Conventional reliability methods

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Table of contents

1. Power system and blackout risk
1.1 Complexity of the electric power system
1.2 A cascading failure
1.3 Industry practice
1.4 Methods of analysis
1.4.1. Power flow based analysis
1.4.2. The hidden failure
1.4.3. Resilience
1.4.4. High-level probabilistic models
1.4.4.1. CASCADE model
1.4.4.2. Network theory approaches
1.4.5. Critical components and high risk multiple contingencies
1.4.6. Recognizing patterns
1.4.7. Conventional reliability methods
1.5 Risk approach
1.5.1. Emerging technologies
1.5.2. Risk quantification approach
2. Design power network model based in Self Organized Criticality
2.1 Self-Organized Criticality
2.1.1. In power systems
2.1.2. In Colombian power systems.
2.1.2.1. Colombian power system description
2.1.2.2. Colombian database
2.2 Statistical analysis
2.2.1. α -stable Laws Properties
2.2.2. Particle Swarm Optimization for estimation of α -stable laws
2.2.3. α-stable distribution for Colombian power system data
2.3 Estimation of VaR of demand not supplied in electric power systems
3. Design of a simulation process to fit a power network behavior
3.1 Model general structure
3.2 Slow dynamics: Power network evolution
3.2.1. Power demand and generation power evolution
3.2.2. Network improvement strategy
3.2.2.1. Immediate strategy approach
3.2.2.2. Delayed strategy approach
3.2.3. Generation economic dispatch (OPF eco)
3.2.4. Final load power demand shedding and/or generation power re-dispatching 54
3.2.5. Identification of “power demand shedding” event
3.3 Fast dynamics: Cascade phenomena
3.3.1. Line trip initial occurrence
3.3.1.1. Overloaded line condition
3.3.1.2. Overloaded line trip occurrence
3.3.2. Power demand load shedding and/or generation power re-dispatching process
3.4 DC SPFM inputs and outputs summarize
3.4.1. DC SPFM input parameters summarize
3.4.2. DC SPFM outputs summarize
3.5 DC SPFM inputs from Colombian system
3.5.1. Parameter for Transmission DC SPFM Model:
3.5.2. Parameter for Demand DC SPFM Model:
3.5.3. Parameter for generation DC SPFM Model:
3.5.4. Parameter for line fault DC SPFM Model:
3.6 SOC Conditions Settings
3.6.1. Cellular automata
3.6.1.1. Local Phase
3.6.1.2. Accumulation phase
3.6.1.3. Transmission evolution capacity
3.6.1.4. Determination of coefficient (local phase and accumulation phase) with respect to the observable (historical data)
3.6.2. Parameter associated with SOC conditions setting
3.6.2.1. Physical point of view of SOC for power grid
3.6.2.2. Assumptions from the Colombian power system
4. Applications in day-ahead market in real power system. N-1 criteria.
4.1 General results
4.2 Reliability criteria model
4.3 Other interesting results
4.3.1 Critical lines
4.3.2 Probability of fault on particular line
4.3.3 Sequence of events
5. Conclusions