Information Technology in Power Systems: from Challenges to Solutions

Transcription

1 Information Technology in Power Systems: from Challenges to Solutions presented by ssistant Professor Yoash Levron Electrical Engineering Technion, Israel

2 Energy & Science The Short History of Energy & Science : Humans learn to use more energy Modern Life

3 Energy & Science for 70,000 years: Progress is enabled by improved energy conversion World Energy Consumption The industrial revolution

4 In the 20 th Century: Power Systems are a Major Success What are the major achievements of modern power systems? Efficient use of four primary energy sources: Coal, Gas, Oil and Nuclear. Energy in the form of electricity becomes dominant. Electric power networks deliver energy securely and efficiently. Low cost energy to anywhere and anyone!

5 However, exponential growth cannot last forever How long can we maintain this rate of growth?

6 Our high energy consumption changes the planet : Global Warming Depletion of Natural Sources Oil Peak The Greenhouse effect. Carbon dioxide in the atmosphere: 400 ppm, highest value during the past few million years. Earth average surface temperature rose by 0.75 C over the period of 1906 to re we before or after the peak?

7 Depletion of Natural Resources The industrial revolution Peak Oil What will be the next energy source? back to the stone age? Time

8 Depletion of Natural Resources

9 Renewable Energies an nswer? Wind Solar Hydro Solar Energy Installations Worldwide How much land area is required to power Israel (on average) with today s solar technology?

10 Renewable Energies an nswer? Wind Solar Hydro Solar Energy Installations Worldwide Estimated Land rea

11 Solar Energy Source of the Future?

12 Major Challenges in Modern Power Systems Use more Renewable Energy Sources Use more Electric Vehicles Use more Distributed Energy Sources Operate Power Grids More Efficiently and Reliably

13 Major Challenges in Modern Power Systems Use more Renewable Energy Sources Use more Electric Vehicles Information Technology? Use more Distributed Energy Sources Operate Power Grids More Efficiently and Reliably

14 Major Challenges in Modern Power Systems Today The Future?

15 Energy Management Center Today Centralized Power Systems Energy Management Center

16 The Future Distributed Power Systems? How do we synchronize many independent energy sources and make them work together?

17 Distributed Generation Control Challenges Global Power balance must be maintained Traditional energy sources Network Renewable energy sources loads

18 Distributed Generation Control Challenges Global Power balance must be maintained Traditional energy sources Network Renewable energy sources loads Local stability must be maintained

19 Distributed Sources and Energy Storage Distributed energy sources Energy Storage power input power output time

20 Power Sharing by Virtual Droop m P P * * E E n Q Q * *

21 Power Sharing by Virtual Droop utomatic Synchronization of frequency with no external control

22 Centralized and Distributed Power Systems Today s Grid: Centralized Topology Energy flows from central power plants to loads

23 Centralized and Distributed Power Systems Today s Grid: Centralized Topology Energy flows from central power plants to loads Future Grid: Distributed Topology? Small energy sources are distributed in the network How will energy flow in this network?

24 Centralized and Distributed Power Systems Many Challenges: How do we control this network? How do we design it? Future Grid: Distributed Topology? Small energy sources are distributed in the network How will energy flow in this network? How do we synchronize the elements to work together? How does energy flows in such a network? Is the network stable? Is it reliable? Is it efficient?

25 Smart Grids The missing link: Information Technology Incorporate advanced sensing, communication and control in power systems Today: Passive grids The Future? - Distributed energy sources - Power networks combined with information networks

26 major challenge in power systems: Information Technology - Sensing & Data Processing a) Integration of renewables and distributed energy sources b) Improved planning & design c) Improved reliability d) Reduced energy costs e) Higher efficiency What can we do with more information? e) Reduced equipment degradation f) Fault detection g) Reduced harmonic distortion h) Improved economic operation i) Integration of Electric Vehicles j) To make big changes in power systems, we must learn to predict how energy flows in power networks

27 Sensing and Estimation in Power Networks Our research group at the Technion studies the utilization of information in power systems. - How can we quantify information in power systems? - What minimal signals are required for sensing events in the network? - What can we study from partial information and local measurements? - How can we utilize information for better integration of renewables?

28 The Sensing Problem What is the minimal number of sensors required for sensing every voltage, current and power in a network? What is the minimal sensing array for sensing all the signals?

29 The Sensing Problem Intuitive answer: If we measure the voltage at every node, we can compute currents and powers using Kirchhoff laws. generator + - load voltage signal load generator + - Sensing voltages at these points enables a complete solution of the network

30 The Sensing Problem Intuitive answer: If we measure the voltage at every node, we can compute currents and powers using Kirchhoff laws. generator + - load minimal sensing array: load generator + - N voltage sensors that measure amplitude and phase Sensing voltages at these points enables a complete solution of the network

31 The Sensing Problem New problem: Relative phase is hard to measure voltage signal What is the relative phase of these voltage signals? voltage signal

32 The Sensing Problem - Voltage magnitudes sensors are very simple Relative phase sensors require synchronization over large distances and are much more complex. + - Im V1 V2 Re phasor diagram Relative phase is hard to measure

33 The Sensing Problem The rules in our sensing problem: We limit ourselves to local sensors - We can measure: - voltage magnitudes - current magnitudes - phase between local voltage and current - We cannot measure: - Relative phase between distinct voltages or currents i2 + - v1 v2 + - How many local sensors are needed to solve the network?

34 Complete Sensing using Magnitude Information In a general power system with N nodes (buses) the network is solved using: - N voltage magnitude sensors - N-1 current magnitude sensors This is the minimal sensing array using magnitude information. IEEE 30 bus system

35 Complete Sensing using Magnitude Information The resulting set of equations has no analytic solution, but sometimes we can solve it numerically. error

36 Sensing and Estimation in Power Networks However, when the set of equations is non-convex, finding a solution may be very hard error

37 Partial Information Consider a network in which the sensing array is less than minimal: This problem is under-determined because many network states are compatible with any set of measurements. What can we do with this partial data?

38 Partial Information Sparse Estimation Techniques Example: y 1 z 1 z 2 We wish to detect and locate a short to ground using two current sensors. v ac y 2 current sensors z 5 i 1 i 2 possible shorts z 4 z 3 i 4 i 3 Challenge: two current sensors are a sensing array that is smaller than minimal. By definition, the network state cannot be evaluated.

39 Partial Information Sparse Estimation Techniques Problem formulation: sensors data v ac 1 y1 i 2 y 2 i 3 Sensing Matrix (known) i i 4 y 1 y 2 z 1 current sensors z 5 i 1 i 2 i 4 z 2 possible shorts z 4 i 3 possible short currents z 3 Objective: given the measurements (y 1,y 2 ) T solve the currents (i 1 i 4 ) T and find the shorted node.

40 Partial Information Sparse Estimation Techniques new approach, using sparse representation methods: Example: 1 y i 2 y i 3 i i ssume the following measurements : 4 v ac y 1 current sensors y 2 z 1 z 5 y1 4 y2 12 i 1 i 2 i 4 Sparse vector z 2 possible shorts z 4 i 3 z 3 Only one solution is possible: i1 0 i 2 2 i 3 0 i 4 0 We can find the short current magnitude and location using partial data!

41 Partial Information Sparse Estimation Techniques Can we use the same technique to locate a short to ground in a large power network? sensor short sensor sensor sensor IEEE 30 bus system with 4 sensors

42 Partial Information Sparse Estimation Techniques Can we use the same technique to locate a short to ground in a large power network? short sensor Problem formulation: y 2 1 y 2 y 3 y i i i sensor sensor sensor sensors data sensing matrix possible short currents

43 Partial Information Sparse Estimation Techniques Can we use the same technique to locate a short to ground in a large power network? short sensor Problem formulation: y 2 1 y 2 y 3 y i i i sensor sensor sensor Solution: find the matrix column that is parallel to the measurements.

44 Partial Information Sparse Estimation Techniques Using sparse representation methods, rare events such as faults can be located with few sensors in large power networks. short sensor In this example, we use 4 sensors in a 30 bus network. sensor sensor sensor Using 4 sensors to detect and locate a random fault

45 Partial Information Sparse Estimation Techniques Using sparse representation methods, rare events such as faults can be located with few sensors in large power networks. short sensor Practical significance: We can locate many important events using very few sensors. sensor sensor Theoretical significance: information in an event is lower than previously believed, and is proportional to sparsity of the event rather than to the size of the network. sensor Using 4 sensors to detect and locate a random fault

46 Sensing and Estimation in Power Networks We are currently developing sparse estimation techniques for several types of events: sensor a. Power system faults b. Local instabilities c. Lightning strikes d. Electricity thefts e. Pollution (Harmonic Distortion) f. short sensor sensor sensor Using four sensors to detect and locate a random fault

47 Micro-grids Small power grids Local management of renewable and distributed energy sources. Enables to test new ideas in power systems.

48 Canada: the British-Columbia Boston Bar microgrid Sources: Hydro: 8 MW Load: 3 MW Grid-connected operation.

49 Greece: the Kythnos Island microgrid Sources: PV: 10 kw, Battery: 53 kwh, diesel generator: 5 kw, Load: 12 houses

50 Canada: the Fortis-lberta microgrid Sources: Wind: 3.8 MW, Hydro: 3.0 MW Grid-connected operation.

51 Japan: the Sendai microgrid Sources: Fuel-cells: 250 kw, Gas turbines: 700 kw, PV: 50 kw

52 כיצד אנחנו המורים יכולים לתרום? חזון? - מערכות אנרגיה מתקדמות חיוניות לעתיד של מדינת ישראל.? התפיסה של מקצועות חשמל מתח גבוה: - מקצוע ישן? מקצוע חדש? אולי שילוב - מה שבטוח, העתיד יציב בפנינו אתגרים לא פשוטים, שידרשו חשיבה חדשנית וכוח אדם מיומן. -