### Core team:

# Seth Blumsack

### University of Vermont

### Department of Mathematics and Statistics, Professor

None

#### Most recent papers:

When are decentralized infrastructure networks preferable to centralized ones?.

Paul Hines, Seth Blumsack, Markus Schlaepfer. Proceedings of the 50th Hawaii International Conference on System Sciences, , , 2017.[pdf] [journal page]

**Abstract:**

Many infrastructure networks, such as power, water, and natural gas systems, have similar properties governing flows. However, these systems have distinctly different sizes and topological structures. This paper seeks to understand how these different features can emerge from relatively simple design principles. Specifically, we work to understand the conditions under which it is optimal to build small decentralized network infrastructures, such as a microgrid, rather than centralized ones, such as a large high-voltage power system. While our method is simple it is useful in explaining why sometimes, but not always, it is economical to build large, interconnected networks and in other cases it is preferable to use smaller, distributed systems. The results indicate that there is not a single set of infrastructure cost conditions that cause a transition from centralized networks being optimal, to decentralized architectures. Instead, as capital costs increase network sizes decrease gradually, according to a power-law. And, as the value of reliability increases, network sizes increase abruptlyâ€”there is a threshold at which large, highly interconnected networks are preferable to decentralized ones.

Centralized versus decentralized infrastructure networks.

Paul Hines, Seth Blumsack, Markus Schlaepfer. Preprint, 2015.[pdf] [journal page]

**Abstract:**

While many large infrastructure networks, such as power, water, and natural gas systems, have similar physical properties governing flows, these systems tend to have distinctly different sizes and topological structures. This paper seeks to understand how these different size-scales and topological features can emerge from relatively simple design principles. Specifically, we seek to describe the conditions under which it is optimal to build decentralized network infrastructures, such as a microgrid, rather than centralized ones, such as a large high-voltage power system. While our method is simple it is useful in explaining why sometimes, but not always, it is economical to build large, interconnected networks and in other cases it is preferable to use smaller, distributed systems. The results indicate that there is not a single set of infrastructure cost conditions under which optimally-designed networks will have highly centralized architectures. Instead, as costs increase we find that average network sizes increase gradually according to a power-law. When we consider the reliability costs, however, we do observe a transition point at which optimally designed networks become more centralized with larger geographic scope. As the losses associated with node and edge failures become more costly, this transition becomes more sudden.

Correcting optimal transmission switching for AC power flows.

Clayton Barrows, Seth Blumsack, Paul Hines. System Sciences (HICSS), 2014 47th Hawaii International Conference on, 2374-2379, , 2014.[pdf] [journal page]

**Abstract:**

Optimal Transmission Switching (OTS) has demonstrated significant savings potential on test systems when formulated in a linearized DC power flow framework. OTS solutions generated from DC models, however, are not guaranteed to produce a feasible AC dispatch. Additionally, whether AC-feasible OTS solutions will generate cost savings similar to those suggested in the DC model is not guaranteed. We present a method to correct OTS solutions obtained in the DC model to ensure feasible AC power flow solutions. When applied to the RTS-96 benchmark network, the method achieves results that are both AC feasible and generate significant system cost reductions - in some cases larger than the cost reductions suggested by the DC OTS.

Estimating the impact of fuel-switching between liquid fuels and electricity under electricity-sector carbon.

Jonathan Dowds, Paul Hines, Seth Blumsack. Socio-Economic Planning Sciences, , 47, 2013.[pdf] [journal page]

**Abstract:**

Switching from liquid fuels to electricity in the transportation and heating sectors can result in greenhouse gas emissions reductions. These reductions are maximized when electricity-sector carbon emissions are constrained through policy measures. We use a linear optimization, generation expansion/dispatch model to evaluate the impact of increased electricity demand for plug-in electric vehicle charging on the generating portfolio, overall generating fuel mix, and the costs of electricity generation. We apply this model to the PJM Interconnect and ISO-New England Regional Transmission Organization service areas assuming a CO2 pricing scheme that is applied to the electricity sector but does not directly regulate emissions from other sectors. We find that a shift from coal toward natural gas and wind generation is sufficient to achieve a 50% reduction in electricity-sector CO2 emissions while supporting vehicle charging for 25% of the vehicle fleet. The price impacts of these shifts are sensitive to demand side price responsiveness and the capital costs of new wind construction.

Multi-attribute Partitioning of Power Networks Based on Electrical Distance.

Clayton Barrows, Mahendra Patel, Eduardo Cotilla-Sanchez, Paul Hines, Seth Blumsack. IEEE Transactions on Power Systems, , , 2013.[pdf] [journal page]

**Abstract:**

Identifying coherent sub-graphs in networks is important in many applications. In power systems, large systems are divided into areas and zones to aid in planning and control applications. But not every partitioning is equally good for all applications; different applications have different goals, or attributes, against which solutions should be evaluated. This paper presents a hybrid method that combines a conventional graph partitioning algorithm with an evolutionary algorithm to partition a power network to optimize a multi-attribute objective function based on electrical distances, cluster sizes, the number of clusters, and cluster connectedness. Results for the IEEE RTS-96 show that clusters produced by this method can be used to identify buses with dynamically coherent voltage angles, without the need for dynamic simulation. Application of the method to the IEEE 118 bus and a 2383 bus case indicates that when a network is well partitioned into zones, intra-zone transactions have less impact on power flows outside of the zone; ie, good partitioning reduces loop flows. This property is particularly useful for power system applications where ensuring deliverability is important, such as transmission planning or determination of synchronous reserve zones.

Comparing the Topological and Electrical Structure of the North American Electric Power Infrastructure.

Eduardo Cotilla-Sanchez, Paul Hines, Clayton Barrows, Seth Blumsack. IEEE Systems Journal, 616-626, 6, 2012.[pdf] [arXiv]

**Abstract:**

The topological (graph) structure of complex networks often provides valuable information about the performance and vulnerability of the network. However, there are multiple ways to represent a given network as a graph. Electric power transmission and distribution networks have a topological structure that is straightforward to represent and analyze as a graph. However, simple graph models neglect the comprehensive connections between components that result from Ohm's and Kirchhoff's laws. This paper describes the structure of the three North American electric power interconnections, from the perspective of both topological and electrical connectivity. We compare the simple topology of these networks with that of random (Erdos and Renyi, 1959), preferential-attachment (Barabasi and Albert, 1999) and small-world (Watts and Strogatz, 1998) networks of equivalent sizes and find that power grids differ substantially from these abstract models in degree distribution, clustering, diameter and assortativity, and thus conclude that these topological forms may be misleading as models of power systems. To study the electrical connectivity of power systems, we propose a new method for representing electrical structure using electrical distances rather than geographic connections. Comparisons of these two representations of the North American power networks reveal notable differences between the electrical and topological structure of electric power networks.

Topological models and critical slowing down: Two approaches to power system blackout risk analysis.

Paul Hines, Eduardo Cotilla-Sanchez, Seth Blumsack. System Sciences (HICSS), 2011 44th Hawaii International Conference on, 1-10, , 2011.[pdf] [journal page]

**Abstract:**

This paper describes results from the analysis of two approaches to blackout risk analysis in electric power systems. In the first analysis, we compare two topological (graph-theoretic) methods for finding vulnerable locations in a power grid, to a simple model of cascading outage. This comparison indicates that topological models can lead to misleading conclusions about vulnerability. In the second analysis, we describe preliminary results indicating that both a simple dynamic power system model and frequency data from the August 10, 1996 disturbance in North America show evidence of critical slowing down as the system approaches a failure point. In both examples, autocorrelation in the time-domain signals (frequency and phase angle), significantly increases before reaching the critical point. These results indicate that critical slowing down could be a useful indicator of increased blackout risk.

Do topological models provide good information about vulnerability in electric power networks?.

Paul Hines, Eduardo Cotilla-Sanchez, Seth Blumsack. Chaos, , 20, 2010.[pdf] [arXiv]

**Abstract:**

In order to identify the extent to which results from topological graph models are useful for modeling vulnerability in electricity infrastructure, we measure the susceptibility of power networks to random failures and directed attacks using three measures of vulnerability: characteristic path lengths, connectivity loss and blackout sizes. The first two are purely topological metrics. The blackout size calculation results from a model of cascading failure in power networks. Testing the response of 40 areas within the Eastern US power grid and a standard IEEE test case to a variety of attack/failure vectors indicates that directed attacks result in larger failures using all three vulnerability measures, but the attack vectors that appear to cause the most damage depend on the measure chosen. While our topological and power grid model results show some trends that are similar, there is only a mild correlation between the vulnerability measures for individual simulations. We conclude that evaluating vulnerability in power networks using purely topological metrics can be misleading.

Modeling the impact of increasing PHEV loads on the distribution infrastructure.

Chris Farmer, Paul Hines, Jonathan Dowds, Seth Blumsack. Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010, , , 2010.[pdf] [journal page]

**Abstract:**

Numerous recent reports have assessed the adequacy of current generating capacity to meet the growing electricity demand from Plug-in Hybrid Electric Vehicles (PHEVs) and the potential for using these vehicles to provide grid support (Vehicle to Grid, V2G) services. However, little has been written on how these new loads will affect the medium and low-voltage distribution infrastructure. This paper briefly reviews the results of the existing PHEV studies and describes a new model: the PHEV distribution circuit impact model (PDCIM). PDCIM allows one to estimate the impact of an increasing number of PHEVs (or pure electric vehicles) on transformers and underground cables within a medium voltage distribution system. We describe the details of this model and results from its application to a distribution circuit in Vermont.

A review of results from plug-in hybrid electric vehicle impact studies.

Jonathan Dowds, Chris Farmer, Paul Hines, Seth Blumsack. Preprint, 2009.[pdf]

**Abstract:**

Plug-in Hybrid Electric Vehicles (PHEVs) estimate the costs and benefits associated with a transition to electric energy as a fuel for transportation. This paper reviews these results and describes the factors that result in variance among these studies. Specifically, we find that assumptions about PHEV charging and driving patterns, electric range and the greenhouse gas intensity of electrical generation are critical determinants of conclusions about PHEVs impacts on oil use, greenhouse gas emissions and the electrical grid.

Long-term electric system investments to support plug-in hybrid electric vehicles.

Seth Blumsack, Constantine Samaras, Paul Hines. Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE, 1-6, , 2008.[pdf] [journal page]

**Abstract:**

Plug-in Hybrid Electric Vehicles (PHEV) represent a promising pathway to reduce greenhouse gas emissions associated with the US transportation sector. A large-scale shift from gasoline-powered automobiles to PHEVs would inextricably link the US transportation system with its electric system. We build on [4] to perform a regional emissions analysis of a PHEV use pattern where PHEVs are charged at night and discharged during the day. We find that in some coal-intensive regions like the Midwest, charging PHEVs by burning coal may produce more emissions than burning gasoline. Overnight charging of PHEVs will deteriorate the system load factor by increasing off-peak demand. This may have deleterious effects on system infrastructure. We perform some simple simulations looking at the effect of off-peak PHEV charging on the performance of oilcooled substation transformers.

A centrality measure for electrical networks.

Paul Hines, Seth Blumsack. Hawaii International Conference on System Sciences, Proceedings of the 41st Annual, , , 2008.[pdf] [journal page]

**Abstract:**

We derive a measure of" electrical centrality" for AC power networks, which describes the structure of the network as a function of its electrical topology rather than its physical topology. We compare our centrality measure to conventional measures of network structure using the IEEE 300-bus network. We find that when measured electrically, power networks appear to have a scale-free network structure. Thus, unlike previous studies of the structure of power grids, we find that power networks have a number of highly-connected" hub" buses. This result, and the structure of power networks in general, is likely to have important implications for the reliability and security of power networks.

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