Abstract

Congestion management is one of the core enablers of smart distribution systems where distributed energy resources are utilised in network control to enable cost-effective network interconnection of distributed generation (DG) and better utilisation of network assets. The primary aim of congestion management is to prevent voltage violations and network overloading. Congestion management algorithms can also be used to optimise the network state. This study proposes a hierarchical and distributed congestion management concept for future distribution networks having large-scale DG and other controllable resources in MV and LV networks. The control concept aims at operating the network at minimum costs while retaining an acceptable network state. The hierarchy consists of three levels: primary controllers operate based on local measurements, secondary control optimises the set points of the primary controllers in real-time and tertiary control utilises load and production forecasts as its inputs and realises network reconfiguration algorithm and connection to the market. Primary controllers are located at the connection point of the controllable resource, secondary controllers at primary and secondary substations and tertiary control at the control centre. Hence, the control is spatially distributed and operates in different time frames.

Highlights

  • The amount of distributed generation (DG) is constantly increasing and other controllable resources such as controllable loads, electric vehicles and energy storages are becoming more common in distribution networks

  • Active network management methods can be used to mitigate voltage rise caused by DG or prevent network overloading

  • The proposed methods range from simple methods based only on local measurements to advanced methods utilising all DERs in a coordinated manner

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Summary

Introduction

The amount of distributed generation (DG) is constantly increasing and other controllable resources such as controllable loads, electric vehicles and energy storages are becoming more common in distribution networks. Methods can operate in real-time based on measurements or state estimation data In the methods that operate based on forecasts, the execution time is not that critical and it is possible to consider the whole control horizon in the calculations. The accuracy of these methods, depends on the accuracy of the load and production forecasts. The amount of input measurement data and controllable resources that they can handle is, limited by data transfer and computational limitations, i.e. they are not scalable They are vulnerable to component failures since all the data transfer is to and from one centralised controller. The control concept is scalable and modular and enables easy addition of new DERs to the system

Distributed automation architecture and control system hierarchy
Interactions of the control system
Day-ahead time frame
Intra-hour time frame
Real-time time frame
Secondary control
Real-time power control
Offline cost parameter update
Tertiary control
Network reconfiguration
Market agent
Simulation results
Tertiary control results
Secondary control results
Findings
Conclusions
Full Text
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