16,599 research outputs found
Pseudo-gradient Based Local Voltage Control in Distribution Networks
Voltage regulation is critical for power grids. However, it has become a much
more challenging problem as distributed energy resources (DERs) such as
photovoltaic and wind generators are increasingly deployed, causing rapid
voltage fluctuations beyond what can be handled by the traditional voltage
regulation methods. In this paper, motivated by two previously proposed
inverter-based local volt/var control algorithms, we propose a pseudo-gradient
based voltage control algorithm for the distribution network that does not
constrain the allowable control functions and has low implementation
complexity. We characterize the convergence of the proposed voltage control
scheme, and compare it against the two previous algorithms in terms of the
convergence condition as well as the convergence rate
Reverse and Forward Engineering of Local Voltage Control in Distribution Networks
The increasing penetration of renewable and distributed energy resources in distribution networks calls for real-time and distributed voltage control. In this paper we investigate local Volt/VAR control with a general class of control functions, and show that the power system dynamics with non-incremental local voltage control can be seen as a distributed algorithm for solving a well-defined optimization problem (reverse engineering). The reverse engineering further reveals a fundamental limitation of the non-incremental voltage control: the convergence condition is restrictive and prevents better voltage regulation at equilibrium. This motivates us to design two incremental local voltage control schemes based on the subgradient and pseudo-gradient algorithms respectively for solving the same optimization problem (forward engineering). The new control schemes decouple the dynamical property from the equilibrium property, and have much less restrictive convergence conditions. This work presents another step towards developing a new foundation - network dynamics as optimization algorithms - for distributed real-time control and optimization of future power networks
Reverse and Forward Engineering of Local Voltage Control in Distribution Networks
The increasing penetration of renewable and distributed energy resources in
distribution networks calls for real-time and distributed voltage control. In
this paper we investigate local Volt/VAR control with a general class of
control functions, and show that the power system dynamics with non-incremental
local voltage control can be seen as distributed algorithm for solving a
well-defined optimization problem (reverse engineering). The reverse
engineering further reveals a fundamental limitation of the non-incremental
voltage control: the convergence condition is restrictive and prevents better
voltage regulation at equilibrium. This motivates us to design two incremental
local voltage control schemes based on the subgradient and pseudo-gradient
algorithms respectively for solving the same optimization problem (forward
engineering). The new control schemes decouple the dynamical property from the
equilibrium property, and have much less restrictive convergence conditions.
This work presents another step towards developing a new foundation -- network
dynamics as optimization algorithms -- for distributed realtime control and
optimization of future power networks
Congestion avoidance for recharging electric vehicles using smoothed particle hydrodynamics
In this paper, a novel approach for recharging electric vehicles (EVs) is proposed based on managing multiple discrete units of electric power flow, named energy demand particles (EDPs). Key similarities between EDPs and fluid particles (FPs) are established that allow the use of a smoothed particle hydrodynamics (SPH) method for scheduling the recharging times of EVs. It is shown, via simulation, that the scheduling procedure not only minimizes the variance of voltage drops in the secondary circuits, but it also can be used to implement a dynamic demand response and frequency control mechanism. The performance of the proposed scheduling procedure is also compared with alternative approaches recently published in the literature
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