Zobrazeno 1 - 10
of 1 271
pro vyhledávání: '"reactive power optimization"'
Publikováno v:
Energy Science & Engineering, Vol 12, Iss 11, Pp 4904-4917 (2024)
Abstract Distributed power supply access to the distribution network, although it can effectively support the band voltage, will also cause problems such as voltage overruns at the point of grid connection and large network losses, so this paper esta
Externí odkaz:
https://doaj.org/article/5d7168e3a0874a4aa8a50a784510857d
Publikováno v:
电力工程技术, Vol 43, Iss 3, Pp 121-129 (2024)
Aiming at the problem that traditional fixed-weight multi-objective reactive power optimization is unable to make the most suitable control decisions for real-time working conditions when dealing with the complex and changing working conditions of ne
Externí odkaz:
https://doaj.org/article/c7db583a7af848a2aa432b721d3832bf
Publikováno v:
International Journal of Electrical Power & Energy Systems, Vol 164, Iss , Pp 110376- (2025)
Fast reactive power optimization policy-making for various operating scenarios is an important part of power system dispatch. Existing reinforcement learning algorithms alleviate the computational complexity in optimization but suffer from the ineffi
Externí odkaz:
https://doaj.org/article/5830f1afbde14059980bb7cf88aaa04d
Autor:
YAN Limei, DING Zehua
Publikováno v:
Zhejiang dianli, Vol 43, Iss 2, Pp 58-68 (2024)
With a significant increase in the integration of distributed photovoltaic （PV） systems into distribution networks， traditional optimization approaches struggle to effectively mitigate voltage fluctuations， and the reactive power control capa
Externí odkaz:
https://doaj.org/article/83f744167f104d0b97c1436f333fafc5
Autor:
Jinlin Liao, Jia Lin
Publikováno v:
IEEE Access, Vol 12, Pp 113898-113909 (2024)
An actor-critic based distributed deep reinforcement learning approach is proposed to optimize the reactive power of the distribution network under the access of distributed photovoltaics, wind turbines and other power sources. This approach can opti
Externí odkaz:
https://doaj.org/article/17e21fea17a647cf902bef1c62948cce
Autor:
Guozhen Ma, Ning Pang, Yunjia Wang, Shiyao Hu, Xiaobin Xu, Zeya Zhang, Changhong Wang, Liai Gao
Publikováno v:
Energies, Vol 17, Iss 21, p 5429 (2024)
With the proposed “double carbon” target for the power system, large-scale distributed energy access poses a major challenge to the way the distribution grid operates. The rural distribution network (DN) will transform into a new local power syst
Externí odkaz:
https://doaj.org/article/96e057e95dad454983ba56a8934b57ea
Publikováno v:
EAI Endorsed Transactions on Energy Web, Vol 11 (2024)
The vigorous development of new energy has effectively reduced carbon emissions, but it has also brought fluctuating impacts on the carrying capacity of the power grid. In order to improve the voltage stability after integrating new energy sources an
Externí odkaz:
https://doaj.org/article/973589bf0450452d83bee17213f6ca1f
Publikováno v:
电力工程技术, Vol 42, Iss 6, Pp 74-82 (2023)
When the distributed photovoltaics enters the stage of extremely high proportion penetration, the problem of over-limit voltage in the distribution network becomes more prominent. A variety of adjustable resources in the distribution network are used
Externí odkaz:
https://doaj.org/article/84870a224f984622ae487be3f4e5030d
Publikováno v:
Energies, Vol 17, Iss 16, p 3910 (2024)
With the integration of large-scale wind power clusters into the power system, wind farms play a crucial role in grid reactive power regulation. However, the range of its reactive power remains uncertain, posing challenges in formulating a viable pro
Externí odkaz:
https://doaj.org/article/1572b1d53a674fac82d9ac9e287967c0
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 1888-1896 (2023)
Electric vehicle (EV) charging, and discharging have an important reactive power support capability for the distribution network, for which a reactive power optimization method considering EV dis-/charging is proposed. Firstly, the principle of charg
Externí odkaz:
https://doaj.org/article/b66c59c2fa0a4d96a8f7c9de6ed9a279