Probabilistic assessment of Net Transfer Capacity considering forecast uncertainties

In transmission system planning, researchers propose methods to assess the effect of uncertainties of power system operating condition due to forecasting errors of intermittent generation and loads. In particular probabilistic power flow methods are used to calculate the probability distributions of the voltages and the branch currents, starting from the distributions of power injections/absorptions. These uncertainties play a key role in the operational planning of power systems, as certain configurations of load and intermittent generation can cause security problems. This paper aims to propose a probabilistic methodology to assess Net Transfer Capacity (NTC) among network areas, which quantifies forecast error uncertainties by applying the Point Estimate Method (PEM) combined with Third Order Polynomial Normal (TPN) Transformation. This approach is compared with a conventional NTC assessment technique and has been tested on an IEEE test system

Online security assessment with load and renewable generation uncertainty: The iTesla project approach

The secure integration of renewable generation into modern power systems requires an appropriate assessment of the security of the system in real-time. The uncertainty associated with renewable power makes it impossible to tackle this problem via a brute-force approach, i.e. it is not possible to run detailed online static or dynamic simulations for all possible security problems and realizations of load and renewable power. Intelligent approaches for online security assessment with forecast uncertainty modeling are being sought to better handle contingency events. This paper reports the platform developed within the iTesla project for online static and dynamic security assessment. This innovative and open-source computational platform is composed of several modules such as detailed static and dynamic simulation, machine learning, forecast uncertainty representation and optimization tools to not only filter contingencies but also to provide the best control actions to avoid possible unsecure situations. Based on High Performance Computing (HPC), the iTesla platform was tested in the French network for a specific security problem: overload of transmission circuits. The results obtained show that forecast uncertainty representation is of the utmost importance, since from apparently secure forecast network states, it is possible to obtain unsecure situations that need to be tackled in advance by the system operator

An Integrated Platform for Power System Security Assessment Implementing Probabilistic and Deterministic Methodologies

Power system security assessment for planning (offline) and for operational (online) applications requires various analysis methods aimed to highlight different phenomena (steadystate violations, angle stability, voltage stability, etc.), overall providing an exhaustive vision of the problems. However, carrying out the different analyses in an integrated way is not an easy task. Accordingly, combining the results in a consistent framework is an issue. Moreover, risk-based methods have been recently proposed to complement traditional deterministic approaches. They are expected to investigate security more in depth by introducing the concepts of probability and impact associated to the contingencies. Probabilistic approaches are, however, more complex to manage. This paper proposes the overall architecture of a security assessment platform, integrating probabilistic and deterministic tools in a unified environment

An integrated platform for power system security assessment implementing probabilistic and deterministic methodologies

Power system security assessment for planning (offline) and for operational (online) applications requires various analysis methods aimed to highlight different phenomena (steadystate violations, angle stability, voltage stability, etc.), overall providing an exhaustive vision of the problems. However, carrying out the different analyses in an integrated way is not an easy task. Accordingly, combining the results in a consistent framework is an issue. Moreover, risk-based methods have been recently proposed to complement traditional deterministic approaches. They are expected to investigate security more in depth by introducing the concepts of probability and impact associated to the contingencies. Probabilistic approaches are, however, more complex to manage. This paper proposes the overall architecture of a security assessment platform, integrating probabilistic and deterministic tools in a unified environment

An integrated platform for power system security assessment implementing probabilistic and deterministic methodologies

Power system security assessment both for planning (off-line) studies and for operational (on-line) applications is performed by various analysis methods which highlight different phenomena (steady-state violations, angle stability, voltage stability, etc.) in order to retrieve an exhaustive vision of the problems. Besides traditional deterministic tools, recently proposed probabilistic tools may highlight new interesting security aspects by introducing the concepts of probability and quantifying the risk associated with the contingencies. This paper proposes the overall architecture of a security assessment platform which integrates both probabilistic and deterministic methodologies in a simple environment