Active distribution system management: A dual-horizon scheduling framework for DSO/TSO interface under uncertainty
Open accessAbstract
Active distribution system management (ADSM) aims at optimally operating distribution network assets with a high penetration of distributed energy resources (DERs) while taking into account operational uncertainties, market constraints, and scheduled power flows at the interface with the transmission system. A novel framework for ADSM, which incorporates a dual-horizon rolling scheduling model based on dynamic ac optimal power flow, is proposed in this paper. In the first stage (planning), energy import/export is committed for given times ahead at the grid supply point considering local variable generation and load forecasts. At the second stage (operation) deviations from the schedules are minimised by controlling various assets and DER, including electrical energy storage (EES). We demonstrate how crucial it is to properly consider uncertainties (for instance, associated with forecasts) over different time scales. Case study results on a real U.K. distribution network show that the proposed ADSM approach can provide credible operational strategies to maximise renewable penetration, minimize deviations from time-ahead schedules, and estimate the required level of local reserves from dispatchable generation and EES while realistically accounting for uncertainty. The framework and model formulation proposed can thus be seen as a key tool to facilitate the transition from distribution network operators to distribution system operators and their interaction with transmission sys…
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The exact AC power flow formulation would make the problem nonconvex and NP-hard, and mixed-integer applications proved untractable with present MINLP solvers.
“The use of the exact ('AC') power flow formulation would make the problem nonconvex and NPhard [22], and mixed-integer applications proved untractable with present MINLP solvers [35].”
From Congestion mitigation in unbalanced residential networks with OPF-based demand management (2022) · cites this paper as [35]
Bound tightening is an effective method to bridge the gap between solutions from approximated power flow models and exact models.
“Bound tightening has recently been proved an effective method to bridge the gap between solutions from approximated power flow models and exact models [35], [44].”
From Congestion mitigation in unbalanced residential networks with OPF-based demand management (2022) · cites this paper as [35]
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- Authors
- Saint-Pierre, A., & Mancarella, P.
- Affiliations
- University of Manchester (GB)
- Venue
- IEEE Transactions on Smart Grid
- Published
- 2017-09
- Volume
- 8
- Issue
- 5
- Pages
- 2186-2197
- ISSN
- 1949-3053 (ISSN-L)
- 1949-3061
- OpenAlex
- W2313092143
- Cited by
- 190
- References
- 26
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 18 · 2023: 21 · 2022: 32 · 2021: 25 · 2020: 18 · 2019: 31 · 2018: 13 · 2017: 11 · 2016: 5
- FWCI
- 9.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- IEEE Transactions on Smart Grid (publishedVersion, cc-by)
- Research Explorer (The University of Manchester) (publishedVersion, other-oa)
- Funders
- Engineering and Physical Sciences Research Council through the HubNet Programme (EP/I013636/1)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Keywords
- distribution system operators, distributed energy resources, energy storage, forecast uncertainty, renewable energy penetration, distribution network operation
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