This paper presents a risk-based advanced distribution network management system (NMS) aimed at maximizing wind energy harvesting while simultaneously managing congestion and voltages. The NMS allows the adoption of multi-minute control cycles so the volume of actions from on-load tap changers (OLTCs) and distributed generation (DG) plants can be reduced while effectively catering for the effects of wind power uncertainties. This work presents the quantification of benefits and impacts from adopting different control cycles as well a comparison with a deterministic approach. The risk-based approach is implemented by adapting and expanding an AC optimal power flow.

A risk level is used to determine the extent to which congestion and voltage rise could exist during a control cycle. The proposed NMS is applied to a real-life U.K. MV network from the North West of England to assess its effectiveness in managing high penetration of wind power considering minute-by-minute simulations for one week. The results show that the risk-based approach can effectively manage network constraints better than the deterministic approach, particularly for multi-minute control cycles, reducing also the number of control actions but at the expense of higher levels of curtailment.

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