Innovations for the future Energy System. European Utility Week, Amsterdam, 5. October 2017 Michael Weinhold, CTO Siemens Energy Management

Transcription

1 Innovations for the future Energy System European Utility Week, Amsterdam, 5. October 27 Michael Weinhold, CTO Siemens Energy Management Restricted siemens.com

2 Agenda 1 Trends 2 Innovations 3 Outlook Page 2

3 The Energy Revolution: Big Picture From centralized power and unidirectional grid Distributed Energy Systems to fully integrated & intelligent Central and Distributed Energy Systems and bidirectional balancing Transmission Distribution and Consumption 1 Changing generation mix 2 Generation capacity additions Distance from source to load Decentralization (public/private) Refurbishment/ upgrades Page 3

4 Storyline of the global Energy Transition: Electricity is key to reach sustainable Energy Systems! Political Targets: 1. De-carbonization 2. Sustainability 3. Energy Efficiency 4. Resiliency Breakthrough Technologies (Performance & Cost): 1. Wind- and PV Power Gen. 2. Energy Storage (Li-Ion) 3. Digitalization 1. Large-scale Renewable integration into the electricity system (Wind, PV, Hydro) Changing System Operation ( Physics & Acceptance ) + 2. Distributed Energy Systems to maximize: 1. Energy System efficiency Consumercentric 2. Local Renewable integration 3. Resiliency Energy World 3. Electrification of Consumption ( Physics & e. g. Heat Pump, E-Car Psychology ) Page 4

5 The revolution of energy systems has just started Connecting Grids Increase of Renewables Growing electricity supply Distributed Power Generation Digitalization & Automation New installations in GW p.a. Generation in 1000 TWh New installations in GW p.a. New Smart Meter installations (Electricity, Gas, Water) in mio units p.a. ~90 36% 19% 20 45% ~191 33% 47% 20% 2020 ~303 29% 58% 14% 2030 ~21 20% 80% 20 ~26 29% 71% 2020 ~32 40% 60% 2030 ~373 49% 51% 20 ~358 62% 38% 2020 ~444 67% 33% 2030 ~50 25 ~ Smart Grid IT Spendings in bln USD ~9 ~14 ~ ~18 Wind Solar Others Renewables Conventional decentral central Increased distance to Load / Need for Balancing Reinforcing national grids Interconnect national grids Connect large Renewables Increased electrification in emerging countries e.g. China, India, Indonesia of building heating and industrial processes of mobility (ecars, ebus,..) DES & critical power systems Energy storage solutions Micro- /Nanogrids arising Low & Medium Voltage growth Drives agility in energy systems Sensors / meters provide data, IT solutions make it actionable New market participants New pricing / business models Efficient Asset Management Page 5 Note: Siemens assumptions based on market and industry analysts

6 Agenda 1 Trends 2 Innovations 3 Outlook Page 6

7 Energy Management requires an open and standard-based end-to-end architecture from field level to applications and services Planning and Simulation Operations and Control Maintenance and Usage DIGITALIZATION Software and Services PSS grid planning and simulation: Digital Twin Data model Spectrum Power grid operations/ control: Central Data Madel EnergyIP applications, analytics: distributed, Internet of Things MindSphere AUTOMATION Substation: Automation and protection Field area networks: Sensors, meters, controls, concentrators EM Assets Other Siemens and 3 rd party ELECTRIFICATION HV AIS HV GIS PT DT MV Swg LV systems LV Circuit Breakers PAC meters Page 7

8 HVDC: Power Electronics managed by intelligent control software Page 8

9 ULTRANET, Germany, 2021 World s first VSC HVDC with full-bridge converter Customer Project Name Location Power Rating Type of Plant Voltage Levels Semiconductors Amprion / TransnetBW ULTRANET Osterath Philippsburg, Germany 2000 MW, bipolar HVDC PLUS in full-bridge topology, 340 km ± 380 kv DC, 400 kv AC, 50 Hz IGBT Page 9

10 Seconds Minutes Hours Days Weeks Battery-based Storage for very different purposes Application Segmentation Reserve capacity Reserves SIESTORAGE Response to emergencies Consumer / Prosumer Decentralized generation Variable generation (PV, Wind) Conventional power plants Firming Time shifting Residential/ commercial selfsupply Industrial peak shaving On-grid + grid upgrade deferral Remote areas/ off-grid Avoid curtailment Rules for grid integration Energy arbitrage (time shifting) Increase flexibility / load optimization Distribution grid Transmission grid System stability Ensure stability Load optimization Ensure power system stability 1 kw 100 kw 1 MW 10 MW 20 MW Power Page 10

11 InovCity Évora, Portugal: Energy storage pilot project with EDP 472 kw/ 360 kwh SIESTORAGE system MicroGrid Controler Main applications Energy backup, voltage regulation, peak shaving, Islanding Turnkey solution Page 11

12 Research project Dynamic Grid Control Center SPECTRUM 7 Challenge: Changing system dynamics More power electronics within the grid, less rotating mass Target: Autopilot and Master Power Control operation Controllable grid dynamics Self healing capabilities Partnering: 3 universities 4 TSOs 2 scientific institutes PJM interconnection Page 12

13 Microgrid IREN2 research project in Wildpoldsried, Germany Solution Combining micro grid and Virtual Power Plant to form a topological power plant, which can be operated in island mode Benefits Stable and economically optimized grid operation Black start capability Profitable use of renewable resources Ancillary services from the distribution grid Page 13

14 Reference projects demonstrate the broad range of different prosumers in a distributed energy system Battery storage system safeguards power supply at VEO Data analytics decisionmaking support for GESTAMP Turnkey integrated power supply solution for Südzucker Intelligent microgrid for Savona University Black start capability of power plant's gas turbine at any time and without feeding in power from the public grid This island network keeps the critical production processes at the steel mill operating Real-time monitoring via web portal Early detection of machinery failure and inefficient processes Customized reports Worldwide implementation possible Drawing power from the high-voltage grid, but also feeding electricity from the on-site power plants into the grid Highly energy-efficient conventional and renewable sources are controlled in real-time The campus can generate enough electricity and heat to satisfy its needs autonomously Page 14

15 Possible advantages of the blockchain technology No separate financial management process necessary any more Cost reduction: (real-time) peer-to-peer transactions with integrated payment / currency Security: Immutable records & Trust of source No verification costs to prove the origin e.g. of renewable energy, performance validation Blockchain (P2P) energy trading (incl. e. g. regulation power), grid charging, nodal pricing, EV-Charging New Business Models: Multi-stakeholder collaboration in different use cases Optimization: Data available in one distributed / shared database analytics across shared data (e. g. price data, market data, load profiles, grid utilization) Page 15

16 Innovative Microgrid solution using blockchain technology supporting New York s Reforming the Energy Vision (REV) program Page 16

17 Challenges Energy System Stakeholder challenges Complexity and Uncertainty (Technology, Regulation) System Dynamics (Stability) Vulnerability (Physical and Cyber Attacks) Competitive advantage through: Adaptability, flexibility, speed Forecasting accuracy Decision Quality Data Analytics turns data into knowledge Page 17

18 Application of Artificial Intelligence (including Machine Learning) Act Analyze Prescriptive Analytics Inform Predictive Analytics Diagnostic Analytics Descriptive Analytics What happened? Why did it happen? What will / should happen? What shall we do? Business Applications Service statistics Sales reports Root cause identification Fault analysis Condition monitoring Fault prediction Power optimization Load balancing Data Mining Machine Learning Page 18

19 Artificial Intelligence Deep Learning Example: Online Decision Support for Power Grids Growing share of renewable energy Growing and share distributed of renewable power generation call for enhanced capabilities of intelligent devices. Wide-Area Disturbance Classification Wide area monitoring combined with decision support Disturbance identification and compensation Fault Localization and Classification Increase quality of supporting information in case of faults Localization of faults even in difficult cases Operation Center: Disturbance Classification Infield: Fault location using neural networks Stream Data Recognize Contingencies Counter Measures Model Training Model Generation Model Deployment Interpreter TIME contingency Source code Embedded Analytics Framework (LEAF) Page 19

20 Agenda 1 Trends 2 Innovations 3 Outlook Page 20

21 Outlook More Wind- and PV, Electrification, Distributed Energy Systems Sector-couplings and Energy Storage increasingly relevant Digitalization is key key enabler (simulation, operation, market integration) Emerging Sharing Economy concepts for Prosumers Artificial Intelligence gaining momentum Page 21

22 Thank you very much! Unrestricted Siemens AG 25 siemens.com

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