A probabilistic approach to power system security assessment under uncertainty

Le, Duong; Berizzi, Alberto; Bovo, Cristian; Ciapessoni, Emanuele; Cirio, D.; Pitto, A.; Gross, George

doi:10.1109/irep.2013.6629411

Cited by 15 publications

(19 citation statements)

References 15 publications

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“…About the sources uncertainty, the following holds: for loads, their uncertainty distributions are assumed to be stationary and normally distributed, with expected values equal to their base case data and standard deviations equal to 9% of the expected values; random outages of 170 lines are also considered with the probability of failure equal to 0.1%. Distributed slack bus formulation [28] is exploited so as to possibly include the steady-state behavior of the frequency regulation of conventional generation in the calculation.…”

Section: Application To Security Assessmentmentioning

confidence: 99%

“…This is a very attractive feature of the proposed method to deal with high-dimensional data. From pdfs of currents as well as voltages, we can evaluate probability of line overloading and probability of over-/under-voltage [28]; however, in this test, there is no violation of voltages and flows.…”

Section: Application To Security Assessmentmentioning

confidence: 99%

“…It is worth noticing that MCS-based probabilistic power flow (PPF) [28] using samples obtained by sampling nontemporal probability distributions of input random variables at different time-steps (e.g., wind power distributions provided by a probabilistic forecast technique [29]) can provide output (voltages, currents, and power flows) in terms of probability distributions at each time-step, which may be sufficient for assessing probability of violation for these quantities.…”

Section: Application To Security Assessmentmentioning

confidence: 99%

“…Conventional generators connected to 18 buses are distributed slack, so that any mismatch, and/or any uncertainty, in the system is shared by the relevant generators with corresponding participation factors. Conventional generator at bus 468 (g 468 ), for instance, is assigned in real power allocation process with the participation factor 0.15 [28], resulting in its power output p h,ξ g468 at time h for wind output scenario ξ (ξ = 1, 2, . .…”

Section: Application To Security Assessmentmentioning

confidence: 99%

See 3 more Smart Citations

Probabilistic Modeling of Multisite Wind Farm Production for Scenario-Based Applications

Gross

Berizzi

2015

IEEE Trans. Sustain. Energy

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The deepening penetration of wind resources introduces major challenges into power system planning and operation activities. This is due to the need to appropriately represent salient features of wind power generation from multiple wind farm sites such as nonstationarity with distinct diurnal and seasonal patterns, spatial and temporal correlations, and non-Gaussianity. Hence, an appropriate model of multisite wind power production in systems with integrated wind resources represents a major challenge to meet a critical need. In this paper, we aim at defining a new methodology to improve the quality of generated scenarios by means of historical multisite wind data and effective deployment of time series and principal component (PC) techniques. Scenariobased methodologies are already available in power systems, but sometimes lack in accuracy: this paper proposes a methodology that is able to capture the main features of wind: it can both characterize spatio-temporal properties and be used to reduce size of data sets in practical applications without using any simplifying assumption. Extensive testing indicates good performance in effectively capturing the salient wind characteristics to provide useful models for various problems related to multisite wind production, including security assessment, operational planning, environmental analysis, and system planning. An application to security assessment is presented. His research interests include probabilistic approaches applied to power systems, integration of renewable energy resources into power grids, power system security assessment, power system planning, operations, and analysis.George Gross (F'86-LF'11) received the Undergraduate degree in electrical engineering from

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Section: Application To Security Assessmentmentioning

confidence: 99%

Section: Application To Security Assessmentmentioning

confidence: 99%

Section: Application To Security Assessmentmentioning

confidence: 99%

Section: Application To Security Assessmentmentioning

confidence: 99%

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Probabilistic Modeling of Multisite Wind Farm Production for Scenario-Based Applications

Gross

Berizzi

2015

IEEE Trans. Sustain. Energy

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“…Several methodologies for security assessment have been developed over decades, each solving a specific part of the overall problem and there are different indicators in use to describe security [2]. Considerable effort has been devoted to the power system risk assessment using the probabilistic techniques [3], [4]. More recent, efforts to introduce online dynamic and static security assessment has been well documented in literature [5], [6].…”

Section: Introduction the Draft Network Code On High Voltage Direcmentioning

confidence: 99%

Risk-based DC security assessment for future DC-independent system operator

González-Longatt

Carmona-Delgado

Santos

et al. 2015

2015 International Conference on Energy Economics and Environment (ICEEE)

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Abstract-The use of multi-terminal HVDC to integrate wind power coming from the North Sea opens de door for a new transmission system model, the DC-Independent System Operator (DC-ISO). DC-ISO will face highly stressed and varying conditions that requires new risk assessment tools to ensure security of supply. This paper proposes a novel risk-based static security assessment methodology named risk-based DC security assessment (RB-DCSA). It combines a probabilistic approach to include uncertainties and a fuzzy inference system to quantify the systemic and individual component risk associated with operational scenarios considering uncertainties. The proposed methodology is illustrated using a multi-terminal HVDC system where the variability of wind speed at the offshore wind is included.

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Approximate Probabilistic Power Flow

Zuluaga

Álvarez

2017

Data Analytics for Renewable Energy Integration

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A probabilistic approach to power system security assessment under uncertainty

Cited by 15 publications

References 15 publications

Probabilistic Modeling of Multisite Wind Farm Production for Scenario-Based Applications

Probabilistic Modeling of Multisite Wind Farm Production for Scenario-Based Applications

Risk-based DC security assessment for future DC-independent system operator

Approximate Probabilistic Power Flow

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