital significance in the power-flow balance of the microgrid's real-world operation. Thus, the success, validation, and optimization of the control in the real-world operation depends entirely on how successful the compensation of the DC infrastructure influence is [36,37]. Accordingly, a compensation method based on multiagent neighbor-to-neighbor communication has been introduced to locally compensate for the infrastructure impact on the control process, with no need for pregiven information regarding the local infrastructure details.…”

Section: The Compensation Of the DC Infrastructure Influence On The C...mentioning

confidence: 99%

“…Since the operational methodology of each decentralized BESS in the microgrid experiences different instantaneous operational conditions and scenarios, three scenarios were constructed to emulate the real operation in the simulations and hardware-in-the-loop (HiL)-based experiments. These scenarios were taken into consideration when measuring and compensating for the DC infrastructure impact on the controller regarding the discharging participation, charging participation, and plug-and-play off-participation, as described below [16,36,37].…”

Section: The Compensation Of the DC Infrastructure Influence On The C...mentioning

confidence: 99%

“…The accomplished control action is based on the current error (ei_pri) of IB_ref_Ch_Dis_i from the real-time locally measured battery current (Ib_i). This denotes the requested battery charge or discharge to verify the mandatory power-flow balance, as shown in (11) [15,37,38].…”

Section: The Decentralized Control-primary Levelmentioning

confidence: 99%

“…Therefore, an enhanced reduction in the circulating current/overloading was fulfilled. This is reflected in the maintained accuracy of the charge-discharge synchronization, the optimized steadying of the control process, the better battery health, and the longer usage life [10,15,37].…”

Section: The Decentralized Control-primary Levelmentioning

confidence: 99%

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Multiagent-Based Control for Plug-and-Play Batteries in DC Microgrids with Infrastructure Compensation

Al-Saadi,

Short

2023

Batteries

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The influence of the DC infrastructure on the control of power-storage flow in micro- and smart grids has gained attention recently, particularly in dynamic vehicle-to-grid charging applications. Principal effects include the potential loss of the charge–discharge synchronization and the subsequent impact on the control stabilization, the increased degradation in batteries’ health/life, and resultant power- and energy-efficiency losses. This paper proposes and tests a candidate solution to compensate for the infrastructure effects in a DC microgrid with a varying number of heterogeneous battery storage systems in the context of a multiagent neighbor-to-neighbor control scheme. Specifically, the scheme regulates the balance of the batteries’ load-demand participation, with adaptive compensation for unknown and/or time-varying DC infrastructure influences. Simulation and hardware-in-the-loop studies in realistic conditions demonstrate the improved precision of the charge–discharge synchronization and the enhanced balance of the output voltage under 24 h excessively continuous variations in the load demand. In addition, immediate real-time compensation for the DC infrastructure influence can be attained with no need for initial estimates of key unknown parameters. The results provide both the validation and verification of the proposals under real operational conditions and expectations, including the dynamic switching of the heterogeneous batteries’ connection (plug-and-play) and the variable infrastructure influences of different dynamically switched branches. Key observed metrics include an average reduced convergence time (0.66–13.366%), enhanced output-voltage balance (2.637–3.24%), power-consumption reduction (3.569–4.93%), and power-flow-balance enhancement (2.755–6.468%), which can be achieved for the proposed scheme over a baseline for the experiments in question.

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Section: The Decentralized Secondary Correctionmentioning

confidence: 99%

Section: The Compensation Of the DC Infrastructure Influence On The C...mentioning

confidence: 99%