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Security of Supply Issues: Technical & Economic Aspects Chen-Ching Liu Advanced Power Technologies Center University of Washington
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Outline Blackout and cascaded events Shortage of transmission enhancement Defense system technology Flexible grid configuration Future areas - Transmission economics and Microgrids
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U.S. Blackout (Aug. 14, 2003) High temperature in Midwest. FE 870 MW nuclear power plant was down for maintenance. MISO SE is ineffective from 12:15 to 16:04. A sequence of lines outages westward and northward across Ohio and into Michigan, and then eastward, splitting New York from Pennsylvania and New Jersey. Eastlake unit 5 in northern Ohio tripped due to an exciter failure @ 13:31. A series of 138-kV lines tripped in the vicinity of Akron @ 15:39. 345-kV line (Stuart – Atlanta) tripped @ 14:02. Voltages in the Akron area fell below low limits. Loss of the FE Control Center function shortly after 14:14. 345-kV line (Sammis – Star) tripped @ 16:05 Star-South Canton tie line between FE and AEP tripped and reclosed @ 14:27. Transient instability began after 16:10, and large power swings occurred. The system becomes unstable The system become vulnerable Total blackout
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Some NERC Recommendations Strengthen the NERC compliance enforcement program. Evaluate vegetation management procedures and results. Evaluate reactive power and voltage control practices. Improve system protection to slow or limit the spread of future cascading outages. Install additional time-synchronized recording devices as needed. Re-evaluate system design, planning, and operating criteria.
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Load Shedding According to the Final NERC Report on August 14, 2003, Blackout, at least 1,500 to 2,500 MW of load in Cleveland-Akron area has had to be shed to prevent the blackout.
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Planned Generation Capacity & Transmission Enhancement in U.S. Actual data (1999~2000) Planned Capacity ( 25% increase ) Projected Demand ( 18% increase ) Planned Transmission ( 3.5% increase ) Estimated Capacity Margin (5% increase ) Source: “Reliability Assessment 2001-2010 Report” by NERC, 2001. Information Administration Website: “http://www.eia.doe.gov/cneaf/electricity/page/fact_sheets/transmission.html”
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Defense Plans Coordination of a number of special protection schemes for the entire system Modification is required (e.g., BPA needs to update the SPSs regularly) Build a defense system that performs self- healing control actions in an adaptive manner
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Strategic Power Infrastructure Defense (SPID) – Design self-healing strategies and adaptive reconfiguration schemes To achieve autonomous, adaptive, and preventive remedial control actions To provide adaptive/intelligent protection To minimize the impact of power system vulnerability Research consortium with UW, Iowa State, Arizona State and Virginia Tech, sponsored by EPRI, U.S. DoD and 4 institutions, $ 3M total, 1998-2001
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Vulnerability Assessment Vulnerability Regions A B CB A CB B Protection Voltage Stability Oscillator y Stability Transient Stability PiPi Dynamics and Control Communication
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Intelligent System Models for the Complex Networks Physics Model-based reasoning Rule-based system Evolutionary algorithm ANN Generic tasks Agent Multi-agent System Decision-making Forecasting Learning Self-healing Adaptation Team work Coordination Negotiation
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Multi-Agent System for SPID REACTIVE LAYER COORDINATION LAYER DELIBERATIVE LAYER Knowledge/Decision exchange Protection Agents Generation Agents Fault Isolation Agents Frequency Stability Agents Model Update Agents Command Interpretation Agents Planning Agent Restoration Agents Hidden Failure Monitoring Agents Reconfiguration Agents Vulnerability Assessment Agents Power System Controls Inhibition Signal Controls Plans/Decisions Event Identification Agents Triggering Events Event/Alarm Filtering Agents Events/Alarms Inputs Update Model Check Consistency Comm. Agent
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Adaptive Self-healing: Load Shedding Agent A control action might fail Reinforcement Learning – Autonomous learning method based on interactions with the agent ’ s environment – If an action is followed by a satisfactory state, the tendency to produce the action is strengthened
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Adaptive Self-healing: Load Shedding Agent The 179 bus system resembling the western U.S. system ETMSP simulation Remote load shedding scheme based on frequency decline + frequency decline rate Temporal Difference (TD) method is used for adaptation: Need to find the learning factor for convergence
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Adaptive Self-healing: Load Shedding Agent 179 bus system
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Adaptive Self-healing: Load Shedding Agent frequency Time (multiples of 0.02 sec)
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Adaptive Self-healing: Load Shedding Agent Number of trials Normalized frequency Expected normalized system frequency that makes the system stable “The load shedding agent is able to find the proper control action in an adaptive manner based on responses from the real power system”
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Flexible Grid Configuration to Enhance Robustness Flexible grid configuration can play a significant role in defense against catastrophic events Power infrastructure must be more intelligent and flexible – To allow coordinated operation and control measures to absorb the shock and minimize potential damages caused by radical events
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Area-Partitioning Algorithm To develop a k-way partitioning algorithm, which uses the information available in network matrices and divides the power grid into k disjoint areas while minimizing load-generation imbalance for each area
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Area-Partitioning Algorithm
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Flexible Grid Configuration by Partitioning Risk Management of Power Infrastructure Self-sufficient Sub-networks Flexible Grid Configuration by Partitioning Normal Configuration (Wide Area Grid) High Risk Alert Lower the Risk Level Alert is Over
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Cascaded Events - Simulation Compute Power Flows after Tripping – Six lines are found with limit violations – Trip these lines, Bus170 and 171 become isolated buses Identify New Network Configuration and Solve Power Flows Again – Fifteen lines are found with limit violations – Trip these lines, seven buses become isolated buses Continue This Simulation Procedure – Finally the system collapses: most transmission lines are tripped and most loads are lost
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Flexible Grid Configuration to Absorb the Shock Split the System into Two Areas – Seeds=[Bus 83, Bus 47] – Area One: 92 buses, 117 branches – Area Two: 87 buses, 140 branches
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WECC 179-bus System Example
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Split System into Two Areas
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Flexible Grid Configuration to Absorb the Shock Use “ Power Redispatching & Load Shedding ” in Area Two – Totally, 188 + 64.4 + 60 = 312.4 MW load are shed Bus # Original Load (MW) Load Shed (MW) Load Supplied (MW) 823918851 16793.464.4729 1541066601006
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Alert is Over (Wide-Area Grid)
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Investment & Return Analysis of Transmission Expansion Economics of transmission expansion should be analyzed from an investment / return point of view. - Economic value of transmission capacity improvement - Economic incentives of transmission owners - Economic incentives of generators Techniques for electricity price forecasting can be used for economic analysis of transmission expansion.
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Example: Investment & Return Analysis of Transmission Expansion The expected present value of the discounted stream of revenues ($100) exceeds the investment cost ($84). Invest now 012...T Period Initial Investment $15 $5 $15 $5... Revenue if Price is high Revenue if Price is low 50% Discount rate = 10% Cost of investment = $84
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Wait for One Period to Decide Don ’ t invest If price is low, $50 < $ 84 Don ’ t invest Invest If price is high, $150 > $ 84 Invest Expected payoff (= 0.5*($150-$84)/1.1 = $30). Waiting for one period is better than investing now since $30 > $16. 012...T Period Initial Investment $15 $5 $15 $5... Revenue if Price is high Revenue if Price is low 50% Discount rate = 10% Cost of investment = $84
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Value of Investment Opportunity An investment project whose revenue follows a geometric Brownian motion Value of waiting Overall value of the investment opportunity
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Micro Grid Concept Distant or remote locations -Islands -Regions with no pre-existing infrastructure Special power needs -Chip fabrication plants -Financial centers
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Wind Generators CADET Technical Brochure 68 “33.6 MW Wind Farm near Carno” EA, OECD, 1998
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Example
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Frequency Response with no Control Agent
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Inter-Machine Oscillations With no control agent there are clear indications of inter-machine oscillation Results: Unnecessary flow oscillations of power along tie lines Unnecessary stress on the machines Excessively large overshoots Excessively long settling times
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Control Agent Scheme Measure the load at each of the load buses. Measure the frequency at each of the load buses. When a load change is sensed the control agent generates control signals based on the current rotational energy of the rotors.
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Frequency Response with a Control Agent
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Grand Challenges Prevention of Major Blackouts Energy Crisis in Western U.S. Evolution of Electricity Markets Alternative Energy and Distributed Generation Engineering / Technology, Economics, Public Policy
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