Energy storage in intelligent energy networks
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1 Energy storage in intelligent energy networks Kari Mäki VTT New developments in battery technology Oulu, January 2017
2 Contents Towards intelligent energy systems Storage status overview Needs for storage units in energy systems Storage integration in energy systems Services built on storages Research examples Conclusions 07/02/2017 2
3 Towards intelligent energy systems 3
4 Key drivers for more intelligent energy systems Accommodating renewable energy resources Flexibly integrating and controlling variety of active components Introduction of electric mobility Providing better reliability and quality of service Enabling platforms for new businesses Better involving individual users 07/02/2017 4
5 Radical changes in the ecosystem Individual customer in the centre CLIC / FLEXe program 07/02/2017 5
6 Radical changes in the ecosystem Energy as such will not be the main value Instead; power and its controllability gains more value New businesses can be built around flexibility provision Triangle of observability intelligence controllability, enabled by efficient communication and data management Intelligence Social aspects Markets & regulation Intelligence & data Technical layer Flexibilit y Observability Controllability 07/02/2017 6
7 New technologies as enablers Bridging the intelligence gap at customer or equipment level IoT technologies Wireless sensors and monitoring New components providing flexibility as a service Distributed generation, demand response, energy storages, EV charging, Aggregation into larger entities Markets evolving for such businesses Energy data enabling new solutions Open interface approaches, new players, new services Processing the data, finding essential information 07/02/2017 7
8 Brief storage status 8
9 Current status of storage in energy systems 07/02/2017 9
10 Current status of storage in energy systems 07/02/
11 Current status of storage in energy systems 07/02/
12 CAES: promising novel concepts Adiabatic-heated CAES Greater storage power density Improved control possibilities Thermal expansion due to cyclic heating? Low-temperature CAES Avoids technical restrictions Fast start-up times (5 min) Efficiency losses due to additional stages? 07/02/
13 Storage units in energy systems 13
14 Potential for energy storages Amount of intermittent RES generation Storage enabling more efficient integration Need for better service reliability Avoiding service interruptions Improving customer power quality Amount of electric vehicles Potential for smart charging and vehicle to grid (V2G) integration Customer-level applications Economical use of dynamic tariffs Optimization of microgeneration Local back-up solutions Extension of demand side management - from controllable load to controllable load/supply combination 07/02/
15 Generation gets more variable... 07/02/
16 load profiles really gain attention 07/02/
17 ...flexibility will have a value... Controllable flexibility will have an increasing value Aggregating individual distributed resources can form significant entities Communication enables the control observe loop 07/02/
18 ..and markets do evolve Fingrid reserve types 07/02/
19 Efficient storage can solve it all! Backup power Investment deferral Voltage control Power Balancing power Reserves Frequency control PV smoothing Power quality Energy Market operations Capacity Hourly tariffs 07/02/
20 Different solutions for different timescales Energy system needs according to operation time scale Time response requirements as defined in IoE project. 07/02/
21 Different solutions for different timescales Energy system needs according to operation time scale Power quality improvement - from microseconds to seconds. Suitable for local applications where sensitive loads are present. Power balance smoothing - from seconds to hours. Suitable especially for integration of renewable energies like wind power and PV. Also for load peak shaving. Diurnal variation smoothing scale of hours. This usually means variation between day and night. Seasonal smoothing - from days to months. Especially between seasons. Difficult to achieve currently. Primarily heat storage applications? Grid ancillary services - from minutes to days or even to months. Grid state related services agreed between network operator and storage owner. 07/02/
22 Different application areas HV/MV LV network power quality / LV network island operation PV unit G AC Power Smoothing Generator transformer MV/LV Customer meter AC/DC DC power smoothing Customer energy optimization Customer network G AC/DC DC circuit power Smoothing DC/AC MV network power quality Customer power quality 07/02/
23 Different application areas Hours Minutes Customer energy optimization Li-Ion Ni-Cad PV output smoothing Small-scale island operation Lead-acid NAS Vanadium redox Large-scale island operation Pumped hydro Flywheel Seconds Milliseconds Customer power quality improvement Supercapacitor Gusty wind output power smoothing Network power quality improvement SMES Storage capacity kw 07/02/
24 Energy density (Wh/kg) Different characteristics Energy density / power density -plane Suitable application areas can be defined Hybrid systems can be beneficial 1000 Fuel cell 100 Ni-MH, Ni-Cd Lithium ion 10 Lead acid Flywheel Super capacitor 1 SMES Electrolytic capacitor 0, Power density (W/kg) 07/02/
25 Example: PV smoothing Use of storage for smoothing PV output momentary variations 07/02/
26 Example: PV smoothing PV output smoothing in Nordic conditions Daily variation can be reduced Other methods needed for seasonal level 07/02/
27 Services built on storages 27
28 Service models with storages Participation on energy markets optimization based on arbitrage and price differences System services through reserve markets or direct service agreements (fast reserves, frequency control, virtual inertia, etc.) Balancing services for smoothing energy balances and profiles (balance responsible parties, energy producers, big customers) Ancillary services for local network Services for individual customer customer s own preferences for energy management Aggregator models for combining multiple small storage units as a bigger entity Potential can be found when building a portfolio combining different service types 07/02/
29 Ancillary services Most of the technical solutions mentioned could be offered to local grid operator as ancillary services Voltage and frequency control Local power quality management Islanded operation and back-up solutions Peak avoidance investment deferral Providing ancillary services requires efficient co-operation Communication and control of storage device Integration to network operator s SCADA and other systems Measurements, agreements etc. 07/02/
30 Aggregator business logics Aggregator service is a potential solution Aggregator combines multiple small units Combination of storages as wel as controllable loads, microgeneration, etc. Aggregate impact of small units can be significant Aggregator could be serving both local grid and customer s own energy management Aggregator Network operator Customer energy management Ancillary services Customer interface and energy strategy Measure and control 07/02/ V2G EV
31 Aggregator business logics Measurements Network operator Service order Service offer Energy market Price information Exchange Balancing power market Customer information Public network Customer network Smart meter Aggregator Customer location Measure Customer energy management PV panel Controllable loads EV/ storage Measure and control Customer UI 07/02/
32 Finding the potential: multi use of storage Backup power Investment defer Voltage control Power Balancing power Reserves Frequency control PV smoothing Power quality Energy Market operations Capacity Hourly tariffs 07/02/
33 Research examples 33
34 VTT covers whole value chain of energy storage research Battery cell level Charging systems Climatic testing of storage units Control systems Integration with renewable energy sources Energy system integration Modelling and simulation Ancillary services and reserves Energy markets 07/02/
35 Optimization of solar energy and storage use Solar forecasts Optimal dimensioning of the storage unit Optimal control strategy Scalable solution from individual units to large area systems Available storage technologies VTT optimization intelligence 07/02/
36 Optimal storage solutions for eco-efficient areas Economic feasibility studies Local energy use optimization Self-sufficient area strategies Backup energy solutions Local power quality services Area yearly electricity from grid No PV PV PV+optimal storage 07/02/
37 Aggregator business concepts Aggregators or virtual power plants as future service providers Technical solutions, business models, market tools Pictures: EU ADDRESS project 07/02/
38 Conclusions 38
39 To conclude Efficient storage units are increasingly needed in energy systems Controllable flexibility will have a value Different requirements according to the application From power quality to seasonal variation Different storage technologies to match different requirements New business models and market roles evolve around storages Interesting aggregator models developing Regulative framework can constrain full utilization of storages The business potential is found in models offering storage on various markets 07/02/
40 TECHNOLOGY FOR BUSINESS 40
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