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Distributed Intelligence in Critical Infrastructures for Sustainable Power

Distributed Intelligence in Critical Infrastructures for Sustainable Power. Luc Hamilton. IT & Energy: General Background. Energy: becomes increasingly decentralized network (“distributed, virtual utility”). Note similarity with e-business developments

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Distributed Intelligence in Critical Infrastructures for Sustainable Power

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  1. Distributed Intelligence in Critical Infrastructures for Sustainable Power Luc Hamilton

  2. IT & Energy: General Background • Energy: becomes increasingly decentralized network (“distributed, virtual utility”). • Note similarity with e-business developments • Internet/Web: “everything” becomes part of it, including even home appliances (“ambient intelligence”) • Convergence: IT and Energy are distributed critical infrastructures that can beneficially be used together • “Out of the box”: new systems thinking needed • Crossing traditional in-building/access/network boundaries gives interesting possibilities • Business and technology aspects must be simultaneously dealt with to make progress: innovation and its adoption

  3. CRISP Project Objective: • To investigate and test how ICT-based distributed intelligence can be exploited for the management of power networks with high degrees of Distributed Energy Resources (DER) and renewable energy (sustainability) • Duration: 3 years, Oct. 2002 – Oct. 2005 • Budget: EUR 3.1 M • Effort: 22 person-years • EU-EESD project No. ENK8-CT-2002-00673 • Website: http://www.ecn.nl/crisp

  4. ECN (Netherlands) ENECO (Netherlands) INPG (France) Schneider (France) EnerSearch (Sweden) Sydkraft (Sweden) BTH (Sweden) ABB (Sweden) CRISP Partners Consortium: • ECN (NL) • ENECO (NL) • INPG/LEG (F) • Schneider (F) • EnerSearch (SE) • Sydkraft (SE) • BTH (SE) • ABB (SE)

  5. CRISP Approach • CRISP: new operating strategies for high-DER power networks enabled by recent progress in intelligent ICT • CRISP concentrates on specific practical scenarios: • Market-oriented demand-supply matching to increase the cost-effectiveness of DER network operations • Online distant fault detection and recovery, ensuring robustness and performance of high-DER networks • Intelligent load shedding in emergency situations • Multi-agent systems for online control of DER supply, demand and storage, providing bottom-up optimization strategies • Intelligent decision support for risk and security analysis of DER networks, including cost-benefit and priority analysis • Results: novel high-DER strategies, corresponding ICT tools, validating field/lab experiments (NL, F, SE), guidelines for advanced ICT use in DER networks

  6. CRISP Workplan

  7. WP I: ICT-enabled scenarios + strategies for high-DG power networks • Functional specs of the grid with high degree DG • modelling operative roles of players • baseline reference model for scenarios/studies/tools • Cost-effective distribution through market-oriented on-line demand-supply matching • 15 min to 1 day ahead matching • cost terms + utilisation RES + security/reliability • multi-agent algorithms / micro-economic optimisation theory

  8. WP I: ICT-enabled scenarios + strategies for high-DG power networks • DG as means to increase system robustness • potential of DG for robustness in major disturbances • benefits of DG for distribution networks • increase system autonomy / islanded supply • modular communication and control • Fault detection, analysis and diagnostics in high-DG distribution systems • new structures and operational environment • investigate need for new functions • improving islanding detection reliability • smart sensors, measurement, monitoring, • Artificial Intelligence, fuzzy, real time processing

  9. WP I: ICT-enabled scenarios + strategies for high-DG power networks • Intelligent load shedding • improve system stability • improve load shedding schemes; individual load objects • strategies to keep track on load available to shed • algorithms to find optimal “amount” and “location” • algorithms for detection disturbance +initiate shedding • Network security models and their economics • incorporate security models from information networking in protection systems • include risk analysis methodologies to protect value-chains and business processes • architecture for protection of baseline reference model

  10. WP I: ICT-enabled scenarios + strategies for high-DG power networks • Highly distributed network architectures and simulations • collection of functional components and protocols • “virtual utility”, high reliability, electronic power market • modelling architecture and assigning functionality and roles to individual nodes • case study simulations using tools of WP II

  11. WP II: Intelligent distributed ICT-development + tools for power applications • Business, application and ICT technology requirements for tools • ICT-node network and Power Delivery network have different requirements • tools must be able to handle dynamically configuration settings • Multi-agent simulation tool for market-oriented distributed demand-supply matching • competitive and co-operative scheduling, optimal use of deferrable load, scalability • implementation of e-market algorithms in power applications • Library of agents and algorithms

  12. WP II: Intelligent distributed ICT-development + tools for power applic. • Simulation tool for fault detection and diagnostics • locate fault, investigate differences in type and criticism of faults • intelligent techniques used based on output of WP I • use as prototype for “off-line” tests • Decision support tool for network security models and their economics • to identify proper safeguards at given risk/benefit level • cost/benefit based on analysis of value-chains in business processes at risk • evaluation on different scenarios

  13. WP III: Implementation, Experiments and Tests • Preparation, execution and evaluation of experiments • recommendations for strategic use of intelligent ICT’s in power networks • 3 experiments in 3 different countries • Field test with 50 different CHP units in various segments (horticulture, industry, households), focussed on demand-supply matching (NL) • Lab-tests in industrial real-time simulator of power networks ARENE and analogue power system simulator, focussed on fault diagnostics (F) • Lab- and field test for testing load shedding scenarios, Öland (S)

  14. CRISP builds on earlier work For example: • PALAS EU project • Intelligent Internet solutions for building control and energy management, realized by agent-mediated e-markets • SMART project: field experiment in office building (ECN, Petten, NL) • New field experiments underway (ECN, NL) • Advances in IT: e-markets and Internet agents

  15. Distributed Intelligence • Exploit distributed intelligence for DER networks • Demonstrate by realistic scenarios • E.g. Optimized DSM by e-markets, intelligent load shedding • And by experiments • NL (field test DER) , F (lab tests), SE (Öland operation) • Bridge gap between latest ICT advances in ICT and their strategic use for power applications • Links EU-IST and EESD programs • Combine capabilities of two critical infrastructures: ICT and power networks

  16. For more information • CRISP website:www.ecn.nl/crisp • www.enersearch.com, www.ecn.nl • CRISP flyer

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