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      Receding-horizon OPF for real-time management of distribution networks

      research-article
      , ,
      IET Generation, Transmission & Distribution
      The Institution of Engineering and Technology
      power system management, distributed power generation, power generation scheduling, power distribution control, power generation economics, power generation dispatch, receding-horizon OPF, real-time management, distribution networks, real-time active network management control, ANM control, energy yield maximization, distributed generation, coordinated scheduling, renewable DG, distribution network control assets, DG curtailment, energy yield, economic performance, optimal power flow, OPF, single-time frame snapshot formulations, narrow interpretation, temporal constraint, control real-time ANM, spatially-variable renewable DG, temporally-variable renewable DG, time sequences, system dispatch

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          Abstract

          This study presents a new formulation for real-time active network management (ANM) control of distribution networks to maximise energy yield from distributed generation (DG). Coordinated scheduling of renewable DG and distribution network control assets can limit DG curtailment and significantly increase energy yield and economic performance of DG in weak or congested networks. Optimal power flow (OPF) has been employed in the literature for this purpose. However, single time frame snapshot formulations are limited by their narrow interpretation of temporal constraints. Here a formulation is presented for a new receding-horizon OPF technique to better control real-time ANM in distribution networks with high levels of temporally and spatially variable renewable DG. It is shown to improve the coordination between time sequences of system dispatch and improve voltage performance.

          Most cited references19

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          Demand side management: Benefits and challenges

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            Summary of Distributed Resources Impact on Power Delivery Systems

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              Distribution Network Capacity Assessment: Variable DG and Active Networks

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                Author and article information

                Contributors
                Journal
                IET-GTD
                IET Generation, Transmission & Distribution
                IET Gener. Transm. Distrib.
                The Institution of Engineering and Technology
                1751-8687
                1751-8695
                25 January 2018
                14 March 2018
                15 May 2018
                : 12
                : 9
                : 2124-2131
                Affiliations
                School of Engineering, University of Edinburgh , King's Buildings, Edinburgh, UK
                Article
                IET-GTD.2016.1939 GTD.SI.2016.1939.R2
                10.1049/iet-gtd.2016.1939
                32f63840-dee0-454a-a08e-c8509f4b114c

                This is an open access article published by the IET under the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/)

                History
                : 30 November 2016
                : 22 November 2017
                : 11 January 2018
                Page count
                Pages: 0
                Categories
                Research Article

                Computer science,Engineering,Artificial intelligence,Electrical engineering,Mechanical engineering,Renewable energy
                OPF,distributed generation,economic performance,coordinated scheduling,receding-horizon OPF,real-time active network management control,ANM control,time sequences,distribution network control assets,distribution networks,temporal constraint,DG curtailment,power distribution control,optimal power flow,power generation dispatch,distributed power generation,system dispatch,energy yield,narrow interpretation,real-time management,temporally-variable renewable DG,spatially-variable renewable DG,control real-time ANM,power generation economics,single-time frame snapshot formulations,renewable DG,power generation scheduling,energy yield maximization,power system management

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