Blue Growth Opportunities in the Digitized Sustainable Energy Economy

Transcription

1 Blue Growth Opportunities in the Digitized Sustainable Energy Economy Eicke R. Weber Vice President, International Solar Energy Society ISES Former Director, Fraunhofer Institute for Solar Energy Systems 1

2 Blue Growth Opportunities in the Digitized Sustainable Energy Economy The largest challenge for mankind today is the needed transformation of our economy within this century. If we want to enjoy life on this planet as we like it today even in the year 2500, we have to change to a sustainable lifestyle by 2100! This task is most urgent in the energy sector, climate change threatens to destroy the basis of our life as-we-know-it by 2050! This disruptive transformation process offers many economic opportunities; the needed economic growth can hardly be labeled as Green Growth as it often interfers with our biosphere, it should be called Blue Growth! Blue Growth : Blue as the water, the sky,.and our solar panels! The rapid development of the PV market is an excellent example of Blue Growth, let us look at it in more detail:

3 Blue Growth Opportunities in the Global Digitized Sustainable Growth of Energy PV Installations Economy From 0.1 MW 1992 to 400 GW 2017: CAGR of 33%! CAGR : 33%! Source: Wikipedia., accessed May 20, 2018

4 Electricity supply from renewable energy sources Development in Germany EEG Januar 2012 EEG August 2014 Year 2017 Total: 37,9% 165 TWh EEG August 2004 EEG Januar 2009 PV 8,5 % 37,1 TWH Strom EinspG: EEG April 2000 Bio 8,5% 37,1 TWh Januar 1991 März 2000 Wind 17,1 % 74,6 TWh Hydro 3,7% 16,0 TWh

5 PV System Module Price Learning Curve since 1980 Source: Fraunhofer ISE (2015): Current and Future Cost of Photovoltaics. Study on behalf of Agora Energiewende

6 Crystalline Silicon Technology Portfolio c-si PV is not a Commodity, but a High-Tech Product! material quality diffusion length base conductivity device quality passivation of surfaces low series resistance light confinement cell structures PERC: Passivated Emitter and Rear Cell MWT: Metal Wrap Through IBC-BJ: Interdigitated Back Contact Back Junction HJT: Hetero Junction Technology material quality Industry Standard 14% PERC 15% BC- HJT IBC-BJ HJT MWT- PERC 16% module efficiency 21% 20% 19% 18% 17% device quality Adapted from Preu et al., EU-PVSEC 2009

7 Projections to TW-scale PV from TW workshop Freiburg N. M. Haegel et al., Science 356, 141 (2017). Using simple assumptions, we can project that just maintaining the 2015 deployment rate would reach 1-TW deployment before A 25% annual growth rate would reach 5-10 TW by 2030!

8 PV Heading into the Terawatt Range this is a Disruption! Rapid introduction of PV globally is fueled by availability of cost-competitive, distributed energy In 2050 or before between and GWp PV will be installed! By 2017, only about 400 GWp have been installed! We are just at the beginning of the global growth curve! Source: IEA 2014

9 Price Lernkurve Experience Batterien (Learning) für Elektroautos Curve for car batteries The learning rate for NiMH batteries in hybrid vehicle applications have historically been 9% most likly in future 2007 LR=8% market leader 300$/kWh US$300/kWh market-leader BEV standard in 2014 (Tesla S) battery ¼ of total EV costs Tesla S, N. Leaf B. Nykvist, M. Nilsson; «Rapidly Falling costs of battery packs for electric vehicles», Stockholm Environment Institute & KTH Royal Institute of Technology, Stockholm; Nature Climate Change; 9th Feb 2015 Franz Baumgartner, ; ST. Gallen; Slide 42.

10 PV a Key Pillar of the Future, Sustainable Blue Economy PV has become a cost-efficient, rapidly growing element of the electricity supply in many countries, driven by political incentives, technology improvements, and related cost reductions: à < 2 ct/kwh 2016/17 announced in several auctions! Global Photovoltaics is a fast growing market: The Compound Annual Growth Rate (CAGR) of PV installations was 33% between 1992 to 2017! Drivers are the combination of cost effectiveness and climate concerns. With PV entering the Terawatt age, substantial new PV production capacities along the full food-chain are needed: poly-si, wafers, cells, modules, inverters (BOS), based on high-efficiency technology generations, allowing further efficiency improvements at decreasing cost! Croatia has a serious chance to participate in the further growth of this part of the future Blue Economy: Program Vallis Solaris Croatia:

11 R & D, Industry and Energy Program "Vallis Solaris Croatia" 1). : The Future Energy System Based on Renewables, Sector Coupling Full Integrated PV Modules and PV Electricity Production in Croatia (Solar silicon / Solar glass / Ingots / Wafers / Cells / Modules / Inverters / System components / PV Power Plants) 2).. Establishment of leading Electricity Storage Technology (production of stationary and mobile Lithium-Ion battery storage systems in Croatia) 2).. Energy supply systems that combine both technologies with the electricity grid and the whole energy supply system inclusive traffic, heating, cooling and industrial processes (intelligent sector coupling based on smart technologies). These 3 technologies will be accompanied by studies, research and development together with local institutes and universities under the leadership of the Fraunhofer ISE, the leading institute in Europe in this area. 1). The Program was developed and supported in cooperation of the Fraunhofer ISE and German industry partners and is divided into 4 phases, which enables the start of production after only years and Program development cycle maximum after 8-10 years. Direct benefits for Croatia from the Program are vast, like long-term and a strong increase of GDP, employment, export and state budget income total investment app. EUR 6.5 Billion, total new workplaces app. 7,000 / years ). 2). The whole productions lines will be based on Industry 4.0 technologies.

12 Integration of fluctuating renewable power from Solar and wind requires a disruptive transformation of our energy system, including storage, sector coupling - such as power to gas - and thorough digitization of the complete energy system.

13 Paradigm shift of the Power Supply Model The sheer number of participants in the electricity grid alone would not require to change to a data-based interconnection of these systems. However, the growing fraction of volatile, non-regulated power input from solar and wind requires a fundamental paradigm shift of the power supply model. In the past, power was supplied as needed by big thermal power plants. This will be replaced by a new data-based system, that includes the continuous balance between power production and consumption through a complex interplay of timely load management, stronger sector coupling of electricity, heat and traffic, temporary use of flexible power production such as gas plants, and implementation of storage technologies: electrical, thermal, and chemical. Integration of modern prediction methods for power production and consumption is part of organization and management of these more and more complex systems. All of this can only be achieved using the techniques and methods of digitization.

14 Additional Complexity: International Integration Differences in Rules and Regulations within the EU Different incentives for Regenerative Energies Challenge for transnational coordination Digitization: comprehensive standards required for transnational Integration! Slide adapted from H.M. Henning et al., FVEE Annual Meeting 2018

15 Dimensions of Digitization Methods Artificial Intelligence Internet of Things IoT Big Data Computing Digital twins Blockchain Applications Data analysis Operation and control Automation Application areas Energy economy Generation Grids Trade Consumption Production technology of system components Data storage and processing Local (edge computing) Central (cloud computing) Mixed Slide adapted from H.M. Henning et al., FVEE Annual Meeting 2018

16 Digitizing the Energy System: Areas of Application Generation Virtual power plants Generation forecasts Predictive Maintenance Production Producing components Industry 4.0 Automattion, control Optimizing product quality Digitizing the Energy System Consumption Load Management Feed-in management Optimized operation Need forecasts Grid Real-time data Automatic grid control Management of System services Trade Virtual markets Peer-to-Peer Trade with system services Time-variable prices Slide adapted from H.M. Henning et al., FVEE Annual Meeting 2018

17 Example Power Production: Virtual Combi-Power Plant What? Software to aggregate power producer, consumer and storage systems Energy management of the system portfolio (presently 2 GW) User-friendly operator surface Who? Tool für direct sellers / aggregators Support for the grid operation Why? The VPP package allows the customer to record, manage, process and optimize system information with high frequency Slide adapted from H.M. Henning et al., FVEE Annual Meeting 2018

18 Example Grid: Big Data and Artificial Intelligence (AI) to Predict Power Production out of Volatile RE Approach: 1. Prediction of Power feed-in from individual systems 2. Extrapolation of individual predictions 3. Aggregation of predictions 4. Verification of predictions Slide adapted from H.M. Henning et al., FVEE Annual Meeting 2018

19 Example Prosumers: Individual Buildings In the future: Several smart prosumers, producers and consumers, in one system: Integrated, optimized operation of all components including predictive control allows to minimize storage and energy conversion losses Example: passiv house in Hannover, with PV-system, batterie und heat pump: Solar fraction of power: 53 % Renewable fraction 79 %! Slide adapted from H.M. Henning et al., FVEE Annual Meeting 2018

20 Grid stability with growing amounts of fluctuating RE: Grid in Germany today more stable than in 2006, and in France, UK today! Source: Hans-Josef Fell : For comparison (2013): SAIDI: France System (81% Average Nuclear Power): Interuption 68 min., Duration UK: 55 mins.! Index

21 Opportunities and Challenges of the digitized renewable energy power supply Opportunities: Creation of new business models in the Blue Economy Efficient use of existing infrastructure (e.g., Heinrichs und Jochem, 2016) Increased reliabilityin systems with increasing fraction of power from volatile sources Efficient integration of climate-friendly renewable energy with flexible power consumption Large energy savings through optimized systems, for customers and the total system Challenges: Privacy (e.g., Buchman et al. 2013) and control of data Establishing social acceptance Adjustment of political framework Investment costs Slide adapted from H.M. Henning et al., FVEE Annual Meeting 2018 Heinrichs, H., Jochem, P. (2016), Long-term impacts of battery electric vehicles on the German electricity system, European Physical Journal Special Topics 225, , doi: /epjst/e x Buchmann, E.; Kessler, S.; Jochem, P.; Böhm, K. (2013): The Costs of Privacy in Local Energy Markets, IEEE Conference on Business Informatics (CBI), Vienna, Austria.

22 Holistic Modelling and Analysis of a Future German Energy System as Model for Croatia* Inter-sectorial analysis of the overall system / Approach: Comprehensive model of the overall system with all energy fluxes based on hourly energy balance Generic optimizer optimum composition and sizing of all components including energy retrofit of the building stock Goal function: minimum of total annual cost (re-investment, maintenance, operation, financing) Appropriate treatment of a highly complex system with many interdependencies *) Fraunhofer ISE, Sustainable energy supply for Germany in 2050 (results of a study), German Energy System as possible Model for Croatia / project cooperation with Croatian Universities and Research Institutes

23 The Future Globale Supergrid: One sun one planet one Grid!

24 Thank you