Graphical Ways to Visualize Operational Risk Results for Transmission System Contingencies
Abstract
:1. Introduction
- The first one is a lack of standard definitions of severity factor. Several definitions are used in research studies, but there is no commonly used set of definitions. Such are needed for a TSO to compare and interpret the results and to exchange information related to operational risk with other operators, for instance, for benchmarking.
- The second potential barrier is the absence of criteria to identify the permissible risk level in the grid; in other words, when does the operational risk become so high that mitigation actions should be taken?
- The third major barrier is the lack of methods to decide which mitigation methods are needed to reduce the operational risk once that risk is perceived as being too high. Method are needed for presentation and detailed analysis of operational risk results; for example, efficient ways to visualize the operational risk data.
- A fourth barrier is the lack of data on instantaneous failure and repair rate.
- The systematic identification of the data available after an ORA, as the base for making a decision, and the way in which this differs from the data available from the conventional (N-1) approach to operational security. This is addressed mainly in Section 3.1.
- The proposal of a heat-map that assists the TSOs in visualizing the contribution of individual contingencies to the operational risk and which potential component outages have the biggest impact on the operational risk. This method is introduced in Section 3.2.
- The proposal of a risk-based contingency chart that provides information to TSOs on the relative severity and probability of individual contingency cases for a specific operational state. This method is introduced in Section 3.3.
2. Contingency Computation and Analysis under Different Operational Scenarios
2.1. Component Unavailability Model
2.2. Contingency Analysis and Considered Severity Factor
- Overvoltage;
- Extreme loading;
- Undervoltage;
- System collapse.
2.3. Quantifying the Operational Risk
2.4. Operational Scenarios
- Std-GLM as the first operational scenario (OS-1);
- 40% increment in GLM as a second operational scenario (OS-2);
- 60% increment in GLM as a third operational scenario (OS-3);
- 80% increment in GLM as a fourth operational scenario (OS-4).
3. Proposed Methods for Visualization of the Results
3.1. Data Resulting from Operational Risk Assessment
- The probability of occurrence of the contingency case;
- Severity factor or factor quantifying the impact of the contingency case;
- Contribution to the operational risk of each contingency.
3.2. Contribution of Contingencies Visualization through Heat-Map
3.3. Contingencies Analysis through Risk-Based Contingency Chart
- LIHP (low impact high probability);
- MIHP (medium impact high probability);
- HIHP (high impact high probability);
- LIMP (low impact medium probability);
- MIMP (medium impact medium probability);
- HIMP (high impact medium probability);
- LILP (low impact low probability);
- MILP (medium impact low probability);
- HILP (high impact low probability).
4. Practical Interpretation of Contingencies Pattern and Its Contribution towards Operational Risk
4.1. Operational Risk of Extreme Loading (OREL)
4.1.1. Visualization through Heat-Map
4.1.2. Risk-Based Contingency Chart
4.2. Operational Risk of Overvoltage (OROV)
4.2.1. Visualization through Heat-Map
4.2.2. Risk-Based Contingency Chart
4.3. Operational Risk of Undervoltage (ORUV)
4.3.1. Visualization through Heat-Map
4.3.2. Risk-Based Contingency Chart
4.4. Operational Risk of System Collapse (ORSC)
4.4.1. Visualization through Heat-Map
4.4.2. Risk-Based Contingency Chart
5. Discussion
5.1. Data Resulting from Operational Risk Assessment
5.2. Continuous and Discrete Contingencies under the Integration of Intermittent Energy Resources
5.3. Standardization
5.4. N-3 Contingencies Visualization and Fast Filtration
6. Recommendations
7. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Nazir, Z.; Bollen, M.H.J. Graphical Ways to Visualize Operational Risk Results for Transmission System Contingencies. Electricity 2022, 3, 442-462. https://doi.org/10.3390/electricity3030023
Nazir Z, Bollen MHJ. Graphical Ways to Visualize Operational Risk Results for Transmission System Contingencies. Electricity. 2022; 3(3):442-462. https://doi.org/10.3390/electricity3030023
Chicago/Turabian StyleNazir, Zunaira, and Math H. J. Bollen. 2022. "Graphical Ways to Visualize Operational Risk Results for Transmission System Contingencies" Electricity 3, no. 3: 442-462. https://doi.org/10.3390/electricity3030023
APA StyleNazir, Z., & Bollen, M. H. J. (2022). Graphical Ways to Visualize Operational Risk Results for Transmission System Contingencies. Electricity, 3(3), 442-462. https://doi.org/10.3390/electricity3030023