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 …
Critical review of recent advances and further developments needed in AC optimal power flow
F Capitanescu - Electric Power Systems Research, 2016 - Elsevier
This paper is a sequel to and builds upon the survey paper on optimal power flow (OPF)[4]. It
provides an up-to-date critical review of the recent major advancements in the OPF state-of …
provides an up-to-date critical review of the recent major advancements in the OPF state-of …
Distributionally robust chance-constrained optimal power flow with uncertain renewables and uncertain reserves provided by loads
Aggregations of electric loads can provide reserves to power systems, but their available
reserve capacities are time-varying and not perfectly known when the system operator …
reserve capacities are time-varying and not perfectly known when the system operator …
Chance-constrained AC optimal power flow: Reformulations and efficient algorithms
Higher levels of renewable electricity generation increase uncertainty in power system
operation. To ensure secure system operation, new tools that account for this uncertainty are …
operation. To ensure secure system operation, new tools that account for this uncertainty are …
Chance-constrained optimal power flow: Risk-aware network control under uncertainty
When uncontrollable resources fluctuate, optimal power flow (OPF), routinely used by the
electric power industry to redispatch hourly controllable generation (coal, gas, and hydro …
electric power industry to redispatch hourly controllable generation (coal, gas, and hydro …
Data-driven local control design for active distribution grids using off-line optimal power flow and machine learning techniques
The optimal control of distribution networks often requires monitoring and communication
infrastructure, either centralized or distributed. However, most of the current distribution …
infrastructure, either centralized or distributed. However, most of the current distribution …
Energy storage sizing taking into account forecast uncertainties and receding horizon operation
Energy storage systems (ESS) have the potential to be very beneficial for applications such
as reducing the ram** of generators, peak shaving, and balancing not only the variability …
as reducing the ram** of generators, peak shaving, and balancing not only the variability …
Data-based distributionally robust stochastic optimal power flow—Part I: Methodologies
We propose a data-based method to solve a multi-stage stochastic optimal power flow (OPF)
problem based on limited information about forecast error distributions. The framework …
problem based on limited information about forecast error distributions. The framework …
Data-driven decision making in power systems with probabilistic guarantees: Theory and applications of chance-constrained optimization
Uncertainties from deepening penetration of renewable energy resources have posed
critical challenges to the secure and reliable operations of future electric grids. Among …
critical challenges to the secure and reliable operations of future electric grids. Among …
Corrective control to handle forecast uncertainty: A chance constrained optimal power flow
Higher shares of electricity generation from renewable energy sources and market
liberalization is increasing uncertainty in power systems operation. At the same time …
liberalization is increasing uncertainty in power systems operation. At the same time …