Value of Security: Modeling Time-Dependent Phenomena and Weather Conditions

Ríos, Mario Alberto Gaviria; Kirschen,; Jayaweera,; Nedic,; Allan,

doi:10.1109/mper.2002.4312377

Cited by 39 publications

(57 citation statements)

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“…al. [26] propose a probabilistic cost/benefit analysis and calculate the expected blackout cost, which they equate with the value of grid security, using Monte Carlo simulations of a power system model that represents the effects of cascading line overloads, hidden failures of the protection system, and power system dynamic instabilities. In this approach the authors replace the complex time-dependent modeling of transient instability with a sophisticated probabilistic modeling using off-line computation of conditional probabilities based on the fault type and its location with respect to the vulnerability region of each generator.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Model for Power Grid Dynamics

Anghel

Werley

Motter³

2007

2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07)

126

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Abstract-We introduce a stochastic model that describes the quasi-static dynamics of an electric transmission network under perturbations introduced by random load fluctuations, random removing of system components from service, random repair times for the failed components, and random response times to implement optimal system corrections for removing line overloads in a damaged or stressed transmission network. We use a linear approximation to the network flow equations and apply linear programming techniques that optimize the dispatching of generators and loads in order to eliminate the network overloads associated with a damaged system. We also provide a simple model for the operator's response to various contingency events that is not always optimal due to either failure of the state estimation system or due to the incorrect subjective assessment of the severity associated with these events. This further allows us to use a game theoretic framework for casting the optimization of the operator's response into the choice of the optimal strategy which minimizes the operating cost. We use a simple strategy space which is the degree of tolerance to line overloads and which is an automatic control (optimization) parameter that can be adjusted to trade off automatic load shed without propagating cascades versus reduced load shed and an increased risk of propagating cascades. The tolerance parameter is chosen to describes a smooth transition from a risk averse to a risk taken strategy. We present numerical results comparing the responses of two power grid systems to optimization approaches with different factors of risk and select the best blackout controlling parameter.

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Section: Introductionmentioning

confidence: 99%

Stochastic Model for Power Grid Dynamics

Anghel

Werley

Motter³

2007

2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07)

126

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“…IEEE and CIGRE have developed task forces working on risk analysis and probabilistic techniques for planning and operation [155,156]. Recently, various domains in risk-based planning have been studied, like power transfer limit [157], weather conditions [158], stability [159], and reserve generation [160]. Preece and Milanovic [159] combined probabilistic and fuzzy inference systems to categorise different degrees of risk, which facilitates the understanding of the planner.…”

Section: System Operationmentioning

confidence: 99%

Time‐horizons in the planning and operation of transmission networks: an overview

Khuntia

Tuinema

Rueda

et al. 2016

IET Generation, Transmission & Distribution

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In the planning and operation of power systems, actions are taken in different processes and time-horizons. The purpose of these actions is to secure a high reliability level. Although the three main processes (grid development, asset management, and system operation) are described in literature, there has been no explicit study on the time-horizons (long-term, mid-term, and short-term) and actual time-scale (decades, years, months, etc.) that these processes focus on. This study aims at making a review of the various activities performed by transmission system operators while reviewing the concept of each time-horizon and methodologies developed in literature. As decisions taken in different time-horizons can influence each other, the interactions and overlapping are discussed.

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“…Due to the level of uncertainties exists in an active distribution network, a probabilistic approach is necessary to capture the rational characteristics of large wind farms that can impact the steady-state security. The approach proposed in this paper incorporates non-sequential Monte Carlo simulation to capture uncertainties of operating conditions of an active distribution network [27].…”

Section: The Approachmentioning

confidence: 99%

“…Occurrences of random outages can change the network configuration which leads to re-assess the power balance using A/C power flow solution. Loads are shedded if the operating condition leads to the divergence of the power flow solution [27,33].…”

Section: Monte Carlo Simulationmentioning

confidence: 99%

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Steady-state security in distribution networks with large wind farms

Jayaweera

Islam

2014

J. Mod. Power Syst. Clean Energy

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Aging network assets, forced and unforced outages, and the way the networks are operated in a deregulated market are of significant concerns to integrate large wind farms in a distribution network. In many cases, the constrained network capacity is a potential barrier to the large-scale integration of wind power. This paper probabilistically assesses the steady-state security in a distribution network in the presence of large wind farms. The approach incorporates active distribution network operating conditions, including intermittent power outputs, random outages, demand fluctuations, and dynamic interactions and exchanges, and then assesses the steady state security using Monte Carlo simulation. A case study is performed by integrating large wind farms into a distribution network. The results suggest that intermittent outputs of large wind farms in a distribution network can impact the steady-state security considerably. However, the level of impact of wind farms does not necessarily correlate with the installed capacity of them.

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Value of Security: Modeling Time-Dependent Phenomena and Weather Conditions

Cited by 39 publications

References 0 publications

Stochastic Model for Power Grid Dynamics

Stochastic Model for Power Grid Dynamics

Time‐horizons in the planning and operation of transmission networks: an overview

Steady-state security in distribution networks with large wind farms

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