Abstract-This paper deals with day-ahead security management with respect to a postulated set of contingencies, while taking into account uncertainties about the next day generation/load scenario. In order to help the system operator in decision making under uncertainty, we aim at ranking these contingencies into four clusters according to the type of control actions needed to cover the worst uncertainty pattern of each contingency with respect to branch overload. To this end we use a fixed point algorithm that loops over two main modules: a discrete bi-level program (BLV) that computes the worst-case scenario, and a special kind of security constrained optimal power flow (SCOPF) which computes optimal preventive/corrective actions to cover the worst-case. We rely on a DC grid model, as the large number of binary variables, the large size of the problem, and the stringent computational requirements preclude the use of existing mixed integer nonlinear programming (MINLP) solvers. Consequently we solve the SCOPF using a mixed integer linear programming (MILP) solver while the BLV is decomposed into a series of MILPs. We provide numerical results with our approach on a very large European system model with 9241 buses and 5126 contingencies. Index Terms-Bi-level programming, mixed integer linear programming, operation under uncertainty, optimal power flow, security-constrained optimal power flow, worst-case analysis.

In this paper, we publish nine new test cases in MATPOWER format. Four test cases are French very high-voltage grid generated by the offline plateform of iTesla: part of the data was sampled. Four test cases are RTE snapshots of the full French very high-voltage and high-voltage grid that come from French SCADAs via the Convergence software. The ninth and largest test case is a pan-European ficticious data set that stems from the PEGASE project. It complements the four PEGASE test cases that we previously published in MATPOWER version 5.1 in March 2015. We also provide a MATLAB code to transform the data into standard mathematical optimization format. Computational results confirming the validity of the data are presented in this paper.

Abstract-In this paper, we propose to analyse the pratical task of dealing with uncertainty for security management by Transmission System Operators in the context of day-ahead planning and intraday operation. We propose a general but very abstract formalization of this task in the form of a threestage decision making problem under uncertainties in the minmax framework, where the three stages of decision making correspond respectively to operation planning, preventive control in operation, and post-contingency emergency control. We then consider algorithmic solutions for addressing this problem in the practical context of large scale power systems by proposing a bilevel linear programming formulation adapted to the case where security is constrained by power flow limits. This formulation is illustrated on two case studies corresponding respectively to a synthetic 7-bus system and the IEEE 30-bus system.Index Terms-operation planning, intraday operation, security management under uncertainties, transmission system operator, worst case analysis, mathematical programming I. OUTLINE D AY-AHEAD operational planning as well as intraday operation of power systems is affected by an increasing amount of uncertainty due to the coupling of wind power intermittency, cross-border interchanges, market clearing, and load evolution. In this context, a deterministic approach that consists of forecasting a single best-guess of the system injections for the next day or hours, and of ensuring system security along this trajectory only, becomes inappropriate. The Transmission System Operator (TSO) will rather determine his strategic decisions by considering a set of scenarios reflecting his uncertainty and by making sure that under the worst of these scenarios the system security is still controllable.In this paper, we analyze the practical problem of security management in operation planning and intraday operation of large scale systems, and then formalize it in an abstract and generic way as a multi-stage decision making problem under uncertainties. We also propose and illustrate some practically feasible algorithms to address this problem for large scale systems. These algorithms are targeted towards solving a set of manageable subproblems of practical interest. In the practical context of operation planning and operation of power systems, decision making is carried out in an iterative fashion at different timeframes from day-ahead to minutesahead. The objective is to ensure system security at the lowest possible cost; the strategy to reach this objective is based on the evaluation of possible future scenarios so as to identify the most difficult ones and to determine strategic "ahead of time" decisions enabling operators to cope with these difficult scenarios during the next periods of time. In this context, a reasonable and in practice commonly adopted strategy consists in (i) searching in advance for the potentially most difficult operating scenarios, and (ii) postponing the commitment of the most costly actions at the latest ...

Abstract-This paper deals with day-ahead power systems security planning under uncertainties, by posing an optimization problem over a set of power injection scenarios that could show up the next day and modeling the next day's real-time control strategies aiming at ensuring security with respect to contingencies by a combination of preventive and corrective controls. We seek to determine whether and which day-ahead decisions must be taken so that for scenarios over the next day there still exists an acceptable combination of preventive and corrective controls ensuring system security for any postulated contingency. We formulate this task as a three-stage feasibility checking problem, where the first stage corresponds to day-ahead decisions, the second stage to preventive control actions, and the third stage to corrective post-contingency controls. We propose a solution approach based on the problem decomposition into successive optimal power flow (OPF) and security-constrained optimal power flow (SCOPF) problems of a special type. Our approach is illustrated on the Nordic32 system and on a 1203-bus model of a real-life system. Index Terms-power systems security, operation planning under uncertainty, worst-case analysis, security-constrained optimal power flow, nonlinear programming

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