Zobrazeno 1 - 10
of 1 460
pro vyhledávání: '"Chance-constraints"'
Publikováno v:
International Journal of Electrical Power & Energy Systems, Vol 163, Iss , Pp 110319- (2024)
This paper proposes a stochastic strategic bidding approach for a multi-energy microgrid (MEMG) to optimize its participation across electricity, thermal energy, and hydrogen markets. A MEMG powered entirely by renewable energy and integrating these
Externí odkaz:
https://doaj.org/article/a515d0978e1b40a1ad88e060f02c2a29
Autor:
Danyang Xu, Zhigang Wu
Publikováno v:
International Journal of Electrical Power & Energy Systems, Vol 162, Iss , Pp 110310- (2024)
This paper introduces an enhanced frequency aware microgrid scheduling (E-FAMS) model designed to achieve seamless islanding (SI) for microgrids after experiencing an unintentional islanding event (UIE). The model addresses uncertainties in load fore
Externí odkaz:
https://doaj.org/article/a34fea923f89489abf451f869689e486
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
Compared to traditional resources, user-side resources are of various types and have more significant uncertainty about their regulatory capacity, leading to difficulties in coordinating decisions about their simultaneous participation in the electri
Externí odkaz:
https://doaj.org/article/02d0595e34e340bea1c0a7abf4b96ea7
Publikováno v:
电力工程技术, Vol 43, Iss 3, Pp 78-87 (2024)
Within the context of carbon peaking and neutrality, carbon capture plants can effectively reduce carbon emissions in power systems. Yet, the regular integration of these units for peak shaving in grids harnessing renewable energy tends to hamper sys
Externí odkaz:
https://doaj.org/article/6425eecedb9841719af4e17781e99aa4
Publikováno v:
Journal of Engineering and Applied Science, Vol 71, Iss 1, Pp 1-31 (2024)
Abstract In the forthcoming decades, significant advancements will shape the construction and operations of distribution systems. Particularly, the increasing prominence of photovoltaic (PV) systems in the power industry will impact the security of t
Externí odkaz:
https://doaj.org/article/ceb354497cf242c7b12fb77190d59eb2
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
The distribution grid experiences node voltage fluctuations due to the growing uncertainty of large-scale renewable energy sources A practical solution is establishing a chance-constrained optimal model to deal with the uncertainties. However, using
Externí odkaz:
https://doaj.org/article/f20086593b49487e8ad2fb9b68fd2c46
Autor:
Murat Cal, Sibel Atan
Publikováno v:
Journal of Applied Science and Engineering, Vol 27, Iss 5, Pp 2453-2460 (2024)
Nonlinear mathematical models are widely used better to reflect the stochastic structure of financial investment problems and to express them numerically. However, in some real-life situations, it is necessary to consider not only one purpose but man
Externí odkaz:
https://doaj.org/article/f64373c45fb14ec687ad1ea569e9c9cd
Publikováno v:
IEEE Open Journal of Control Systems, Vol 3, Pp 282-294 (2024)
This paper presents a fully risk-aware model predictive control (MPC) framework for chance-constrained discrete-time linear control systems with process noise. Conditional value-at-risk (CVaR) as a popular coherent risk measure is incorporated in bot
Externí odkaz:
https://doaj.org/article/1bae460e39b5449aa286b693ece454c2
Publikováno v:
IEEE Access, Vol 12, Pp 86869-86885 (2024)
Large-scale integration of renewable energy sources with their intermittent output is introducing new challenges for system operators. The challenge arises from imperfect wind and solar forecasts that lead to deviations in electricity production in r
Externí odkaz:
https://doaj.org/article/edfd039c60d5480cb0285d1b0c11f260
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
This paper proposes an optimal power flow model that takes into account the uncertainty in the probability distribution of wind power. The model can schedule controllable generators under any possible distribution of wind power to ensure the safe and
Externí odkaz:
https://doaj.org/article/3256e8b3d4a54332921d2103e16310b8