This paper proposes a bi-level control framework for dynamic microgrid clusters in a distribution network with distributed photovoltaic and battery storage systems. The proposed bi-level control framework comprises in...
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This paper proposes a bi-level control framework for dynamic microgrid clusters in a distribution network with distributed photovoltaic and battery storage systems. The proposed bi-level control framework comprises interactive secondary and tertiary level control systems. A distributed event-triggered mechanism is proposed for the secondary level control of each dynamic microgrid cluster to achieve frequency and voltage regulation and balancing of the state of charge of battery storage systems within the cluster. At the tertiary level, a receding horizon model predictive control is implemented to minimize transmission power losses and battery storage systems losses by providing optimal battery storage systems output powers and the voltage source converters output voltages, with a one-minute interval. The secondary level control is modified to implement the optimal solutions provided by the tertiary level modelpredictivecontrol. Furthermore, the secondary level distributed event-triggered control minimizes unnecessary data transmission by introducing a time delay, resulting in a reduced communication burden. The proposed bi-level control framework is validated in real-time on a modified IEEE 13-node test feeder using RTDS with the tertiary level modelpredictivecontrol solved on a computer via the hardware-in-loop method.
Centralized control of a multi-agent system improves upon distributed control especially when multiple agents share a common task e.g., sorting different materials in a recycling facility. Traditionally, each agent in...
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ISBN:
(纸本)9798350384581;9798350384574
Centralized control of a multi-agent system improves upon distributed control especially when multiple agents share a common task e.g., sorting different materials in a recycling facility. Traditionally, each agent in a sorting facility is tuned individually which leads to suboptimal performance if one agent is less efficient than the others. Centralized control overcomes this bottleneck by leveraging global system state information, but it can be computationally expensive. In this work, we propose a novel framework called Longitudinal control Volumes (LCV) to model the flow of material in a recycling facility. We then employ a Kalman Filter that incorporates local measurements of materials into a global estimation of the material flow in the system. We utilize a modelpredictivecontrol algorithm that optimizes the rate of material flow using the global state estimate in real-time. We show that our proposed framework outperforms distributed control methods by 40-100% in simulation and physical experiments.
The virtual power plant (VPP) is a promising paradigm to promote the integration of renewable energy-based microgrid (MG) into the power system. This paper addresses the coordinated operation and energy trading proble...
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The virtual power plant (VPP) is a promising paradigm to promote the integration of renewable energy-based microgrid (MG) into the power system. This paper addresses the coordinated operation and energy trading problem for VPP aggregated with multi-stakeholder MGs. A two-stage hierarchical coordinated operation framework for VPP is developed consisting of the day-ahead bidding and intra-day dispatch fully considering the settlement of deregulated electricity market, the profit of the VPP operator and the aggregation interest of MGs. To cope with the intra-day operational uncertainties of individual MGs, recedinghorizon-based modelpredictivecontrol (MPC) is adopted and extra power balancing services are provided by the VPP operator. The proposed solution is extensively assessed through simulation experiments in presence of four MGs with different ownerships and penetration levels of RDERs, and the numerical results confirm that the proposed solution outperforms two benchmarks. Further, the comparison with two existing methods demonstrates that the adoption of time-ofuse price (ToUP) and extra power balancing services in the proposed solution can benefit both MGs and the VPP operator with enhanced energy management performance.
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