Security management under uncertainty: From day-ahead planning to intraday operation

Abstract

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 ...

Contingency Ranking With Respect to Overloads in Very Large Power Systems Taking Into Account Uncertainty, Preventive, and Corrective Actions

“…To tackle this problem [1] sets up a broader framework as a three-stage decision making process, including slow strategic preventive controls (e.g., starting up a power plant, postponing maintenance works), fast preventive controls (e.g., generation rescheduling) and corrective (or emergency) controls (e.g., generation rescheduling, network switching, phase shifter actions, etc.). The computation of worst-case scenarios is an essential task of this approach.…”

“…Reference [1] formulates the worst case with respect to a contingency as a bi-level (min-max) optimization problem which, assuming a DC load flow approximation and hence focusing on thermal overload only, can be transformed into a mixed integer linear programming (MILP) problem for which suitable solvers are available. [4] proposes an approximate heuristic solution of the bi-level worst-case problem in its nonlinear form (i.e., using the AC network model).…”

“…In this paper, which builds upon our previous work in [1], we focus on the contingency ranking with respect to overloads in 0885-8950/$31.00 © 2013 IEEE very large systems, taking into account uncertainty and preventive/corrective actions. The main contributions of this paper are summarized as follows:…”

Corrective control to handle forecast uncertainty: A chance constrained optimal power flow

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Structured power system model reduction of non-coherent areas

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