Expansion Planning of Electricity Grid to Mitigate Wildfire Risks through Solar Integration, Line Modifications, and New Line Additions

Grunnleggende konsepter

A two-stage robust optimization model is proposed to determine the optimal expansion planning decisions, including distributed solar generation, modification of existing power lines, and addition of new lines, to serve customers while mitigating the risk of wildfires.

Sammendrag

The paper presents a two-stage robust optimization model for electricity grid expansion planning in areas at risk of wildfires. The key highlights are:

1. The model quantifies the risk of fire ignition by power lines under different weather conditions using a machine learning-based approach developed in previous work. This fire ignition score is integrated into the expansion planning problem.

2. The first-stage of the optimization problem minimizes the operation cost by considering three decision variables: distributed solar generation, modification of existing power lines, and addition of new power lines.

3. The second-stage problem realizes the uncertainty in system demand and solar energy generation to find the worst-case realization.

4. The impact of de-energization of high-risk lines on distributed solar generation is assessed. The number of hours each line is energized and the total load shedding during the 10-year planning horizon are evaluated.

5. The effectiveness of the proposed algorithm is demonstrated on a 6-bus and an IEEE 118-bus system. Different uncertainty levels for system demand and solar energy integration are considered to analyze their impact on the total operation cost.

6. The results show that distributed solar generation, modification of existing lines, and addition of new lines can help serve customers in power systems at risk of severe wildfires.

Statistikk

The total fire ignition score for the 6-bus system ranges from 0.16 to 7.75 over the 10-year period, depending on the wind speed scenario.
The net demand in the 6-bus system increases from 1078 MW in year 1 to 1288 MW in year 10.
The average wind speed in the 6-bus system ranges from 28 mph to 68 mph over the 10-year period, depending on the scenario.
In the IEEE 118-bus system, the total fire ignition score ranges from 6.78 to 18.06 over the 10-year period, depending on the percentage of lines at risk.
The net demand in the IEEE 118-bus system increases from 50032 MW in year 1 to 57471 MW in year 8.
The average wind speed in the IEEE 118-bus system ranges from 58 mph to 67 mph over the 10-year period, depending on the scenario.

Sitater

"The utilities consider public safety power shut-offs imperative for the mitigation of wildfire risk."
"Power lines are listed as a cause of wildfire ignitions."
"The breaking of towers and failure of power lines are among the faults that could occur due to the high wind speeds."

Viktige innsikter hentet fra

The Dilemma of Electricity Grid Expansion Planning in Areas at the Risk of Wildfire

by Muhammad Was... klokken arxiv.org 09-11-2024

https://arxiv.org/pdf/2409.00334.pdf

Dypere Spørsmål

How can the proposed expansion planning model be extended to consider other natural disaster risks, such as earthquakes or floods, in addition to wildfires?

The proposed expansion planning model can be extended to incorporate other natural disaster risks, such as earthquakes and floods, by integrating additional risk assessment metrics and decision variables that reflect the unique characteristics of these hazards. For instance, the model can include a seismic risk score that quantifies the vulnerability of power lines and substations to earthquake-induced damage. This score can be derived from historical seismic data, geological surveys, and structural assessments of existing infrastructure.
Similarly, for flood risks, the model can incorporate hydrological data to evaluate the likelihood of flooding in specific areas, which can affect the physical integrity of power lines and substations. Decision variables can be introduced to represent the modification of infrastructure, such as elevating substations or reinforcing power lines in flood-prone areas.
Moreover, the optimization framework can be adapted to consider multi-hazard scenarios, where the interaction between different natural disasters is analyzed. This would involve developing a comprehensive risk profile for each power line and bus, taking into account the combined effects of wildfires, earthquakes, and floods. By employing a multi-objective optimization approach, the model can balance the trade-offs between cost, reliability, and resilience against various natural disasters, ultimately leading to a more robust and adaptable power system.

What are the potential trade-offs between the cost of hardening power lines versus the cost of distributed solar generation and load shedding in terms of overall system resilience?

The trade-offs between the cost of hardening power lines and the costs associated with distributed solar generation and load shedding are multifaceted and involve several key considerations.

Cost of Hardening Power Lines: Hardening measures, such as modifying existing lines or installing new lines in less hazardous areas, can be expensive due to the physical nature of the infrastructure changes. These costs include materials, labor, and potential disruptions during construction. However, hardening can significantly reduce the risk of fire ignitions and enhance the reliability of the power system during extreme weather events.

Cost of Distributed Solar Generation: Investing in distributed solar generation can provide a more flexible and decentralized approach to energy supply. While the initial installation costs may be high, solar generation can reduce reliance on traditional power lines and mitigate the impact of load shedding during emergencies. Additionally, solar energy can be harnessed in areas that are less prone to natural disasters, thus enhancing overall system resilience.

Load Shedding Costs: Load shedding represents a last-resort measure to maintain system stability during peak demand or emergencies. The costs associated with load shedding include not only the direct economic losses from unserved demand but also the potential long-term impacts on customer satisfaction and utility reputation. Frequent load shedding can lead to increased customer churn and reduced trust in the utility's ability to provide reliable service.

In summary, while hardening power lines may incur significant upfront costs, it can lead to long-term savings by preventing outages and enhancing system reliability. Conversely, investing in distributed solar generation can provide a more resilient energy supply but may require careful planning to ensure that it complements existing infrastructure. The optimal strategy will depend on the specific context, including the frequency and severity of natural disasters, regulatory frameworks, and the economic landscape of the region.

How can the insights from this study be applied to improve the resilience of power systems in developing countries that are also facing increasing risks from climate change-induced natural disasters?

The insights from this study can be instrumental in enhancing the resilience of power systems in developing countries facing climate change-induced natural disasters through several key strategies:

Risk Assessment and Prioritization: Developing countries can adopt the risk assessment methodologies outlined in the study to identify vulnerable areas within their power systems. By quantifying the risks associated with various natural disasters, utilities can prioritize investments in infrastructure improvements and resilience measures where they are most needed.

Integration of Renewable Energy: The study emphasizes the importance of distributed solar generation as a means to enhance system resilience. Developing countries can leverage their abundant solar resources to diversify their energy mix, reduce dependence on centralized power generation, and improve energy access in remote areas. This decentralized approach can also mitigate the impacts of natural disasters by providing localized energy sources that are less susceptible to widespread outages.

Community Engagement and Capacity Building: Engaging local communities in the planning and implementation of resilience measures is crucial. By involving stakeholders in decision-making processes, utilities can ensure that the solutions are tailored to the specific needs and conditions of the communities they serve. Capacity building initiatives can also empower local technicians and engineers to maintain and operate renewable energy systems effectively.

Flexible and Adaptive Planning: The study's robust optimization framework can be adapted to the unique challenges faced by developing countries. By incorporating flexibility into expansion planning, utilities can better respond to changing conditions, such as fluctuating demand and the increasing frequency of natural disasters. This adaptive approach can help ensure that power systems remain reliable and resilient in the face of uncertainty.

International Collaboration and Funding: Developing countries can seek partnerships with international organizations, NGOs, and private sector stakeholders to access funding and technical expertise for resilience-building initiatives. Collaborative efforts can facilitate knowledge sharing and the implementation of best practices in power system resilience.

By applying these insights, developing countries can enhance the resilience of their power systems, ensuring reliable electricity access while effectively managing the risks posed by climate change and natural disasters.