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The AgentMatcher Architecture Applied to Power Grid Transactions

The AgentMatcher Architecture Applied to Power Grid Transactions. Riyanarto Sarno Faculty of Information Technology , Sepuluh Nopember Institute of Technology Surabaya, 60111 Indonesia Lu Yang, Virendra C. Bhavsar Faculty of Computer Science, University of New Brunswick

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The AgentMatcher Architecture Applied to Power Grid Transactions

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  1. The AgentMatcher Architecture Applied to Power Grid Transactions Riyanarto Sarno Faculty of Information Technology, Sepuluh Nopember Institute of Technology Surabaya, 60111 Indonesia Lu Yang, Virendra C. Bhavsar Faculty of Computer Science, University of New Brunswick Fredericton, NB, E3B 5A3 Canada Harold Boley Institute for Information Technology e-Business National Research Council of Canada Fredericton, NB, E3B 9W4 Canada 1 Lu Yang

  2. Outline • Introduction • A Multi-Agent System for Power Plant Transactions: Transactions consist of determining the most economical power plants to satisfy electricity demands and operating constraints • The AgentMatcher Architecture • Similarity Computation • Ranked Pairing • Focused Negotiation • Conclusion 2 Lu Yang

  3. Jawa-Bali Island Power Distributor Power Plant Geographical Regions of Indonesia 4 Lu Yang

  4. Introduction • Computational grids: can support power grids • Vision: Intelligent power grids compute their own transactions • Power grids: electricity sellers and buyers 3 Lu Yang

  5. Power Distributor 1 Power Plant 1 Power Sellers Power Buyers Power Distributor 2 Power Plant 2 Virtual Power Grid Market . . . . . . Power Distributor n Power Plant m Scenario of Power Plant Application of our Multi-Agent System 5 Lu Yang

  6. seller agents buyer agents Similarity Computation Ranked Pairing Focused Negotiation The AgentMatcher Architecture ranking similarity table pairs of buyer and seller agents finalized transaction 6 Lu Yang

  7. Power Power availability availability quality quality price price 0.1 0.3 capacity capacity 0.2 0.1 0.4 0.2 0.3 0.4 Parameters Fast Load Load Parameters Large Small Fast freq freq 100% 100% 75% 75% voltage voltage 0.3 0.3 0.1 0.8 0.4 0.6 phase phase 25% 25% 0.5 0.1 50% 50% 0.1 0.2 0.2 0.1 0.2 0.1 Good Low Good High Bad Good Low Average High Low Low Bad High Low Seller Tree Buyer Tree Similarity Computation Similarity: 0.9328 (A(Si ) (wi + w'I )/2) 7 Lu Yang

  8. Ranked Pairing Initial Table (b3, s4) 8 Lu Yang

  9. Ranked Pairing (b1, s1) (b2, s2) 9 Lu Yang

  10. Paired buyer and seller agents buyers sellers similarity s4 b3 0.96 s1 b1 0.84 s2 b2 0.75 s5 b4 0.69 Ranked Pairing (b4, s5) 10 Lu Yang

  11. Ranked Pairing Special Case 1 11 Lu Yang

  12. Ranked Pairing Special Case 2 12 Lu Yang

  13. Power availability quality price 0.1 0.2 capacity 0.4 0.3 Parameters Load … … Middle Large Focused Negotiation-An Example (I) Suppose that the total demand of capacity is: 125 MW 13 Lu Yang

  14. P2: P1: price($) capacity(MW) price($) sellers capacity(MW) sellers s1 s3 20 5 2 10 s2 s12 10 8 5 10 s4 s10 20 3 20 7 s5 s8 4 20 20 5 ∑=70 ∑=40 P3: price($) capacity(MW) sellers s6 5 6 s9 5 3 s7 10 12 s11 18 15 ∑=35 Focused Negotiation-An Example (II) total demand 125 MW 14 Lu Yang

  15. P3: price($) capacity(MW) sellers s9 3 5 s6 6 5 s7 10 12 s11 18 15 ∑=35 Focused Negotiation-An Example (III) Price ($/MWh) Clearing Price Q7 12 P7 Q6 6 P6 Q9 3 P9 -Q 110 115 120 125 130 Capacity (MW) 15 Lu Yang

  16. Conclusion • Tree similarity is the basis for subsequent ranked pairing and focused negotiation • The AgentMatcher architecture has been implemented in java for similarity computation and ranked pairing • A capacity/price-focused negotiation algorithm has been developed for transactions in power grids • This negotiation algorithm can be extended for further power attributes 16 Lu Yang

  17. Thank you!

  18. “The Computational Grid” is analogous to Electricity (Power) Grid and the vision is to offer a (almost) dependable, consistent, pervasive, and inexpensive access to high-end resources irrespective their location of physical existence and the location of access.

  19. tree t tree t´ Car Car Make Year Year Make 0.7 0.3 0.7 0.3 2002 Ford Ford 1999 0 1

  20. tree t´ tree t vehicle vehicle autumn summer autumn summer 0.5 0.5 0.5 0.5 auto auto auto auto make make year year make year make year 0.3334 0.3334 0.3333 0.3333 0.3334 0.3334 model 0.3333 model 0.3333 model model 0.3333 0.3333 0.3333 0.3333 van ford van ford truck van ford ford 1999 1999 2000 2001 mini big big big mini mini 0.5 0.5 0.5 0.5 0.5 0.5 free star e-series wagon e-series wagon free star montery free star (A(si)(wi + w'i)/2)

  21. PowerPlant capacity price 0.8 0. 2 PowerPlant Middle High t2 price capacity 0.8 PowerPlant 0. 2 High Middle t1 price capacity 0. 2 0.8 High Middle t3 where n = the number of weight pairs

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