Solar energy paper index
Data-driven distributed optimal control of VPP for guaranteed frequency response in low-inertia power systems
One-line summary
A solar energy research paper on Data-driven distributed optimal control of VPP for guaranteed frequency response in low-inertia power systems.
Engineering notes
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Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
In this study, we propose a data-driven distributed optimal control approach to realize guaranteed system frequency response (SFR) from aggregated resources within the virtual power plant (VPP). First, a framework for guaranteed SFR based on the concept of VPP is proposed, which includes an upper optimization layer and a lower coordinated control layer. The optimization layer provides each VPP with the frequency response target expected by the transmission system operator (TSO). Then, in the coordinated control layer, DERs can be controlled to realize the frequency response target. Second, the problem is formulated as a robust output containment control problem of heterogeneous leader–follower multi-agent systems with disturbances. Finally, a data-driven distributed robust containment controller is proposed for DERs. An off-policy integral reinforcement learning (IRL) algorithm is developed to obtain the optimal controller, which does not require any knowledge of system dynamics.
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