Distributed generation (DG), whose installed capacity is increasing rapidly, can be defined as low rating generation that is neither planned nor dispatched centrally and is usually connected to the distribution network. Appropriate control of DG can improve the performance of DG units without violating network constraints, and facilitate the effective participation of DG in power system and market operation. Two control levels, DG unit control and network control, are summarized. DG unit control is introduced based on three technologies: induction generators, synchronous generators and power electric converters. Effective network control can be built based upon active management concept. Finally, three DG control paradigms, MicroGrid, cell and virtual power plant, are discussed. Steuerung der dezentralen Erzeugung. Dezentrale Erzeugung kann als Erzeugung geringerer Leistung bezeichnet werden, die an das Verteilnetz angeschlossen ist, jedoch ohne zentrale Planung und zentrale Einspeisung in das Netz auskommt. Eine geeignete Steuerung der dezentralen Erzeugung kann deren Leistung erheblich verbessern, ohne Netzbegrenzungen zu verletzen, und erleichtert damit eine erfolgreiche Beteiligung im Stromnetz und am Strommarkt. Im Folgenden werden zwei Steuerungsebenen -die Steuerung der einzelnen Einheiten dezentraler Erzeugung sowie die Netzsteuerung -vorgestellt. Erstere wird auf Basis von drei Technologien erlä utert: Induktionsgeneratoren, Synchrongeneratoren und Stromrichter. Eine wirkungsvolle Netzsteuerung kann anhand eines aktiven Managementkonzepts aufgebaut werden. Schließlich werden drei Beispiele fü r die Steuerung -MicroGrids, Speicherzelle und virtuelles Kraftwerk -besprochen. Schlü sselwö rter: dezentrale Erzeugung; Steuerung; MicroGrids; virtuelle Kraftwerke IntroductionDistributed generation (DG), according to the CIGRE WG 37-23 definition, is low rating generation that is neither planned nor dispatched centrally and is usually connected to the distribution network (CIGRE working group 1999). The range of DG includes, for example, wind turbines, small hydro turbines, CHP units, photovoltaic (PV) cells, fuel cells, and micro turbines. DG, energy storage and manageable loads are incorporated in the wider concept of distributed energy resources (DER). The installed capacity of DG is expected to continue increasing over the coming years (Pecas Lopes et al., 2007).Different control systems are being investigated in order to accommodate DG in the network. Those systems are to improve the performance of DG units without violating network constraints, and provide appropriate frameworks for them to participate effectively in the power system and market operation. Two different control levels have been identified, DG unit level and distribution network level. Moreover, a number of control paradigms are also being investigated in order to provide the required framework for the operation and management of DER.

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1 2 3 4 A GB electricity generation system for 2030 with a large amount of renewables is studied. Its ability to meet projected 2030 demand on a half-hourly basis is investigated for two extreme weeks of the year: winter maximum demand and summer minimum demand. For each week, either operating costs or carbon dioxide emissions were optimised. The effects of a carbon price of £30/t or £75/t on the power production of different generating units, the carbon intensity and operating costs are shown. Load reduction through demand-side management during the winter maximum demand week was necessary for 10-15 h. During the summer minimum demand week, wind curtailment of 5 GWh occurred only when carbon dioxide emissions were optimised. Notation C i ðP t i Þ operating costs of generator i at time t (£ million) E t PH available energy of pumped hydro at time t (GWh) EM i ðP t i Þ carbon dioxide emissions of generator i at time t (kt) G i number of time steps generator i is declared on (up) HRðP t i Þ heat rate (linear) of generator i at time t L t FC forecast system demand at time t (GW) L i number of time steps generator i is declared off (down) N total number of generators P t i generating capacity of generator i at time t (GW) P i,min , P i,max upper and lower limits of generator i at time t (GW) P t PHþ , P t PHÿ generating, pumping of pumped hydro at time t (GW) R i,max ramp rate of generator i (GW) R t sys system operating reserve at time t (GW) R t FC forecast renewables power output at time t (GW) T total number of time steps in simulation T i,up , T i,down minimum up/down time of generator i (time steps) U t i state of generator i at time t: 1 (up); 0 (down) ðP t i Þ thermal efficiency (linear) of generator i at time t DF demand forecast standard deviation WF wind power forecast error standard deviation

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