De-risking transient stability of AC/DC power systems based on ESS integration

• Published in: Journal of engineering (Stevenage, England) Vol. 2019; no. 16; pp. 1221 - 1226
• Main Authors: Yao, Liangzhong, Wu, Fubao, Qiu, Gao, Liu, Junyong, Liu, Youbo, Cui, Hongfen, Sang, Bingyu, Ye, Jilei
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.03.2019; Wiley
• Subjects: AC-DC power convertors; AC/DC power system; AC/DC system; charging/discharging flexibility; electric storage system; energy storage; ESS integration; evolutionary computation; modified AC/DC test system; multiobjective ESS allocating; optimisation; Pareto optimisation; power system control; power system faults; power system security; power system transient stability; power systems; probability; risking transient stability; size; sizing approach; sizing model; The 14th IET International Conference on AC and DC Power Transmission (ACDC 2018); transient power balancing; transient stability risk; Pareto optimisation; probability; power system transient stability; modified AC/DC test system; transient stability risk; power system security; power system faults; sizing approach; charging/discharging flexibility; evolutionary computation; multiobjective ESS allocating; ESS integration; optimisation; AC/DC system; risking transient stability; size; energy storage; AC/DC power system; transient power balancing; sizing model; power systems; electric storage system; AC-DC power convertors; power system control
• ISSN: 2051-3305; 2051-3305
• DOI: 10.1049/joe.2018.8580

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.