Evaluating the robustness of an active network management function in an operational environment

Alberto Venturi, Michael James Dolan, Paul Clarkson, Paul Wright, Alistair Forbes, Xin-She Yang, Andrew Roscoe, Graham Ault, Graeme Burt

Research output: Contribution to conferencePaper

Abstract

This paper presents the integration process of a distribution network Active Network Management (ANM) function within an operational environment in the form of a Micro-Grid Laboratory. This enables emulation of a real power network and enables investigation into the effects of data uncertainty on an online and automatic ANM algorithm's control decisions. The algorithm implemented within the operational environment is a Power Flow Management (PFM) approach based around the Constraint Satisfaction Problem (CSP). This paper show the impact of increasing uncertainty, in the input data available for an ANM scheme in terms of the variation in control actions. The inclusion of a State Estimator (SE), with known tolerances is shown to improve the ANM performance.

Conference

ConferenceCIRED 2013, 22nd International Conference on Electricity Distribution
CountrySweden
CityStockholm
Period10/06/1313/06/13

Fingerprint

Active networks
Network management
Constraint satisfaction problems
Electric power distribution
Uncertainty

Keywords

  • active network management
  • power flow management
  • constraint satisfaction

Cite this

Venturi, A., Dolan, M. J., Clarkson, P., Wright, P., Forbes, A., Yang, X-S., ... Burt, G. (2013). Evaluating the robustness of an active network management function in an operational environment. Paper presented at CIRED 2013, 22nd International Conference on Electricity Distribution, Stockholm, Sweden.
Venturi, Alberto ; Dolan, Michael James ; Clarkson, Paul ; Wright, Paul ; Forbes, Alistair ; Yang, Xin-She ; Roscoe, Andrew ; Ault, Graham ; Burt, Graeme. / Evaluating the robustness of an active network management function in an operational environment. Paper presented at CIRED 2013, 22nd International Conference on Electricity Distribution, Stockholm, Sweden.
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author = "Alberto Venturi and Dolan, {Michael James} and Paul Clarkson and Paul Wright and Alistair Forbes and Xin-She Yang and Andrew Roscoe and Graham Ault and Graeme Burt",
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Venturi, A, Dolan, MJ, Clarkson, P, Wright, P, Forbes, A, Yang, X-S, Roscoe, A, Ault, G & Burt, G 2013, 'Evaluating the robustness of an active network management function in an operational environment' Paper presented at CIRED 2013, 22nd International Conference on Electricity Distribution, Stockholm, Sweden, 10/06/13 - 13/06/13, .

Evaluating the robustness of an active network management function in an operational environment. / Venturi, Alberto; Dolan, Michael James; Clarkson, Paul; Wright, Paul; Forbes, Alistair; Yang, Xin-She; Roscoe, Andrew; Ault, Graham; Burt, Graeme.

2013. Paper presented at CIRED 2013, 22nd International Conference on Electricity Distribution, Stockholm, Sweden.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Evaluating the robustness of an active network management function in an operational environment

AU - Venturi, Alberto

AU - Dolan, Michael James

AU - Clarkson, Paul

AU - Wright, Paul

AU - Forbes, Alistair

AU - Yang, Xin-She

AU - Roscoe, Andrew

AU - Ault, Graham

AU - Burt, Graeme

PY - 2013/6/10

Y1 - 2013/6/10

N2 - This paper presents the integration process of a distribution network Active Network Management (ANM) function within an operational environment in the form of a Micro-Grid Laboratory. This enables emulation of a real power network and enables investigation into the effects of data uncertainty on an online and automatic ANM algorithm's control decisions. The algorithm implemented within the operational environment is a Power Flow Management (PFM) approach based around the Constraint Satisfaction Problem (CSP). This paper show the impact of increasing uncertainty, in the input data available for an ANM scheme in terms of the variation in control actions. The inclusion of a State Estimator (SE), with known tolerances is shown to improve the ANM performance.

AB - This paper presents the integration process of a distribution network Active Network Management (ANM) function within an operational environment in the form of a Micro-Grid Laboratory. This enables emulation of a real power network and enables investigation into the effects of data uncertainty on an online and automatic ANM algorithm's control decisions. The algorithm implemented within the operational environment is a Power Flow Management (PFM) approach based around the Constraint Satisfaction Problem (CSP). This paper show the impact of increasing uncertainty, in the input data available for an ANM scheme in terms of the variation in control actions. The inclusion of a State Estimator (SE), with known tolerances is shown to improve the ANM performance.

KW - active network management

KW - power flow management

KW - constraint satisfaction

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M3 - Paper

ER -

Venturi A, Dolan MJ, Clarkson P, Wright P, Forbes A, Yang X-S et al. Evaluating the robustness of an active network management function in an operational environment. 2013. Paper presented at CIRED 2013, 22nd International Conference on Electricity Distribution, Stockholm, Sweden.