Coordinated Emergency Operation Strategy for Distribution Networks and Photovoltaic-Storage-Charging Integrated Station Based on Master–Slave Game.
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| Title: | Coordinated Emergency Operation Strategy for Distribution Networks and Photovoltaic-Storage-Charging Integrated Station Based on Master–Slave Game. |
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| Authors: | Lan, Zheng1 (AUTHOR), Zhou, Jiawen1,2 (AUTHOR) m23080800011@stu.hut.edu.cn, Wang, Xin1,2 (AUTHOR) |
| Source: | Energies (19961073). Apr2026, Vol. 19 Issue 8, p1922. 19p. |
| Subject Terms: | *Bilevel programming, *Game theory, *Electric power system stability, *Power distribution networks, *Electric vehicle charging stations, *Predictive control systems, *Emergency management |
| Abstract: | Under fault conditions, Photovoltaic-Storage-Charging Integrated Stations (PSCISs) are regarded as a key resource for enhancing distribution network resilience. However, traditional centralized optimization fails to account for conflicts of interest between the distribution network and PSCISs and neglects the actual response behavior of EV users. To address these issues, a coordinated emergency operation strategy for distribution networks and PSCISs based on the master–slave game is proposed. Firstly, a bilevel optimization framework based on the master–slave game is constructed, where the upper level performs system-level coordination and the lower level handles autonomous decision-making. For the upper level, the minimization of distribution network operation cost is set as the optimization objective by the dispatching center to determine power purchase prices and load shedding rates, which serve as guidance signals for lower-level PSCISs. In terms of the lower level, a dual-factor S-shaped response curve is introduced into the lower-level model to precisely characterize EV users' nonlinear response behavior to price incentives. Furthermore, based on the signals received from the upper level, the maximization of each PSCIS's profit is set as the optimization objective to determine the PV output, storage dispatch, and V2G incentive prices. Subsequently, Model Predictive Control (MPC) is employed to implement rolling optimization during the fault period, addressing the source-load uncertainties. Finally, an improved IEEE 33-node distribution network is used for case analysis and validation of the proposed operation strategy. The results indicate that the proposed strategy can effectively coordinate the interests of multiple parties, achieving synergistic improvements in both the economy and reliability of the distribution network. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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