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Power systems optimization under uncertainty: A review of methods and applications
Electric power systems and the companies and customers that interact with them are
experiencing increasing levels of uncertainty due to factors such as renewable energy …
experiencing increasing levels of uncertainty due to factors such as renewable energy …
Active integration of electric vehicles into distribution grids: Barriers and frameworks for flexibility services
Distribution system operators face a challenging environment marked by increased
decentralization, digitalization, and the decarbonization of transport and heating sectors. In …
decentralization, digitalization, and the decarbonization of transport and heating sectors. In …
Uncertainty handling techniques in power systems: A critical review
Integration of renewable generations with electrical power systems has gained considerable
attention in recent years due to environmental and economic benefits. However, this …
attention in recent years due to environmental and economic benefits. However, this …
Distributionally robust joint chance-constrained dispatch for integrated transmission-distribution systems via distributed optimization
This paper focuses on the distributionally robust dispatch for integrated transmission-
distribution (ITD) systems via distributed optimization. Existing distributed algorithms usually …
distribution (ITD) systems via distributed optimization. Existing distributed algorithms usually …
Wasserstein distributionally robust chance-constrained optimization for energy and reserve dispatch: An exact and physically-bounded formulation
In the context of transition towards sustainable, cost-efficient and reliable energy systems,
the improvement of current energy and reserve dispatch models is crucial to properly cope …
the improvement of current energy and reserve dispatch models is crucial to properly cope …
Tractable convex approximations for distributionally robust joint chance-constrained optimal power flow under uncertainty
Uncertainty arising from renewable energy results in considerable challenges in optimal
power flow (OPF) analysis. Various chance-constrained approaches are proposed to …
power flow (OPF) analysis. Various chance-constrained approaches are proposed to …
Data-driven joint distributionally robust chance-constrained operation for multiple integrated electricity and heating systems
Integrating heating and electricity networks offers extra flexibility to the energy system
operation while improving energy utilization efficiency. This paper proposes a data-driven …
operation while improving energy utilization efficiency. This paper proposes a data-driven …
Toward distributed energy services: Decentralizing optimal power flow with machine learning
The implementation of optimal power flow (OPF) methods to perform voltage and power flow
regulation in electric networks is generally believed to require extensive communication. We …
regulation in electric networks is generally believed to require extensive communication. We …
A survey on conic relaxations of optimal power flow problem
Conic optimization has recently emerged as a powerful tool for designing tractable and
guaranteed algorithms for power system operation. On the one hand, tractability is crucial …
guaranteed algorithms for power system operation. On the one hand, tractability is crucial …
Distributionally robust chance-constrained generation expansion planning
This article addresses a centralized generation expansion planning problem, accounting for
both long-and short-term uncertainties. The long-term uncertainty (demand growth) is …
both long-and short-term uncertainties. The long-term uncertainty (demand growth) is …