Cautious Operation Planning Under Uncertainties

Abstract

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

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

“…We finally notice that other works of the authors [4], [8] utilize the AC nonlinear model as some system operator operational rules (e.g., conditional corrective actions) are relaxed. Consequently, the control variables used were either continuous (e.g., generator active power) or allowed continuous relaxation (e.g., generator start-up as strategic preventive action), enabling thereby the use of a sequence of MILP and NLP solvers.…”

“…Its algorithm relies on the identification in a combinatorial fashion of the worst-case by looking at the sets of constraints violated by worst uncertainty patterns. Furthermore, [8] focuses on the computation of strategic actions in order to cover the worst-cases that cannot be satisfied by best preventive/corrective controls.…”

“…Consequently, the control variables used were either continuous (e.g., generator active power) or allowed continuous relaxation (e.g., generator start-up as strategic preventive action), enabling thereby the use of a sequence of MILP and NLP solvers. Even under these assumptions, the approaches of [4] and [8] are very computationally intensive on our very large scale model.…”

“…To cover the current worst-case scenario of contingency while taking into account SO operating rules we solve the following SCOPF problem which minimizes the amount of preventive actions: (8) where the preventive actions include generation re-dispatch, generator start-up, and load shedding, and are bounds on preventive actions, the corrective actions include phase shifter angle change and generator start-up, and are bounds on corrective actions, is a vector of weights of preventive control to distinguish between generator re-dispatch or start-up and load shedding in order to ensure that load shedding takes place only if the post-contingency constraints are not met by other types of preventive/corrective actions, binary variables model the generators start-up and load shedding. Matrix links the post-contingency angles to pre-contingency angles , is the sensitivity matrix of post-contingency angles to corrective actions, and are flow limits that must be satisfied by preventive actions only.…”

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

“…[3]- [11], but only few have considered the application of corrective control actions or the existence of power flow control devices such as PSTs or HVDC. In [12], [13], a threestage optimal power flow (OPF) framework where corrective control actions are used to ensure feasibility during worst-case combinations of contingencies and uncertainty was proposed, and was extended to the definition of optimal corrective control actions in [14]. The OPF formulation in [15] accounts for uncertainty and includes corrective control for a limited number of pre-selected, critical uncertainty scenarios.…”