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

Venturi, Alberto and Dolan, Michael James and Clarkson, Paul and Wright, Paul and Forbes, Alistair and Yang, Xin-She and Roscoe, Andrew and Ault, Graham and Burt, Graeme (2013) Evaluating the robustness of an active network management function in an operational environment. In: EU EURAMET EMRP Metrology for Smart Grids Workshop, 25-26 June 2013, 2013-07-25 - 2013-07-26.

[thumbnail of Pres_2013_Venturi_EU_EURAMET_EMRP_Robust_active_network_management.pdf] PDF. Filename: Pres_2013_Venturi_EU_EURAMET_EMRP_Robust_active_network_management.pdf
Accepted Author Manuscript

Download (1MB)


Incentives to renewable sources of energy are causing an increase of the number of generators connected to distribution networks. The cost of the network reinforcement are very high and utilities are interested in active network management solutions in order to manage the generator connection to the net, reducing to the minimum the network reinforcement. So, automatic control systems, based on software tools, are becoming more desirable in distribution power systems. Primarily, such schemes are expected to manage system voltage fluctuations, network power flows and fault levels. Functionalities include also power balancing, system frequency control and management of demand side resources for the primary system constraints. A critical concern is the robustness of online and automatic active network management (ANM) algorithms/schemes. The ANM scheme’s functionality depends on convergence to a solution when faced with uncertainty and its reliability can be reduced by data skew and errors. The work presented evaluates power flow management (PFM) functionality based on the Constraint Satisfaction Problem (CSP) in an operational environment. The objective is to assess performances when subjected to different levels of data uncertainty and verify the introduction of a state estimator (SE) in the ANM architecture to mitigate the data uncertainty effects on the control action.