03090nas a2200313 4500008003900000022001300039245012300052210006900175260001200244300001400256490000700270520212400277653001002401653002402411653002802435653001302463100002402476700002002500700001202520700002302532700001402555700002502569700001702594700001402611700002502625700002502650700002502675856007602700 2014 d a0928765500aDoes a detailed model of the electricity grid matter? Estimating the impacts of the Regional Greenhouse Gas Initiative0 aDoes a detailed model of the electricity grid matter Estimating c01/2014 a191 - 2070 v363 aThe consequences of environmental and energy policies in the U.S. can be severely constrained by physical limits of the electric power grid. Flows do not follow the shortest path but are distributed over all lines in accordance with the laws of physics, so grid operators must select which generation units to operate at each moment, not only to minimize production costs, but also to prevent the system from collapsing because of line overloads. Because of the complexity of power grid operation, computing limitations have until very recently made it impossible to solve a policy analysis or planning model that combines realistic modeling of flows with a detailed transmission system model and the prediction of generator investment and retirement. We construct and solve a model of the eastern US and Canada that combines these characteristics. Then, because a smaller model would be usable for some additional purposes, we explore the effects of transmission model simplification on the accuracy of simulation results. To evaluate the amount of detail necessary, we simulate the short- and long-term effects of imposing a price on the carbon dioxide emissions from the power plants in nine northeastern US states, as the Regional Greenhouse Gas Initiative does. We consider three grid models that simplify the actual 62,000-node system to varying degrees. Our 5000-node model matches the 62,000-node model very closely. We use it as the basis for evaluating the more simplified models: a 300-node model and a model with just one node, i.e. no transmission constraints. With each of the three models, we predict the carbon dioxide emission impacts, electricity price impacts, and generator entry and exit impacts of the emission price, over the next 20 years. We find that most of the impact predictions produced by the 300- and one-node models differ from those of the 5000-node model by more than 20%, and some by much more. Fortunately, the 5000-node model, and others with its combination of transmission detail, realistic flows, entry prediction, and retirement prediction can be used for many useful purposes.10aCERTS10aelectricity markets10areliability and markets10aRM11-0051 aShawhan, Daniel, L.1 aTaber, John, T.1 aShi, Di1 aZimmerman, Ray, D.1 aYan, Jubo1 aMarquet, Charles, M.1 aQi, Yingying1 aMao, Biao1 aSchuler, Richard, E.1 aSchulze, William, D.1 aTylavsky, Daniel, J. uhttps://certs.lbl.gov/publications/does-detailed-model-electricity-grid01423nas a2200181 4500008003900000245005500039210005500094260003600149300001000185520086500195653001001060653002601070653001301096100001301109700002501122700001701147856007701164 2014 d00aImproved dc network model for contingency analysis0 aImproved dc network model for contingency analysis aPullman, WA, USAbIEEEc09/2014 a1 - 63 aContingency analysis is employed by system operators to estimate post-disturbance power system robustness. For large system like WECC or the Eastern Interconnection (EI) the computational burden and time consumed for full blown ac analysis is tremendous. Also, a recent upsurge in the area of electric energy markets and transmission/generation planning has created a niche for computationally efficient and yet reliable, simple and robust power flow models. This has intensified the inclination of researchers to come up with equivalent dc networks that match ac solutions as close as possible. This paper introduces a novel method of deriving dc model using PTDF approach. The performance of this model is then compared to the several other dc models for single branch outage contingencies. Furthermore, shortcomings of several dc models shall be analyzed.
10aCERTS10aPower system modeling10aRM11-0051 aSood, P.1 aTylavsky, Daniel, J.1 aQi, Yingying uhttps://certs.lbl.gov/publications/improved-dc-network-model-contingency01351nas a2200193 4500008003900000020002200039245005800061210005800119260003800177300001000215520075700225653001000982653002600992653001301018100001701031700001201048700002501060856007201085 2012 d a978-1-4673-2306-200aImpact of assumptions on DC power flow model accuracy0 aImpact of assumptions on DC power flow model accuracy aChampaign, IL, USAbIEEEc09/2012 a1 - 63 aThe industry seems to be sanguine about the performance of dc power-flow models, but recent research has shown that the performance of different formulations is highly variable. Considering their pervasive use, the accuracy of dc power-flow models is of great concern. In this paper, three dc power-flow formulations are examined: the classical dc power-flow model, dc power-flow model with loss compensation and the so-called a-matching dc power-flow model. These three models are tested in three systems of different sizes, ranging from 10 buses to 62,000 buses. By comparing the dc power-flow results with the ac power-flow results, the paper concludes that the a-matching formulation has the highest accuracy among three dc power flow formulations.10aCERTS10aPower system modeling10aRM11-0051 aQi, Yingying1 aShi, Di1 aTylavsky, Daniel, J. uhttps://certs.lbl.gov/publications/impact-assumptions-dc-power-flow