This chapter assesses the various requirements to facilitate the transition toward active distribution systems (ADSs), introducing a structured framework for short-, medium-, and long-term planning under the new operational paradigm (Planning and optimization methods for active distribution systems – CIGRE working group C6.19. CIGRE, Paris. Brochure 591, 2014). An active distribution system (ADS) is a distribution network in which electricity flows are no longer passively accepted but actively managed through a combination of distributed energy resources (DERs) and advanced control of the grid infrastructure. Flexibility becomes a central planning and operational asset, though it takes different forms depending on its source and maturity. The exploitation of flexibility from DERs—such as generation, controllable loads, and storage—is already being trialed across Europe through pilot projects, regulatory sandboxes, and local market platforms. Demonstrations include PicloFlex (UK), GOPACS (Netherlands), NorFlex (Norway), ENEDIS flexibility tenders (France), SmartFLEX and FLEXIGRID (Portugal), and in Italy projects such as EDGE, MiNDFlex, and RomeFlex (Special report session 5, [Online]. Available: https://www.cired2025.org/media/rsvhyje3/special_report_session-5.pdf ; Celli et al., IEEE Access 12. https://doi.org/10.1109/ACCESS.2024.3421615 , 2024). These initiatives confirm that DER-based flexibility is technically feasible and is becoming an operational resource in network planning. In parallel, a second and complementary form of flexibility arises from the distribution infrastructure itself. Grid-based flexibility—enabled by innovative technologies such as hybrid MVDC/LVDC architectures and soft open points (SOPs)—allows dynamic redistribution of power flows, controlled meshed operation, and enhanced hosting capacity, while preserving radial protection schemes. Though this form of flexibility is still emerging and requires further technological development and investment, its regulatory integration may be simpler, since it relies on DSO-controlled infrastructure rather than market mechanisms (Bathurst et al., MVDC – The New Technology for Distribution Networks. IET Conference Publication, 2015; CIRED Working Group 2019-1. DC networks on the distribution level – new trend or vision? ISSN N°2684-1088 [Online]. Available: https://www.cired.net/working-group/dc-distribution-networks/ ; Zhuang et al., IEEE Trans Power Electron 37:2283–2296. https://doi.org/10.1109/TPEL.2021.3105528 , 2021; Wang and Li, Electr Power Syst Res 227, 2024. https://doi.org/10.1016/j.epsr.2024.110324 ; Zhang et al., CSEE J Power Energy Syst 6, 2020. https://doi.org/10.17775/cseejpes.2020.03660 ; Celli et al., Adoption of soft open points for increasing the flexibility perimeter exploitation on power distribution networks. CIRED 2025, Paper n. 1245; Higuera-Gutierrez and Kazemtabrizi, Network reconfiguration under a stochastic optimisation framework for day-ahead operation planning for future distribution networks. In: IET Conf. Proc., pp. 1603–1607. https://doi.org/10.1049/icp.2023.0963 , 2023; Cao et al., Appl Energy 165:36–47. https://doi.org/10.1016/j.apenergy.2015.12.022 , 2016). Information and Communication Technology (ICT) cannot be considered a simple add-on to the power system; simultaneous analysis (co-simulation) of both power system and ICT system behavior is required for planning, reliability studies, and risk analysis. Smart meters and automatic meter reading (AMR) offer huge volumes of data for load profiling and modeling. Data analytics and big data management are key drivers for planning, as essential insights must be extracted from online measurements, and raw data can increasingly be used directly in real-world planning workflows. ADS planning relies on daily customer profiles represented probabilistically, to reflect the uncertainty and variability of consumption and production behavior across time and location. The growing convergence between planning and operation demands a shift from traditional deterministic approaches to probabilistic, time-series, and multi-objective methodologies. These advanced tools are necessary to fully capture the value of both resource-based and grid-based flexibility. Large-scale studies have demonstrated that such integrated planning frameworks can increase hosting capacity, defer network reinforcements, and support more efficient, risk-aware development pathways aligned with energy transition targets (Celli et al., IEEE Access 12. https://doi.org/10.1109/ACCESS.2024.3421615 , 2024).

Active Distribution Network Operation and Planning

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发表日期：

2026年

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Fabrizio Pilo,
Federico Silvestro

摘要

This chapter assesses the various requirements to facilitate the transition toward active distribution systems (ADSs), introducing a structured framework for short-, medium-, and long-term planning under the new operational paradigm (Planning and optimization methods for active distribution systems – CIGRE working group C6.19. CIGRE, Paris. Brochure 591, 2014). An active distribution system (ADS) is a distribution network in which electricity flows are no longer passively accepted but actively managed through a combination of distributed energy resources (DERs) and advanced control of the grid infrastructure. Flexibility becomes a central planning and operational asset, though it takes different forms depending on its source and maturity. The exploitation of flexibility from DERs—such as generation, controllable loads, and storage—is already being trialed across Europe through pilot projects, regulatory sandboxes, and local market platforms. Demonstrations include PicloFlex (UK), GOPACS (Netherlands), NorFlex (Norway), ENEDIS flexibility tenders (France), SmartFLEX and FLEXIGRID (Portugal), and in Italy projects such as EDGE, MiNDFlex, and RomeFlex (Special report session 5, [Online]. Available: https://www.cired2025.org/media/rsvhyje3/special_report_session-5.pdf ; Celli et al., IEEE Access 12. https://doi.org/10.1109/ACCESS.2024.3421615 , 2024). These initiatives confirm that DER-based flexibility is technically feasible and is becoming an operational resource in network planning. In parallel, a second and complementary form of flexibility arises from the distribution infrastructure itself. Grid-based flexibility—enabled by innovative technologies such as hybrid MVDC/LVDC architectures and soft open points (SOPs)—allows dynamic redistribution of power flows, controlled meshed operation, and enhanced hosting capacity, while preserving radial protection schemes. Though this form of flexibility is still emerging and requires further technological development and investment, its regulatory integration may be simpler, since it relies on DSO-controlled infrastructure rather than market mechanisms (Bathurst et al., MVDC – The New Technology for Distribution Networks. IET Conference Publication, 2015; CIRED Working Group 2019-1. DC networks on the distribution level – new trend or vision? ISSN N°2684-1088 [Online]. Available: https://www.cired.net/working-group/dc-distribution-networks/ ; Zhuang et al., IEEE Trans Power Electron 37:2283–2296. https://doi.org/10.1109/TPEL.2021.3105528 , 2021; Wang and Li, Electr Power Syst Res 227, 2024. https://doi.org/10.1016/j.epsr.2024.110324 ; Zhang et al., CSEE J Power Energy Syst 6, 2020. https://doi.org/10.17775/cseejpes.2020.03660 ; Celli et al., Adoption of soft open points for increasing the flexibility perimeter exploitation on power distribution networks. CIRED 2025, Paper n. 1245; Higuera-Gutierrez and Kazemtabrizi, Network reconfiguration under a stochastic optimisation framework for day-ahead operation planning for future distribution networks. In: IET Conf. Proc., pp. 1603–1607. https://doi.org/10.1049/icp.2023.0963 , 2023; Cao et al., Appl Energy 165:36–47. https://doi.org/10.1016/j.apenergy.2015.12.022 , 2016). Information and Communication Technology (ICT) cannot be considered a simple add-on to the power system; simultaneous analysis (co-simulation) of both power system and ICT system behavior is required for planning, reliability studies, and risk analysis. Smart meters and automatic meter reading (AMR) offer huge volumes of data for load profiling and modeling. Data analytics and big data management are key drivers for planning, as essential insights must be extracted from online measurements, and raw data can increasingly be used directly in real-world planning workflows. ADS planning relies on daily customer profiles represented probabilistically, to reflect the uncertainty and variability of consumption and production behavior across time and location. The growing convergence between planning and operation demands a shift from traditional deterministic approaches to probabilistic, time-series, and multi-objective methodologies. These advanced tools are necessary to fully capture the value of both resource-based and grid-based flexibility. Large-scale studies have demonstrated that such integrated planning frameworks can increase hosting capacity, defer network reinforcements, and support more efficient, risk-aware development pathways aligned with energy transition targets (Celli et al., IEEE Access 12. https://doi.org/10.1109/ACCESS.2024.3421615 , 2024).