Smart Grids and their Control Rudolf Sollacher

Transcription

1 Smart Grids and their Control Rudolf Sollacher Siemens

2 The complex and heterogeneous energy system is changed by the influence of decentralized fluctuating renewable energy generation 1) Distributed Energy Resources 2) Combined (Cooling) Heat and Power

3 Specific challenges for distribution grids Physical effects Distributed Generation U problem (rural area), I problem (urban areas) Flexible Tariffs synchronized consumption behavior Implemented protection concepts become obsolete Flexibility Trading & e-mobility load problems combined with U/I challenges High amount of inverters connected to the grid Grid stability Challenges for distribution grid operators Which effect causes problems where in the LV/MV Grid Lack of information Passive consumers become highly dynamic & active prosumers Grid planning rules loose their validity Strong demand to increase efficiency Efficient utilization of existing infrastructure, optimized grid operation Demand for more information to support efficiency of 3rd parties (TSO s, market partners, energy consumer)

4 High voltage distribution grids - new services (SysDL2.0) Use case Description Action SysDL module Adaptation of voltage band at coupling point between transport grid and high voltage grid Risk of violation of agreed voltage bands Compliance with allowed voltage band no longer guaranteed Evaluation of temporary voltage band adaptation for period of potential voltage band violation in high voltage grid TSO Reactive power request by distribution grid Risk of deviation from allowed voltage band in transport grid TSO requests reactive power from DSO Determination of reactive power set-points for distributed power generation systems Evaluation of redispatch request TSO requests allowance of preventive redispatch with power plant from 110 kv grid Evaluation of effects of re-dispatch and as a consequence - acceptance or denial Local voltage control 110 kv Voltage in distribution grid approaches allowed bounds Local voltage control in distribution grid by appropriate reactive power provisioning DSO Minimizing losses 110 kv Local contingency management 110 kv Normal operation Current contingency in 110 kv grid Minimizing losses by appropriate reactive power provisioning Activation of reactive power set-points in distributed power generation systems for contingency management and for minimizing active power reduction

5 Future power system control architecture must be compatible to existing architecture and components A self-similar control architecture guarantees scalability of coordinated distributed control gas turbine control governor, excitation ctr. gas turbine ancillary service platforms wind park control turbine control wind turbine wind turbine wind turbine energy market platforms operation manger low level control multi-modal power plant power system control center micro grid manager building energy manager economic planning supervisory power control voltage and frequency control low level control passive load passive load power grid active load passive load passive load controllable components electric hardware

6 Higher level control tasks - overview Some or all of these tasks can be executed on large scales down to micro-grid or even building level Economic planning Matches predicted power demand and supply (e.g. on day ahead) at lowest cost At large scales, power is supplied by large power plants or by aggregated smaller plants and flexible loads At smaller scales, distributed generation and flexible storages and loads are coordinated centrally (e.g. at building, campus or city level) Market based approaches support economic unbundling of power generation and power distribution and hide sensible information Supervisory power control Execution of economic planning on power system Fast power balancing after unpredicted generation and demand variations Takes into account requirements concerning e.g. power-line overloading or N-1 safety Required flexibility of generation and load is achieved by ancillary service platforms, e.g. for active and reactive power reserves similar to today s primary reserve market Voltage and frequency control Implemented locally on generators and loads and coordinated by superordinate management systems Usually achieved by droop controllers (=proportional controllers) providing reference values for the low level controllers Analysis and design of these controllers is quite challenging because of the complex, interconnected dynamics of the individual generators Voltage control in distribution grids has become an acute problem because of the strong power injection at this level Timescale: 5-15 min <100s <1s

7 Outlook Main trends Substantial progress in battery technology (e.g. longer cycle-lifetime, lower price, simple recharging) Electricity will have increased share in heating and mobility sector Digitalization will lead to reduced engineering effort and allows for new service business models Open research issues How to improve estimates on attractor regions in dynamic power system models? How to treat uncertainties in power flow calculations and optimal control applications properly? How to control islanding of micro-grids? What is the effect of islanding of many micro-grids on the dynamics of the whole grid? Control solutions for multimodal energy systems

8 References I General Introduction: P. Kundur. Power System Stability and Control. McGraw-Hill, Aspern Smart City Research project: C. Bose, C. Hoffmann, C. Kern, and M. Metzger. New principles of operating electrical distribution networks with a high degree of decentralized generation. In CIRED th International Conference and Exhibition on Electricity Distribution - Part 1, pp 1 4, June Y. Chistyakov, E. Kholodova, K. Netreba, A. Szabo, and M. Metzger. Combined central and local control of reactive power in electrical grids with distributed generation. In Proc. IEEE International Energy Conference and Exhibition (ENERGYCON 2012), pages , Florence, Italy, September A. Collazos, F. Maréchal, and C. Gähler. Predictive optimal management method for the control of polygeneration systems. Computers & Chemical Engineering, 33(10): , DynaGridCenter Project: M. Metzger, A. Szabo, and J. Bamberger. Control as a key technology for the integration of renewables. In 18th IFAC World Congress 2011, pages , Milano, Italy, August U. Münz, R. Sollacher, W. Klein, P. T. Pilgram, and C. Heyde. Predictive decision support to protect power systems against wind farm drop outs. In Proc. PowerTech, 2015 U. Münz and M. Metzger, Voltage and angle stability reserve of power systems with renewable generation, IFAC Proceedings Volumes, Elsevier, 2014, 47, U. Münz, M. Metzger, A. Szabo, M. Reischböck, F. Steinke, P. Wolfrum, R. Sollacher, D. Obradovic, M. Buhl, T. Lehmann, M. Duckheim and S Langemeyer, Overview of recent control technologies for future power systems - an industry perspective, at - Automatisierungstechnik, 2015, 63,

9 References II M. Pichler and D. Aufhauser. Intelligent self-consumption optimization in buildings. In e-nova 2014, , Pinkafeld, Austria, 2014 IREN2 Project IRENE Project K. Schaber, F. Steinke, P. Mühlich, and T. Hamacher. Parametric study of variable renewable energy integration in europe: Advantages and costs of transmission grid extensions. Energy Policy, 42: , S. Schuler, U. Münz, and F. Allgöwer. Decentralized state feedback control for interconnected systems with application to power systems. Int. J. Process Contr., 24(2): , J. Seegers, Uncertainty Handling in Model Predictive Control for Smart Buildings, Technical Univ. Munich, 2016 Siemens AG. SICAM Microgrid Manager SysDL2.0 Project: A. Szabo, M. Buhl, and M. Metzger. Voltage control for distributed energy resources - the value of coordination. In Proc. IEEE International Energy Conference and Exhibition (ENERGYCON 2014), Dubrovnik, Croatia, May A. Szabo, M. Metzger, and J. Bamberger. Control as a key technology for the grid integration of renewables. In IFAC World Congress, volume 18, pages , P. Wolfrum, M. Kautz, and J. Schäfer. Smart operation of CHP units. In 8th IFAC Power Plant and Power System Control Symposium (PPPSC), pages , Toulouse, France, P. Wolfrum, M. Kautz, and J. Schäfer. Optimal control of combined heat and power units under varying thermal loads. Control Engineering Practice, 30: , 2013.

10 References III 6. Forum Energiewende, 14. Juni 2016, Siemens AG, Erlangen T. Lehmann et.al., New Energy Systems Energy Management for Commercial Buildings A. Schenk, Smart City Aspern laying the foundation for a sustainable energy system H. Stiesdal, SCOE Society s costs of electricity: How society should find its optimal energy mix

11 Contact Rudolf Sollacher Senior Research Scientist CT RDA AUC RAC-DE Otto-Hahn-Ring Munich Phone: +49 (89) Fax: +49 (89) Mobile: +49 (152) rudolf.sollacher@siemens.com Internet siemens.com/corporate-technology Intranet intranet.ct.siemens.com