html5-img
1 / 16

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

pepin
Download Presentation

Distributed Intelligence in Critical Infrastructures for Sustainable Power

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related