WANG Yufei, LI Keming, CHEN Qiang, XUE Hua, YU Aiqing. Congestion Management Method for Active Distribution Network Based on Market Mechanism and Mobile Energy Storage System[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0372
Citation: WANG Yufei, LI Keming, CHEN Qiang, XUE Hua, YU Aiqing. Congestion Management Method for Active Distribution Network Based on Market Mechanism and Mobile Energy Storage System[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0372

Congestion Management Method for Active Distribution Network Based on Market Mechanism and Mobile Energy Storage System

  • In allusion to the two-way congestion problem of the distribution network caused by the temporal and spatial accumulation of electricity load and the peak of renewable energy output, in view of the response potential of thermostatically controlled loads under the market environment and the spatiotemporal flexibility of mobile energy storage system technology, a day-ahead and intra-day two-stage congestion management method for active distribution networks, taking into account market mechanism and mobile energy storage, was proposed. Firstly, the hierarchical structure and trading mechanism of the power market considering thermostatically controlled load response characteristics were constructed, so as to realize day-ahead management of distribution network congestion by adjusting the power consumption of thermostatically controlled load. Secondly, considering the uncertainty of load response and the prediction error of day-ahead renewable energy output, the mobile energy storage system which could adapt to the spatiotemporal change of distribution network congestion was introduced to build a day-ahead and intra-day congestion management framework based on market mechanism and mobile energy storage, ensuring that system congestion was eliminated, taking into account economy simultaneously. The simulation results show that the proposed method can effectively solve the congestion problem of active distribution networks and reduce the congestion management cost of distribution system operators..
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