12 research outputs found
Experimental Validation of a Dynamic Virtual Power Plant Concept Based on Multiple-Converter Power Hardware-In-the-Loop Test Bench
Recently, the concept of dynamic virtual power plants (DVPP) has been
proposed to collectively provide desired dynamic ancillary services such as
fast frequency and voltage control by a heterogeneous ensemble of distributed
energy resources (DER). This paper presents an experimental validation of a
recent DVPP control design approach on a multi-converter power
hardware-in-the-loop (PHIL) test bed system. More specifically, we consider a
DVPP composed of a wind generation system, a photovoltaic (PV) system, and a
STATCOM with small storage capacity to collectively provide grid-following fast
frequency regulation in the presence of grid-frequency and load variations. The
performance of the aggregated DVPP response is evaluated with respect to its
ability to match a desired dynamic behavior while taking practical limitations
of the individual DVPP units into account.Comment: 8 Pages, 11 Figures, 22nd Wind & Solar Integration Workshop 202
Quantitative Stability Conditions for Grid-Forming Converters With Complex Droop Control
In this paper, we study analytically the transient stability of
grid-connected distributed generation systems with grid-forming (GFM) complex
droop control, also known as dispatchable virtual oscillator control (dVOC). We
prove theoretically that complex droop control, as a state-of-the-art GFM
control, always possesses steady-state equilibria whereas classical droop
control does not. We provide quantitative conditions for complex droop control
maintaining transient stability (global asymptotic stability) under grid
disturbances, which is beyond the well-established local (non-global) stability
for classical droop control. For the transient instability of complex droop
control, we reveal that the unstable trajectories are bounded, manifesting as
limit cycle oscillations. Moreover, we extend our stability results from
second-order GFM control dynamics to full-order system dynamics that
additionally encompass both circuit electromagnetic transients and inner-loop
dynamics. Our theoretical results contribute an insightful understanding of the
transient stability and instability of complex droop control and offer
practical guidelines for parameter tuning and stability guarantees
Dynamic Ancillary Services: From Grid Codes to Transfer Function-Based Converter Control
Conventional grid-code specifications for dynamic ancillary services
provision such as fast frequency and voltage regulation are typically defined
by means of piece-wise linear step-response capability curves in the time
domain. However, although the specification of such time-domain curves is
straightforward, their practical implementation in a converter-based generation
system is not immediate, and no customary methods have been developed yet. In
this paper, we thus propose a systematic approach for the practical
implementation of piece-wise linear time-domain curves to provide dynamic
ancillary services by converter-based generation systems, while ensuring
grid-code and device-level requirements to be reliably satisfied. Namely, we
translate the piece-wise linear time-domain curves for active and reactive
power provision in response to a frequency and voltage step change into a
desired rational parametric transfer function in the frequency domain, which
defines a dynamic response behavior to be realized by the converter. The
obtained transfer function can be easily implemented e.g. via a PI-based
matching control in the power loop of standard converter control architectures.
We demonstrate the performance of our method in numerical grid-code compliance
tests, and reveal its superiority over classical droop and virtual inertia
schemes which may not satisfy the grid codes due to their structural
limitations.Comment: 7 pages, 9 figure
MIMO Grid Impedance Identification of Three-Phase Power Systems: Parametric vs. Nonparametric Approaches
A fast and accurate grid impedance measurement of three-phase power systems
is crucial for online assessment of power system stability and adaptive control
of grid-connected converters. Existing grid impedance measurement approaches
typically rely on pointwise sinusoidal injections or sequential wideband
perturbations to identify a nonparametric grid impedance curve via fast Fourier
computations in the frequency domain. This is not only time-consuming, but also
inaccurate during time-varying grid conditions, while on top of that, the
identified nonparametric model cannot be immediately used for stability
analysis or control design. To tackle these problems, we propose to use
parametric system identification techniques (e.g., prediction error or subspace
methods) to obtain a parametric impedance model directly from time-domain
current and voltage data. Our approach relies on injecting wideband excitation
signals in the converter's controller and allows to accurately identify the
grid impedance in closed loop within one injection and measurement cycle. Even
though the underlying parametric system identification techniques are
well-studied in general, their utilization in a grid impedance identification
setup poses specific challenges, is vastly underexplored, and has not gained
adequate attention in urgent and timely power systems applications. To this
end, we demonstrate in numerical experiments how the proposed parametric
approach can accomplish a significant improvement compared to prevalent
nonparametric methods.Comment: 7 pages, 7 figure
Non-convex Feedback Optimization with Input and Output Constraints for Power System Applications
In this thesis, we present a novel control scheme for feedback optimization. That is, we propose a discrete-time controller that can steer the steady state of a physical plant to the solution of a constrained optimization problem without numerically solving the problem. Our controller can be interpreted as a discretization of a continuous-time projected gradient flow and only requires reduced model information in the form of the steady-state input-output sensitivity of the plant. Compared to other schemes used for feedback optimization, such as saddle-point flows or inexact penalty methods, our scheme combines several desirable properties: It asymptotically enforces constraints on the plant outputs, and temporary constraint violations along the trajectory can be easily quantified. Further, as we prove in our main result, global convergence to a minimum is guaranteed even for non-convex problems, and equilibria are feasible regardless of model accuracy. Additionally, our scheme is straightforward to tune, since the step-size is the only tuning parameter. Finally, we numerically verify robustness (in terms of stability) of the closed-loop behavior in the presence of model uncertainty.
For the envisioned application in power systems, we use our novel feedback approach to steady-state optimization for time-varying AC power flow optimization. In numerical experiments, we show that our scheme scales nicely for larger power system setups and exhibits robustness with respect to time-varying generation limits, unobserved demand variations, and a possible model mismatch
Nonlinear Stability of Complex Droop Control in Converter-Based Power Systems
In this letter, we study the nonlinear stability problem of converter-based power systems, where the converter dynamics are governed by a complex droop control. This complex droop control augments the well-known power-frequency (p-f) droop control, and it proves to be equivalent to the state-of-the-art dispatchable virtual oscillator control (dVOC). In this regard, it is recognized as a promising grid-forming solution to address the high penetration of converters in future power systems. In previous work, the global stability of dVOC (i.e., complex droop control) has been proven by prespecifying a nominal synchronous steady state. For a general case of non-nominal (i.e., drooped) synchronous steady states, however, the stability problem requires further investigation. In this letter, we provide parametric conditions under which a non-nominal synchronous steady state exists and the system is almost globally asymptotically stable with respect to this non-nominal synchronous steady state.ISSN:2475-145
Control Design of Dynamic Virtual Power Plants: An Adaptive Divide-and-Conquer Approach
In this paper, we present a novel control approach for dynamic virtual power
plants (DVPPs). In particular, we consider a group of heterogeneous distributed
energy resources (DERs) which collectively provide desired dynamic ancillary
services such as fast frequency and voltage control. Our control approach
relies on an adaptive divide-and-conquer strategy: first, we disaggregate the
desired frequency and voltage control specifications of the aggregate DVPP via
adaptive dynamic participation matrices (ADPMs) to obtain the desired local
behavior for each device. Second, we design local linear parameter-varying
(LPV) controllers to optimally match this local behaviors.
In the process, the control design also incorporates the physical and
engineered limits of each DVPP device. Furthermore, our adaptive control design
can properly respond to fluctuating device capacities, and thus include
weather-driven DERs into the DVPP setup. Finally, we demonstrate the
effectiveness of our control strategy in a case study based on the IEEE
nine-bus system.Comment: 13 pages, 16 figure
Non-Convex Feedback Optimization with Input and Output Constraints
In this letter, we present a novel control scheme for feedback optimization. That is, we propose a discrete-time controller that can steer a physical plant to the solution of a constrained optimization problem without numerically solving the problem. Our controller can be interpreted as a discretization of a continuous-time projected gradient flow. Compared to other schemes used for feedback optimization, such as saddle-point schemes or inexact penalty methods, our control approach combines several desirable properties: it asymptotically enforces constraints on the plant steady-state outputs, and temporary constraint violations can be easily quantified. Our scheme requires only reduced model information in the form of steady-state input-output sensitivities of the plant. Further, global convergence is guaranteed even for non-convex problems. Finally, our controller is straightforward to tune, since the step-size is the only tuning parameter. © 2017 IEEE.ISSN:2475-145
Control Design of Dynamic Virtual Power Plants: An Adaptive Divide-and-Conquer Approach
In this paper, we present a novel control approach for dynamic virtual power plants (DVPPs). In particular, we consider a group of heterogeneous distributed energy resources (DERs) which collectively provide desired dynamic ancillary services such as fast frequency and voltage control. Our control approach relies on an adaptive divide-and-conquer strategy: first, we disaggregate the desired frequency and voltage control specifications of the aggregate DVPP via adaptive dynamic participation matrices (ADPMs) to obtain the desired local behavior for each device. Second, we design local linear parameter-varying (LPV) H∞ controllers to optimally match this local behaviors. In the process, the control design also incorporates the physical and engineered limits of each DVPP device. Furthermore, our adaptive control design can properly respond to fluctuating device capacities, and thus include weather-driven DERs into the DVPP setup. Finally, we demonstrate the effectiveness of our control strategy in a case study based on the IEEE nine-bus system.ISSN:0885-8950ISSN:1558-067