Resilience of the power grid is most challenged at power blackouts since the issues that led to it may not be fully resolved by the time the power is back. In this paper, a Real-Time Energy Management Algorithm (RTEMA) has been developed to increase the resilience of power systems based on the controlled delivery grid (CDG) concept. In a CDG, loads communicate with a central controller, periodically sending requests for power. The central controller runs an algorithm, based on which it may decide whether to grant the requested energy fully or partially. Therefore, the CDG limits loads discretionary access to electric energy until all problems are resolved. The developed algorithm aims at granting most or all of the requested loads, while maintaining the health of the power system (i.e. the voltage at each bus, and the line loading are within acceptable limits), and minimizing the overall losses. An IEEE 30-bus standard Test Case, encountering a blackout condition, with high penetration of microgrids, has been used to test the developed algorithm. Results proved that the developed algorithm with the CDG have the potential to substantially increase the resilience of power systems.
more »
« less
Ranking the Impact of Interdependencies on Power System Resilience using Stratified Sampling of Utility Data
It is well known that interdependence between electric power systems and other infrastructures can impact energy reliability and resilience, but it is less clear which particular interactions have the most impact. There is a need for methods that can rank the relative importance of these interdependencies. This paper describes a new tool for measuring resilience and ranking interactions. This tool, known as Computing Resilience of Infrastructure Simulation Platform (CRISP), samples from historical utility data to avoid many of the assumptions required for simulation-based approaches to resilience quantification. This paper applies CRISP to rank the relative importance of four types of interdependence (natural gas supply, communication systems, nuclear generation recovery, and a generic restoration delay) in two test cases: the IEEE 39-bus test case and a 6394-bus model of the New England/New York power grid. The results confirm industry studies suggesting that a loss of the natural gas system is the most severe specific interdependence faced by this region.
more »
« less
- Award ID(s):
- 1735354
- PAR ID:
- 10404708
- Date Published:
- Journal Name:
- IEEE Transactions on Power Systems
- ISSN:
- 0885-8950
- Page Range / eLocation ID:
- 1 to 12
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
The increasing use of natural gas power generation has strengthened the interdependence between the power and natural gas subsystems in the integrated power and gas system (IPGS). Due to the interactions between the two subsystems, the disturbances in one system may spread to the other one, triggering a disruptive avalanche of subsequent failures in the IPGS. This paper presents a survey of cascading failure analysis for the IPGS. First, we identify the important features characterizing cascading dynamics in individual power and gas subsystems. Then, we will discuss the features for the cascading failure analysis in the IPGS and future research.more » « less
-
null (Ed.)Given increasing risk from climate-induced natural hazards, there is growing interest in the development of methods that can quantitatively measure resilience in power systems. This work quantifies resilience in electric power transmission networks in a new and comprehensive way that can represent the multiple processes of resilience. A novel aspect of this approach is the use of empirical data to develop the probability distributions that drive the computational model. This paper demonstrates the approach by measuring the impact of one potential improvement to a power system. Specifically, we measure the impact of additional distributed generation (DG) on power system resilience, and find that DG can substantially increase resilience.more » « less
-
Abstract Critical infrastructure networks enable social behavior, economic productivity, and the way of life of communities. Disruptions to these cyber–physical–social networks highlight their importance. Recent disruptions caused by natural phenomena, including Hurricanes Harvey and Irma in 2017, have particularly demonstrated the importance of functioning electric power networks. Assessing the economic impact (EI) of electricity outages after a service disruption is a challenging task, particularly when interruption costs vary by the type of electric power use (e.g., residential, commercial, industrial). In contrast with most of the literature, this work proposes an approach to spatially evaluate EIs of disruptions to particular components of the electric power network, thus enabling resilience‐based preparedness planning from economic and community perspectives. Our contribution is a mix‐method approach that combines EI evaluation, component importance analysis, and GIS visualization for decision making. We integrate geographic information systems and an economic evaluation of sporadic electric power outages to provide a tool to assist with prioritizing restoration of power in commercial areas that have the largest impact. By making use of public data describing commercial market value, gross domestic product, and electric area distribution, this article proposes a method to evaluate the EI experienced by commercial districts. A geospatial visualization is presented to observe and compare the areas that are more vulnerable in terms of EI based on the areas covered by each distribution substation. Additionally, a heat map is developed to observe the behavior of disrupted substations to determine the important component exhibiting the highest EI. The proposed resilience analytics approach is applied to analyze outages of substations in the boroughs of New York City.more » « less
-
Natural disasters has been causing an increasing amount of economic losses in the past two decades. Natural disasters, such as hurricanes, winter storms, and wildfires, can cause severe damages to power systems, significantly impacting industrial, commercial, and residential activities, leading to not only economic losses but also inconveniences to people’s day-today life. Improving the resilience of power systems can lead to a reduced number of power outages during extreme events and is a critical goal in today’s power system operations. This paper presents a model for decentralized decision-making in power systems based on distributed optimization and implemented it on a modified RTS-96 test system, discusses the convergence of the problem, and compares the impact of decision-making mechanisms on power system resilience. Results show that a decentralized decision-making algorithm can significantly reduce power outages when part of the system is islanded during severe transmission contingencies.more » « less