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Active Network Management is a philosophy for the operation of distribution networks with high penetrations of renewable distributed generation. Technologies such as energy storage and flexible demand are now beginning to be included in Active Network Management (ANM) schemes. Optimizing the operation of these schemes requires consideration of intertemporal linkages as well as network power flow effects. Network effects are included in Optimal Power Flow (OPF) solutions but this only optimizes for a single point in time. Dynamic Optimal Power Flow (DOPF) is an extension of OPF to cover multiple time periods. This paper reviews the generic formulation of Dynamic Optimal Power Flow before developing a framework for modeling energy technologies with inter-temporal characteristics in an ANM context. The framework includes the optimization of nonfirm connected generation, Principles of Access for non-firm generators, energy storage and flexible demand. Two objectives based on maximizing export and revenue are developed and a case study is used to illustrate the technique. Results show that DOPF is able to successfully schedule these energy technologies. DOPF schedules energy storage and flexible demand to reduce generator curtailment significantly in the case study. Finally the role of DOPF in analyzing ANM schemes is discussed with reference to extending the optimization framework to include other technologies and objectives. Index Terms-Energy storage, Flexible demand, Active Network Management, OPF, dynamic optimal power flow I. NOMENCLATURE 1 General DOPF Vector of OPF control variables Vector of OPF fixed parameters Vector of intertemporal variables Vector of OPF derived variables Objective function OPF equality constraints OPF inequality constraints Intertemporal equality constraints Intertemporal inequality constraints This work is partly funded through the in Wind Energy Systems Centre for Doctoral Training at the University of Strathclyde. EPSRC EP/G037728/1.

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The rollout of smart meters raises the prospect that domestic customer electrical demand can be responsive to changes in supply capacity. Such responsive demand will become increasingly relevant in electrical power systems, as the proportion of weather-dependent renewable generation increases, due to the difficulty and expense of storing electrical energy. One method of providing response is to allow direct control of customer devices by network operators, as in the UK 'Economy 7' and 'White Meter' schemes used to control domestic electrical heating. However, such direct control is much less acceptable for loads such as washing machines, lighting and televisions. This study instead examines the use of real-time pricing of electricity in the domestic sector. This allows customers to be flexible but, importantly, to retain overall control. A simulation methodology for highlighting the potential effects of, and possible problems with, a national implementation of real-time pricing in the UK domestic electricity market is presented. This is done by disaggregating domestic load profiles and then simulating price-based elastic and load-shifting responses. Analysis of a future UK scenario with 15 GW wind penetration shows that during low-wind events, UK peak demand could be reduced by 8-11 GW. This could remove the requirement for 8-11 GW of standby generation with a capital cost of £2.6 to £3.6 billion. Recommended further work is the investigation of improved demand-forecasting and the price-setting strategies. This is a fine balance between giving customers access to plentiful, cheap energy when it is available, but increasing prices just enough to reduce demand to meet the supply capacity when this capacity is limited

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