An official website of the United States government
Earthquake damage scenarios are required to support design and analysis of spatially distributed infrastructure systems. In this paper we develop a computationally efficient set of damage scenarios for the Los Angeles water transmission system that considers ground motion and liquefaction. Each damage scenario describes one possible realization of damage to the pipe network and includes the corresponding multihazard scenario and an associated adjusted annual occurrence probability. Each damage scenario, which specifies the damage state of each pipe in the network, is defined to be physically realistic and consistent with the associated multihazard scenario. Together, when probabilistically combined, the set of damage scenarios with their occurrence probabilities matches the probabilistic hazard and component damage distributions. The scenarios are selected to be small in number so that subsequent analysis is efficient. We combine ideas from recently developed methods to generate sets of multihazard scenarios and damage scenarios for analysis of spatially distributed infrastructure systems. The method applied in this paper involves simulating multihazard, and a number of respective damage scenarios, and using an optimization to select a subset of damage scenarios and assign adjusted occurrence probabilities.
more »
« less
Quantifying the Earthquake Risk to the Electric Power Transmission System in Los Angeles at the Census Tract Level
This paper develops a probabilistic earthquake risk assessment for the electric power transmis- sion system in the City of Los Angeles. Via a dc load flow analysis of a suite of damage scenarios that reflect the seismic risk in Los Angeles, we develop a probabilistic representation for load shed during the restoration process. This suite of damage scenarios and their associated annual probabilities of occurrence are developed from 351 risk-adjusted earthquake scenarios using ground motion that collectively represent the seismic risk in Los Angeles at the census tract level. For each of these 351 earthquake scenarios, 12 damage scenarios are developed that form a probabilistic representation of the consequences of the earthquake scenario on the components of the transmission system. This analysis reveals that substation damage is the key driver of load shed. Damage to generators has a substantial but still secondary impact, and damage to transmission lines has significantly less impact. We identify the census tracts that are substantially more vulnerable to power transmission outages during the restoration process. Further, we explore the impact of forecasted increases in penetration of residential storage paired with rooftop solar. The deployment of storage paired with rooftop solar is represented at the census tract level and is assumed to be able to generate and store power for residential demand during the restoration process. The deployment of storage paired with rooftop solar reduces the load shed during the restoration process, but the distribution of this benefit is correlated with household income and whether the dwelling is owned or rented.
more »
« less
- PAR ID:
- 10565661
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- IEEE Access
- Volume:
- 12
- ISSN:
- 2169-3536
- Page Range / eLocation ID:
- 126019 to 126032
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)As new grid edge technologies emerge—such as rooftop solar panels, battery storage, and controllable water heaters—quantifying the uncertainties of building load forecasts is becoming more critical. The recent adoption of smart meter infrastructures provided new granular data streams, largely unavailable just ten years ago, that can be utilized to better forecast building-level demand. This paper uses Bayesian Structural Time Series for probabilistic load forecasting at the residential building level to capture uncertainties in forecasting. We use sub-hourly electrical submeter data from 120 residential apartments in Singapore that were part of a behavioral intervention study. The proposed model addresses several fundamental limitations through its flexibility to handle univariate and multivariate scenarios, perform feature selection, and include either static or dynamic effects, as well as its inherent applicability for measurement and verification. We highlight the benefits of this process in three main application areas: (1) Probabilistic Load Forecasting for Apartment-Level Hourly Loads; (2) Submeter Load Forecasting and Segmentation; (3) Measurement and Verification for Behavioral Demand Response. Results show the model achieves a similar performance to ARIMA, another popular time series model, when predicting individual apartment loads, and superior performance when predicting aggregate loads. Furthermore, we show that the model robustly captures uncertainties in the forecasts while providing interpretable results, indicating the importance of, for example, temperature data in its predictions. Finally, our estimates for a behavioral demand response program indicate that it achieved energy savings; however, the confidence interval provided by the probabilistic model is wide. Overall, this probabilistic forecasting model accurately measures uncertainties in forecasts and provides interpretable results that can support building managers and policymakers with the goal of reducing energy use.more » « less
-
Earthquakes cause outages of power transmission system components due to direct physical damage and also through the initiation of cascading processes. This article explores what are the optimal capacity investments to increase the resilience of electric power transmission systems to earthquakes and how those investments change with respect to two issues: (1) the impact of including cascades in the investment optimization model and (2) the impact of focusing more heavily on the early stages of the outages after the earthquake in contrast to more evenly focusing on outages across the entire restoration process. A cascading outage model driven by the statistics of sample utility data is developed and used to locate the cascading lines. We compare the investment plans with and without the modeling of the cascades and with different levels of importance attached to outages that occur during different periods of the restoration process. Using a case study of the Eastern Interconnect transmission grid, where the seismic hazard stems mostly from the New Madrid Seismic Zone, we find that the cascades have little effect on the optimal set of capacity enhancement investments. However, the cascades do have a significant impact on the early stages of the restoration process. Also, the cascading lines can be far away from the initial physically damaged lines. More broadly, the early stages of the earthquake restoration process is affected by the extent of the cascading outages and is critical for search and rescue as well as restoring vital services. Also, we show that an investment plan focusing more heavily on outages in the first 3 days after the earthquake yields fewer outages in the first month, but more outages later in comparison with an investment plan focusing uniformly on outages over an entire 6-month restoration process.more » « less
-
One of the main desired capabilities of the smart grid is ‘self‐healing’, which is the ability to quickly restore power after a disturbance. Due to critical outage events, customer demand or load is at times disconnected or shed temporarily. While deterministic optimisation models have been devised to help operators expedite load shed recovery by harnessing the flexibility of the grid's topology (i.e. transmission line switching), an important issue that remains unaddressed is how to cope with the uncertainty in generation and demand encountered during the recovery process. This study introduces two‐stage stochastic models to deal with these uncertain parameters, and one of them incorporates conditional value‐at‐risk to measure the risk level of unrecovered load shed. The models are implemented using a scenario‐based approach where the objective is to maximise load shed recovery in the bulk transmission network by switching transmission lines and performing other corrective actions (e.g. generator re‐dispatch) after the topology is modified. The benefits of the proposed stochastic models are compared with a deterministic mean‐value model, using the IEEE 118‐ and 14‐bus test cases. Experiments highlight how the proposed approach can serve as an offline contingency analysis tool, and how this method aids self‐healing by recovering more load shedding.more » « less
-
Abstract Climate change, urbanization, and economic growth are expected to drive increases in the installation of new air conditioners, as well as increases in utilization of existing air conditioning (AC) units, in the coming decades. This growth will provide challenges for a diversity of stakeholders, from grid operators charged with maintaining a reliable and cost-effective power system, to low-income communities that may struggle to afford increased electricity costs. Despite the importance of building a quantitative understanding of trends in existing and future AC usage, methods to estimate AC penetration with high spatial and temporal resolution are lacking. In this study we develop a new classification method to characterize AC penetration patterns with unprecedented spatiotemporal resolution (i.e. at the census tract level), using the Greater Los Angeles Area as a case study. The method utilizes smart meter data records from 180 476 households over two years, along with local ambient temperature records. When spatially aggregated, the overall AC penetration rate of the Greater Los Angeles Area is 69%, which is similar to values reported by previous studies. We believe this method can be applied to other regions of the world where household smart meter data are available.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/ACCESS.2024.3408797
