Understanding Electric Power Systems

Casazza, Jack; Delea, Frank

doi:10.1002/0471667854

Cited by 56 publications

(24 citation statements)

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“…Notice that phase angle θ 0 for bus 0 is assumed known as a reference angle, and the size of Z n is normally greater than that of x. [19], [23] One objective of (4) is to determine thex which can minimize…”

Section: Problem Formulationmentioning

confidence: 99%

Real-Time Detection of False Data Injection in Smart Grid Networks: An Adaptive CUSUM Method and Analysis

Huang

Tang

Cheng

et al. 2016

IEEE Systems Journal

152

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Abstract-Smart grid is delay-sensitive and requires the techniques that can identify and react on the abnormal changes (i.e. system fault, attacker, shortcut, etc.) in a timely manner. In this paper, we propose a real-time detection scheme against false data injection attack in smart grid networks. Unlike the classical detection test, the proposed algorithm is able to tackle the unknown parameters with low complexity and process multiple measurements at once, leading to a shorter decision time and better detection accuracy. The objective is to detect of adversary as quickly as possible while satisfy certain detection error constraints. A Markov chain based analytical model is constructed to systematically analyze the proposed scheme. With the analytical model, we are able to configure the system parameters for guaranteed performance in terms of false alarm rate, average detection delay, and missed detection ratio under a detection delay constraint. The Simulations are conducted with MATPOWER 4.0 package for different IEEE test systems.

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Section: Problem Formulationmentioning

confidence: 99%

Real-Time Detection of False Data Injection in Smart Grid Networks: An Adaptive CUSUM Method and Analysis

Huang

Tang

Cheng

et al. 2016

IEEE Systems Journal

152

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“…In particular, P T DF rb is defined as the quantity of power flow (MW) through the critical link of interface b induced by a 1 MW injection at node r [9,10,30].…”

Section: The Model Of the Integrated Electric Power Supply Chain Netwmentioning

confidence: 99%

“…Smeers [77] reviewed a wide range of models of energy markets with various market power assumptions (see also, [1,9,10,30,56,70,76,84,85]). Hogan [36] proposed a market power model to study strategic interactions in an electricity transmission network.…”

Section: Introductionmentioning

confidence: 99%

An integrated electric power supply chain and fuel market network framework: Theoretical modeling with empirical analysis for New England

Liu

Nagurney

2009

Naval Research Logistics

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In this paper, we develop a novel electric power supply chain network model with fuel supply markets that captures both the economic network transactions in energy supply markets and the physical network transmission constraints in the electric power network. The theoretical derivation and analysis are done using the theory of variational inequalities.We then apply the model to a specific case, the New England electric power supply chain, consisting of 6 states, 5 fuel types, 82 power generators, with a total of 573 generating units, and 10 demand market regions. The empirical case study demonstrates that the regional electric power prices simulated by the proposed model very well match the actual electricity prices in New England. We also compute the electric power prices and the spark spread, an important measure of the power plant profitability, under natural gas and oil price variations. The empirical examples illustrate that in New England, the market/gridlevel fuel competition has become the major factor that affects the influence of the oil price on the natural gas price. Finally, we utilize the model to quantitatively investigate how changes in the demand for electricity influence the electric power and the fuel markets from a regional perspective. The theoretical model can be applied to other regions and multiple electricity markets under deregulation to quantify the interactions in electric power/energy supply chains and their effects on flows and prices.

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“…A suitable model, however, must also be able to accommodate changing economic behavior due to the deregulation of the electric power industry, from the historic norm of highly regulated, vertically integrated utilities to a new environment of competition between the major players, such as power generators, suppliers, transmission service providers, and consumers. For additional background on the electric power industry (see Casazza and Delea, 2003;Singh, 1999;Zaccour, 1998).…”

Section: Introductionmentioning

confidence: 99%

Modeling generator power plant portfolios and pollution taxes in electric power supply chain networks: A transportation network equilibrium transformation

Nagurney

Liu

et al. 2006

Transportation Research Part D: Transport and Environment

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Global climate change and fuel security risks have encouraged international and regional adoption of pollution/carbon taxes. A major portion of such policy interventions is directed at the electric power industry with taxes applied according to the type of fuel used by the power generators in their power plants. This paper proposes an electric power supply chain network model that captures the behavior of power generators faced with a portfolio of power plant options and subject to pollution taxes. We demonstrate that this general model can be reformulated as a transportation network equilibrium model with elastic demands and qualitatively analyzed and solved as such. The connections between these two different modeling schemas is done through finite-dimensional variational inequality theory. The numerical examples illustrate how changes in the pollution/carbon taxes affect the equilibrium electric power supply chain network production outputs, the transactions between the various decision-makers the demand market prices, as well as the total amount of carbon emissions generated.

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Understanding Electric Power Systems

Cited by 56 publications

References 0 publications

Real-Time Detection of False Data Injection in Smart Grid Networks: An Adaptive CUSUM Method and Analysis

Real-Time Detection of False Data Injection in Smart Grid Networks: An Adaptive CUSUM Method and Analysis

An integrated electric power supply chain and fuel market network framework: Theoretical modeling with empirical analysis for New England

Modeling generator power plant portfolios and pollution taxes in electric power supply chain networks: A transportation network equilibrium transformation

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