Planning and Optimization Methods for Active Distribution Systems

The CIGRÉ C6 Study Committee (Distribution Systems and Dispersed Generation) considers the different aspects of integration of distributed generation. In this context, the C6.19 Working Group (WG) is specifically focused on “Planning and optimization methods for active distribution systems”. This report assesses the various requirements to facilitate the transition towards active distribution systems (ADSs). Specifically, the report starts from a survey of requirements of planning methodologies and identifies a new framework and methodologies for short, medium and long term models for active distribution planning. Active distribution networks (ADNs) have systems in place to control a combination of distributed energy resources (DERs), defined as generators, loads and storage. With these systems in place, the AND becomes an Active Distribution System (ADS). Distribution system operators (DSOs) have the possibility of managing the electricity flows using a flexible network topology. DERs take some degree of responsibility for system support, which depends on suitable regulatory environments and connection agreements. Distribution operation and planning stages can no longer be considered as separate tasks in the distribution business since the exploitation of existing assets with Advanced Automation and Control may be a valuable alternative to network expansion or reinforcement. Information and communication technology (ICT) cannot be considered as a simple add-on of the power system and simultaneous analysis (co-simulation) of both power system and ICT system behavior is required for planning and reliability studies, as well as risk analysis. Smart meters and automatic meter reading (AMR) offer a huge amount of data for load profiling and modelling. Data analytics and big data are key drivers for planning, since essential information has to be captured from on line measurement and raw data be used directly in real world planning applications. The ADS planning asks for daily customers profile with a probabilistic representation to take account of uncertainties that characterize their behaviour. Finally, interesting methodologies and models have been extracted from relevant publications. Particular attention has been paid to the planning tools, which are ready to be transferred into scaled industrial applications by means of strong interaction with R&D distribution company centres and Academia.