coordinated voltage control algorithm in distribution networks

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A seminar presentation on
COORDINATED VOLTAGE CONTROL IN DISTRIBUTION
NETWORKS
Presented by G. Vyshnavi 16121D0703
Under the esteemed guidance of Mr. A. PRASAD,
M. Tech. Assistant Professor

Department of Electrical and Electronics
engineering SREE VIDYANIKETHAN ENGINEERING
COLLEGE A. Rangampet, Tirupati -517 102
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Contents

• Objective
• Introduction
• Literature survey
• Proposed CVC algorithms
• Time-domain simulations
• Comparison of CVC algorithms
• Limitations of the algorithms
• Conclusion
• References

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Objective

• The main objective is to mitigate the voltage
  rise problems in distribution networks including
  several DERs, by the use of Coordinated Voltage
  Control (CVC) algorithms.

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Introduction

• Interconnection of the Distributed Generations
  (DGs) at higher penetration levels to the
  distribution networks including several
  Distributed Energy Resources (DER) will arises so
  many technical challenges.
• One of the technical challenges is to maintain
  acceptable voltage level.
• When DG is connected to the radial feeder, its
  active power export reduces the power flow from
  the primary substation and so reduces the voltage
  drop along the feeder.
• If the DG power export is larger than the feeder
  load, power flows from the generator to the
  primary substation and this causes a voltage rise
  along the feeder.

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Literature Survey

• Steady State Voltage Rise and Its Control in
  Distribution System with Distributed Generation
  1
• The main aim is to examine the voltage rise
  problem in practical radial feeder and present
  the conventional and emerging developments in
  steady state voltage regulation methods used for
  distribution network with distributed generation
  (DG) system.
• Disadvantage of this method is installation
  and use of load control for voltage regulation
  alone requires significant capital.
• A Two Ways Communication-Based Distributed
  Control for Voltage Regulation in Smart
  Distribution Feeders 2
• new digital technologies such as monitoring,
  automatic control, and two way communication
  facilities have been applied in this paper to
  construct a distributed control that has the
  capability to provide proper voltage regulation
  in smart distribution feeders.
• Automatic Distributed Voltage Control Algorithm
  in Smart Grids Application3
• In this method, an approach based on sensitivity
  theory is shown to control the network voltage
  using the reactive power exchanged between the
  network and the distributed generators.
• This method does not guarantee the correct
  voltage value in the network nodes when the
  distributed generators deliver their power.

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Cascaded Control Architecture
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Proposed CVC Algorithms

• Two CVC algorithms are used to mitigate the
  voltage
• First algorithm ? Relatively simple rule
  based algorithm
• Second algorithm ? Utilizes optimization
• Two coordinated voltage control algorithms are
  proposed and studied to mitigate the voltage rise
  problems in distribution networks.
• The first one uses a relatively simple rule based
  algorithm and consists of basic and restoring
  parts and the other algorithm utilizes
  optimization.
• The operation of the implemented algorithms is
  studied using time domain simulations and also
  are practical implementation issues are discussed

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Rule Based Algorithm

• In this algorithm substation voltage, real and
  reactive powers of DER are used as a control
  variables.
• The rule based algorithm consists of two control
  algorithms
• 1) Basic control
• 2) Restoring control
• Both basic and restoring control algorithms
  consists of three parts substation voltage
  control , reactive power control and real power
  control.

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Basic Control
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Restoring Control
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Optimizing Algorithm

• The optimization of distribution network voltage
  control is a mixed-integer nonlinear programming
  problem (MINLP).
• The objective function is defined such that it
  will minimize the total costs of network losses
  and generation curtailment.
• Where x The vector of dependent
  variables.
• ud The vector of discrete
  control variables.
• uc The vector of continuous
  control variables.
• Closses The price of losses.
• Plosses The amount of losses.
• Ccur The lost income due to
  curtailment.
• ? Pcur The amount of curtailed
  generation .

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Contd

• The inequality constraints are used to model
  network technical constraints and the capability
  limits of the controllable resources.
• The following constraints are used
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• 
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• ?? ?????? ?? ?? ??????
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• The optimization is realized using MATLAB
  Optimization Toolbox.

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Time Domain Simulations

• For time domain simulations, the considered
  network is simulated to in PSCAD environment and
  the CVC algorithms are implemented in MATLAB
  environment.
• PSCAD includes a MATLAB interface which is used
  to combine the two simulation environments.
• Simulation Network
• The simulation network consists of two 20
  kV feeders that are fed from the same substation.
  The network model is constructed based on a real
  Finnish distribution network.

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Simulation Results for Rule based Algorithm
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Simulation Results for Optimizing Algorithm
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Losses using CVC Algorithms
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Comparison of the CVC Algorithms

• The rule based algorithm proposed in this paper
  is quite simple. Its execution time is short and
  remains in the same range regardless of the
  network situation.
• The execution time of the optimization algorithm
  depends on the number of modeled network nodes
  and controllable re-sources. It can also vary
  significantly depending on the network situation.

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Limitations of the Algorithms

• Designed for typical Finnish distribution
  networks.
• In case of unbalanced networks, the algorithms
  need to be revised.
• State estimation algorithm are applicable only in
  radial networks.
• In the optimizing algorithm, the execution time
  can become too large if the number of
  controllable resources is high.

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Conclusion

• Two CVC algorithms (rule based and optimizing)
  suitable for distribution networks including
  several distributed energy resources are proposed
  and studied. The operation of the proposed
  algorithms is tested using time domain
  simulations and statistical distribution network
  planning is used to compare the network effects
  and costs of the control algorithms.

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References

• 1 L. Yu, D. Czarkowski, and F. de Leon,
  Optimal distributed voltage regulation for
  secondary networks with DGs, IEEE Trans.
  SmartGrid, vol. 3, pp. 959967, Jun. 2012.
• 2 Farag, Hany E., Ehab F. El-Saadany, and Ravi
  Seethapathy. "A two ways communication-based
  distributed control for voltage regulation in
  smart distribution feeders." IEEE Transactions on
  Smart Grid 3.1 (2012) 271-281.
• 3 Pilo, Fabrizio, Giuditta Pisano, and Gian
  Giuseppe Soma. "Optimal coordination of energy
  resources with a two-stage online active
  management." IEEE Transactions on Industrial
  Electronics 58.10 (2011) 4526-4537.
• 4 Borghetti, Alberto, Mauro Bosetti, Samuele
  Grillo, Stefano Massucco, Carlo Alberto Nucci,
  Mario Paolone, and Federico Silvestro.
  "Short-term scheduling and control of active
  distribution systems with high penetration of
  renewable resources." IEEE systems Journal 4, no.
  3 (2010) 313-322.
• 5 A. Viehweider, H. Schichl, D. Burnier de
  Castro, S. Henein, and D.Schwabeneder, Smart
  robust voltage control for distribution networks
  using interval arithmetic and state machine
  concepts, in Proc. Innov. Smart Grid Technol.
  Eur., 2010.
• 6 A. Timbus, M. Larsson, and C. Yuen, Active
  management of distributed energy resources using
  standardized communications and modern
  information technologies, IEEE Trans. Ind.
  Electron., vol. 56, pp. 40294037, Oct. 2009.

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