This paper addresses the main challenges to the security constrained optimal power flow (SCOPF) computations. We first discuss the issues related to the SCOPF problem formulation such as the use of a limited number of corrective actions in the post-contingency states and the modeling of voltage and transient stability constraints. Then we deal with the challenges to the techniques for solving the SCOPF, focusing mainly on: approaches to reduce the size of the problem by either efficiently identifying the binding contingencies and including only these contingencies in the SCOPF or by using approximate models for the post-contingency states, and the handling of discrete variables. We finally address the current trend of extending the SCOPF formulation to take into account the increasing levels of uncertainty in the operation planning. For each such topic we provide a review of the state of the art, we identify the advances that are needed, and we indicate ways to bridge the gap between the current state of the art and these needs. * Corresponding author Email addresses: capitane@montefiore.ulg.ac.be (F. Capitanescu), camel@us.es (J.L. Martinez Ramos), patrick.panciatici@rte-france.com (P. Panciatici), kirschen@uw.edu (D. Kirschen), alejandromm@us.es (A. Marano Marcolini), ludovic.platbrood@gdfsuez.com (L. Platbrood), l.wehenkel@ulg.ac.be (L. Wehenkel) Preprint submitted to Electric Power Systems ResearchMay 2, 2011Keywords: mixed integer linear programming, mixed integer nonlinear programming, nonlinear programming, optimal power flow, security constrained optimal power flow MotivationThe SCOPF [1,2] is an extension of the OPF problem [3,4] which takes into account constraints arising from the operation of the system under a set of postulated contingencies. The SCOPF problem is a nonlinear, nonconvex, large-scale optimization problem, with both continuous and discrete variables [1,2]. The SCOPF belongs therefore to the class of optimization problems called Mixed Integer Non-Linear Programming (MINLP).The SCOPF has become an essential tool for many Transmission System Operators (TSOs) for the planning, operational planning, and real time operation of their system [5,6, 7,8]. Furthermore, in several electricity markets (e.g. PJM, New-England, California, etc.) the locational marginal prices calculated using a DC SCOPF are used to price electricity. This approach is also under consideration in other systems [9,10,11].Several papers discussing the challenges to the OPF problem were published during the 90's [5,6, 7,8]. Since then several important changes have taken place not only in power systems operation and control but also in mathematical programming:• Power systems operate today in conditions that are more "stressed" and were not foreseen at the planning stage. In particular the increase in load has not been supported by an adequate upgrade of the generation and transmission systems. Furthermore the creation of electricity markets has led to the trading of significant amounts of electrical energy over lo...

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This paper focuses on improving the solution techniques for the AC SCOPF problem of active power dispatch by using the DC SCOPF approximation within the SCOPF algorithm. Our approach brings two benefits compared to benchmark SCOPF algorithms: it speeds-up the solution of an iterative AC SCOPF algorithm thanks to a more efficient identification of binding contingencies, and allows improving the objective by an appropriate choice of a limited number of corrective actions for each contingency. The proposed approach is illustrated on 5 test systems of 60, 118, 300, 1203, and 2746 buses.

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This paper assesses the behaviour of active distribution networks with high penetration of renewable energy sources when the control is performed in a centralised manner. The control assets are the on-load tap changers of transformers at the primary substation, the reactive power injections of the renewable energy sources, and the active and reactive power exchanged between adjacent feeders when they are interconnected through a DC link. A scaled-down distribution network is used as the testbed to emulate the behaviour of an active distribution system with massive penetration of renewable energy resources. The laboratory testbed involves hardware devices, real-time control, and communication infrastructure. Several key performance indices are adopted to assess the effects of the different control actions on the system’s operation. The experimental results demonstrate that the combination of control actions enables the optimal integration of a massive penetration of renewable energy.