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Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
Smart Energy Management Algorithms
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Smart Energy Management Algorithms

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Autor:Milan Prodanovic

Autor:Milan Prodanovic

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  • 1. Smart Energy Management Algorithms Dr. Milan Prodanović EOI, Madrid, November 2010
  • 2. Introduction Mission of IMDEA Energy is to promote renewable and clean energy technologies Formed of six research units: Thermo-Chemical (production of sustainable fuels, CO2 confinement and valorisation) Bio-Chemical (production of sustainable fuels, CO2 confinement and valorisation) Electrochemical (energy storage, development of systems with enhanced efficiency) High Temperature Processes (solar energy, energy storage) Energy Systems Analysis (CO2 confinement and valorisation, life-cycle analysis) Electrical Processes (Smart management of networks, renewable energy, energy storage) Collaboration with other IMDEA institutes Research objectives of Electrical Processes Unit Development of Smart management techniques for future power networks Active demand side management and energy efficiency improvement Management of energy storage devices across the network Electric vehicles Key technologies ICT Power electronics Embedded RT control systems
  • 3. SmartGrids EU Deployment Priorities for SmartGrids IMDEA Energy “A SmartGrid is an electricity network that can intelligently integrate the actions of all users connected to it - generators, consumers and those that do both – in order to efficiently deliver sustainable, economic and secure electricity supplies.”
  • 4. SmartGrids According to Strategic Deployment Document of European Technology Platform, Key Challenges for SmartGrids are: Strengthening the grid – ensuring transmission capacity Moving offshore Developing decentralized architectures Communications – allowing RT operating and trading Active demand side – all consumers play an active role Integrating intermittent generation Enhanced intelligence of generation, demand and the grid Capturing the benefits of DG and storage Preparing for electric vehicles
  • 5. SmartGrids According to Strategic Deployment Document of European Technology Platform, Key Challenges for SmartGrids are: Strengthening the grid – ensuring transmission capacity Moving offshore Developing decentralized architectures Communications – allowing RT operating and trading Active demand side – all consumers play an active role Integrating intermittent generation Enhanced intelligence of generation, demand and the grid Capturing the benefits of DG and storage Preparing for electric vehicles
  • 6. G Feeder 1 WAN CONTROL Bus 1 Bus 2 Bus 7 Bus 9 Bus 10 Gen 10 Load 10 Load 9 Load 2 Load 7 PF1 ,QF1 PG5,QG5 PL10,QL10 PL9 ,QL9 PL7,QL7 PL2 ,QL2 Bus 4 Load 4 PL4 ,QL4 Bus 8 Bus 6 Load 6 PL6 ,QL6 Bus 3 Bus 5 Load 5 PL5 ,QL5 Load 3 PL3 ,QL3 Tr 8 Tr 4Tr 1 SW1-2 SW6-7 SW7-5 SW3-9 Feeder 2 PF2 ,QF2 Feeder 3 PF3 ,QF3 SW1 SW2 SW3 SW4-10 Distribution Networks Conventional distribution networks: Unidirectional power flows Limited number of generators Passive loads No active control, only reactive (protection) functions Voltage levels and power flows easily maintained by open-loop control Limited measurement and control required
  • 7. Energy storage G Feeder 1 WAN CONTROL Bus 1 Bus 2 Bus 7 Bus 9 Bus 10 Gen 10 Gen 8 Load 10 Load 9 Load 2 Load 7 PF1 ,QF1 PG8 ,QG8 PG5 ,QG5 PL10 ,QL10 PL9 ,QL9 PL7 ,QL7 PE ,QE PL2 ,QL2 Bus 4 Load 4 PL4 ,QL4 Bus 8 Bus 6 Load 6 PL6 ,QL6 Bus 3 Bus 5 Load 5 PL5 ,QL5 Load 3 PL3 ,QL3 Gen 3 PG3 ,QG3 Tr 8 Tr 4Tr 1 SW1-2 SW6-7 SW7-5 SW3-9 Feeder 2 PF2 ,QF2 Feeder 3 PF3 ,QF3 SW1 SW2 SW3 SW4-10 G G AC DC Distribution Networks Networks with DGs and active loads and: Bidirectional power flows Line congestion problems Voltage excursions Protection issues Only limited measurement and control provided Limited use of energy storage
  • 8. Energy storage G Feeder 1 MU WAN CONTROL MU MU Bus 1 Bus 2 Bus 7 Bus 9 Bus 10 Gen 10 Gen 8 Load 10 Load 9 Load 2 Load 7 PF1,QF1 PG8,QG8 PG5,QG5 PL10,QL10 PL9,QL9 PL7,QL7 PE,QE PL2,QL2 Bus 4 Load 4 PL4,QL4 Bus 8 Bus 6 Load 6 PL6,QL6 Bus 3 Bus 5 Load 5 PL5,QL5 Load 3 PL3,QL3 Gen 3 PG3,QG3 Tr 8 Tr 4Tr 1 SW1-2 SW6-7 SW7-5 SW3-9 Feeder 2 PF2,QF2 Feeder 3 PF3,QF3 Fragment 1 SW1 SW2 SW3 SW4-10 Fragment 3 Fragment 2 G G AC DC Distribution Networks Future distribution networks: Fragmented networks Various generators connected Active demand management and Smart loads Large scale and aggregated energy storage devices deployed Future distribution networks: RT measurements and control available RT Active and reactive control and protection functions RT arbitration for the resources RT energy trading between the new entities in the network
  • 9. Distribution Networks Research Objectives Devising algorithms for flexible real-time management of networks Integration of distributed generation Medium level generation 1MW-100MW Aggregated small scale generation Integration of large scale energy storage elements Reversible hydro, electrochemical, mechanical Aggregated storage such as electric vehicles Decentralised management functions Active demand side management More efficient use of installed network capacity Real-time energy trading Real-time active and reactive network control Network modelling assuming RT active management Developing scenarios for fragmented use of distribution networks
  • 10. Smart Energy Consumption Small Networks, Microgrids, Smart Buildings and Residential Loads Real-time demand side management and control Advanced measurement and load prediction Ability to control and limit consumption (Smart Appliances) Energy efficiency improvement Integration of local and on-site generation Renewable energy (solar, wind, geo-thermal) Gas micro-turbines, diesel generators, CHP Integration and management of energy storage elements Electrochemical (batteries, capacitor banks, fuel-cells) Exploiting the effects of thermal capacitance Security of supply Real-time energy trading
  • 11. Smart Energy Consumption A conventional microgrid: Only few generators and loads Islanded or grid-connected With or without energy storage elements
  • 12. Smart Energy Consumption Smart microgrids: Smart load controls and times energy consumption A consumer can also store energy and act as a generator too! Smart Generators benefit from embedded energy storage Network energy storage elements
  • 13. Smart Energy Consumption MU NETWORK MANAGER Control Room MU MU Network management: RT measurement and control Improved energy efficiency Improved security of supply RT energy trading between the entities in and out of the microgrid
  • 14. Electric Vehicles NETWORK MANAGER P,QAC DC DC DC DC DC DC DC Power Network Recharging Station - Provider Green Recharging Station - provider SuperGreen MU MU MU Recharging Station - Provider Green P1 P2 P3 Usage patterns and scenarios: Vehicles require recharging More than 90% of all vehicles stationary at any time New entities in the network An example of service based approach Car owner options Choosing the recharging station Recharging only Fast charging Timed charging Car owner services Energy storage Recharging station functions Energy management Optimisation of energy cost Recharging station services Fast charging Network energy storage Reactive power control Emergency power supply Energy trading Network manager services Energy trading Energy storage Energy transfer
  • 15. Electric Vehicles Investigating the impact of electric vehicle connection Network reinforcement Benefits analysis Development of recharging points and station Devising scenarios and usage patterns for vehicle recharging Using car batteries as an aggregated energy storage Providing service based solutions for: Battery charging Reactive power control Emergency power Demand side management RT energy trading Battery and supercapacitor technologies Investigating static and dynamic properties Life-cycle analysis
  • 16. Electrical Processes Lab Various IT equipment (PCs, routers) Network sensors (voltage, current, etc.) Ambient sensors (temperature, insolation, wind-speed) Distribution level automation (tele-controlled switchgear) Various energy source models (gas, solar, wind, fuel-cells) Energy storage elements (batteries, capacitors, fly-wheels) Various power converters (DC/DC, AC/DC, DC/AC) Distribution network impedance Flexible controller development and programming platforms
  • 17. IMDEA Lab
  • 18. Concluding Remarks SmartGrids will provide flexible, real-time management of the energy balance in the networks A number of new entities (smart loads, generators and storage) will be able to connect and offer their services in the energy market Network optimisation targets can be easily changed according to the market and economic conditions New, real-time, Smart energy management algorithms are needed and should be deployed in all levels of power networks

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