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De‐risking transient stability of AC/DC power systems based on ESS integration
Author(s) -
Yao Liangzhong,
Wu Fubao,
Qiu Gao,
Liu Junyong,
Liu Youbo,
Cui Hongfen,
Sang Bingyu,
Ye Jilei
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.8580
Subject(s) - transient (computer programming) , sizing , electric power system , flexibility (engineering) , computer science , pareto principle , probabilistic logic , control theory (sociology) , stability (learning theory) , fault (geology) , power (physics) , reliability engineering , mathematical optimization , engineering , mathematics , art , statistics , physics , control (management) , quantum mechanics , artificial intelligence , machine learning , seismology , visual arts , geology , operating system
Owing to the charging/discharging flexibility, electric storage system (ESS) is widely recognised as a promising technique that can be introduced to enhance transient stability of power systems. Here, a multi‐objective ESS allocating and sizing approach is presented to de‐risk the loss of stability for the AC/DC power system. The approach contains two major steps. Firstly, transient stability risk (TSR) is assessed based on the severity and probability of contingencies which is simulated according to the good point set sampling considering multiple uncertainties and probabilistic fault. In the second step, an allocating and sizing model is proposed for ESS to minimise the operational cost, while the AC/DC system is subject to the TSR. Additionally, strength Pareto evolutionary algorithm (SPEA2) is employed to solve the model, optimising ESS allocation and size as well as output of regular generators. A modified AC/DC test system is used to validate the presented approach. The results indicate that, with the appropriate planning strategy, ESS is able to significantly contribute to TSR improvement as it can assist in transient power balancing after a severe fault.

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