TY - GEN
T1 - Intelligent optimization of reactive voltage in power grid including PV
AU - Jiang, Lei
AU - Li, Peng
AU - Liu, Dongsheng
AU - Du, Zhenbin
AU - Wang, Jiahao
AU - Zhang, Dong
AU - Pan, Youpeng
N1 - Publisher Copyright:
© VDE VERLAG GMBH.
PY - 2022
Y1 - 2022
N2 - Under the target of "carbon neutral and carbon peak", a large number of PV devices are connected to the power grid, which brings the problem of frequent fluctuation of power grid voltage. The existing reactive voltage optimization methods of power grid rely on accurate power grid model, and the real-time computing ability is difficult to adapt to the frequent voltage fluctuation of power grid including PV. In order to make full use of the reactive power regulation ability of PV, this paper proposes a reactive voltage optimization method including PV. Firstly, a reactive power regulation model of PV with the discrete PV reactive power output is established. Secondly, aiming to minimize voltage deviation and network loss, this paper builds the reactive voltage optimization model including PV based on DQN algorithm. Finally, an example is given to verify the correctness and effectiveness of the proposed method.
AB - Under the target of "carbon neutral and carbon peak", a large number of PV devices are connected to the power grid, which brings the problem of frequent fluctuation of power grid voltage. The existing reactive voltage optimization methods of power grid rely on accurate power grid model, and the real-time computing ability is difficult to adapt to the frequent voltage fluctuation of power grid including PV. In order to make full use of the reactive power regulation ability of PV, this paper proposes a reactive voltage optimization method including PV. Firstly, a reactive power regulation model of PV with the discrete PV reactive power output is established. Secondly, aiming to minimize voltage deviation and network loss, this paper builds the reactive voltage optimization model including PV based on DQN algorithm. Finally, an example is given to verify the correctness and effectiveness of the proposed method.
UR - https://www.scopus.com/pages/publications/85145660994
M3 - Conference contribution
AN - SCOPUS:85145660994
T3 - AIIPCC 2022 - 3rd International Conference on Artificial Intelligence, Information Processing and Cloud Computing
SP - 215
EP - 219
BT - AIIPCC 2022 - 3rd International Conference on Artificial Intelligence, Information Processing and Cloud Computing
A2 - Zhang, Yu-Dong
PB - VDE VERLAG GMBH
T2 - 3rd International Conference on Artificial Intelligence, Information Processing and Cloud Computing, AIIPCC 2022
Y2 - 21 June 2022 through 22 June 2022
ER -