Abstract
In this paper, we propose a framework for coordinating distributed energy resources (DERs) connected to a power distribution system, the model of which is not completely known, so that they collectively provide a specified amount of active power to the bulk power system, while respecting distribution line capacity limits. The proposed framework consists of a linear time-varying input-output (IO) system model that represents the relation between the DER active power injections (inputs), and the total active power exchanged between the distribution and bulk power systems (output); an estimator that aims to estimate the IO model parameters; and a controller that determines the optimal DER active power injections so that the power exchanged between both systems equals to the specified amount at a minimum generating cost. We formulate the estimation problem as a box-constrained quadratic program and solve it using the projected gradient descent algorithm. To resolve the potential issue of collinearity in the measurements, we introduce random perturbations in the DER active power injections during the estimation process. Using the estimated IO model, the optimal DER coordination problem to be solved by the controller can be formulated as a convex optimization problem, which can be solved easily. The effectiveness of the framework is validated via numerical simulations using the IEEE 123-bus distribution test feeder.
| Original language | English (US) |
|---|---|
| Article number | 8642451 |
| Pages (from-to) | 3047-3058 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 34 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jul 2019 |
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Keywords
- Data-driven
- active power provision
- coordination
- distributed energy resource
- parameter estimation
- projected gradient descent
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
Cite this
Data-Driven Coordination of Distributed Energy Resources for Active Power Provision. / Xu, Hanchen; Dominguez-Garcia, Alejandro; Sauer, Peter W.
In: IEEE Transactions on Power Systems, Vol. 34, No. 4, 8642451, 07.2019, p. 3047-3058.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Data-Driven Coordination of Distributed Energy Resources for Active Power Provision
AU - Xu, Hanchen
AU - Dominguez-Garcia, Alejandro
AU - Sauer, Peter W
PY - 2019/7
Y1 - 2019/7
N2 - In this paper, we propose a framework for coordinating distributed energy resources (DERs) connected to a power distribution system, the model of which is not completely known, so that they collectively provide a specified amount of active power to the bulk power system, while respecting distribution line capacity limits. The proposed framework consists of a linear time-varying input-output (IO) system model that represents the relation between the DER active power injections (inputs), and the total active power exchanged between the distribution and bulk power systems (output); an estimator that aims to estimate the IO model parameters; and a controller that determines the optimal DER active power injections so that the power exchanged between both systems equals to the specified amount at a minimum generating cost. We formulate the estimation problem as a box-constrained quadratic program and solve it using the projected gradient descent algorithm. To resolve the potential issue of collinearity in the measurements, we introduce random perturbations in the DER active power injections during the estimation process. Using the estimated IO model, the optimal DER coordination problem to be solved by the controller can be formulated as a convex optimization problem, which can be solved easily. The effectiveness of the framework is validated via numerical simulations using the IEEE 123-bus distribution test feeder.
AB - In this paper, we propose a framework for coordinating distributed energy resources (DERs) connected to a power distribution system, the model of which is not completely known, so that they collectively provide a specified amount of active power to the bulk power system, while respecting distribution line capacity limits. The proposed framework consists of a linear time-varying input-output (IO) system model that represents the relation between the DER active power injections (inputs), and the total active power exchanged between the distribution and bulk power systems (output); an estimator that aims to estimate the IO model parameters; and a controller that determines the optimal DER active power injections so that the power exchanged between both systems equals to the specified amount at a minimum generating cost. We formulate the estimation problem as a box-constrained quadratic program and solve it using the projected gradient descent algorithm. To resolve the potential issue of collinearity in the measurements, we introduce random perturbations in the DER active power injections during the estimation process. Using the estimated IO model, the optimal DER coordination problem to be solved by the controller can be formulated as a convex optimization problem, which can be solved easily. The effectiveness of the framework is validated via numerical simulations using the IEEE 123-bus distribution test feeder.
KW - Data-driven
KW - active power provision
KW - coordination
KW - distributed energy resource
KW - parameter estimation
KW - projected gradient descent
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UR - http://www.scopus.com/inward/citedby.url?scp=85067811116&partnerID=8YFLogxK
U2 - 10.1109/TPWRS.2019.2899451
DO - 10.1109/TPWRS.2019.2899451
M3 - Article
AN - SCOPUS:85067811116
VL - 34
SP - 3047
EP - 3058
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
SN - 0885-8950
IS - 4
M1 - 8642451
ER -