74 research outputs found
Improving the statement of the corrective security-constrained optimal power flow problem
peer reviewedThis letter proposes a formulation of the corrective security-constrained optimal power-flow problem imposing, in addition to the classical post-contingency constraints, existence and viability constraints on the short-term equilibrium reached just after contingency. The rationale for doing so is discussed and supported by two examples
Sensitivity-based approaches for handling discrete variables in optimal power flow computations
peer reviewedThis paper proposes and compares three iterative approaches for handling discrete variables in optimal power flow (OPF) computations. The first two approaches rely on the sensitivities of the objective and inequality constraints with respect to discrete variables. They set the discrete variables values either by solving a mixed-integer linear programming (MILP) problem or by using a simple procedure based on a merit function. The third approach relies on the use of Lagrange multipliers corresponding to the discrete variables bound constraints at the OPF solution. The classical round-off technique and a progressive round-off approach have been also used as a basis of comparison. We provide extensive numerical results with these approaches on four test systems with up to 1203 buses, and for two OPF problems: loss minimization and generation cost minimization, respectively. These results show that the sensitivity-based approach combined with the merit function clearly outperforms the other approaches in terms of: objective function quality, reliability, and computational times. Furthermore, the objective value obtained with this approach has been very close to that provided by the continuous relaxation OPF. This approach constitutes therefore a viable alternative to other methods dealing with discrete variables in an OPF
A new heuristic approach to deal with discrete variables in optimal power flow computations
peer reviewedThis paper proposes a new heuristic approach to deal with discrete
variables in an optimal power flow (OPF). This approach relies on
the first order sensitivity of the objective and inequality
constraints with respect to the discrete variables. The impact of a
discrete variable change on the objective and inequality constraints
is aggregated into a merit function. The proposed approach searches
iteratively for better discrete variable settings as long as the
problem solution can be improved. We provide numerical results with
the proposed approach on four test systems up to 1203 buses and for
the OPF problem of active power loss minimization
Optimal power flow computations with a limited number of controls allowed to move
This letter focuses on optimal power flow (OPF) computations in which
no more than a pre-specified number of controls are allowed to move.
To determine an efficient subset of controls satisfying this constraint
we rely on the solution of a mixed integer linear programming (MILP)
problem fed with
sensitivity information of controls' impact on the objective and
constraints. We illustrate this approach on a 60-bus system and for
the OPF problem of minimum load curtailment cost to remove thermal
congestion
Contingency ranking with respect to overloads in very large power systems taking into account uncertainty, preventive, and corrective actions
peer reviewedThis 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
A New Bi-Objective Approach for Optimal Sizing of Electrical and Thermal Devices in Zero Energy Buildings Considering Environmental Impacts
An advanced tool for Preventive Voltage Security Assessment
peer reviewedThis paper deals with methods for the preventive assessment of voltage security with respect
to contingencies. We describe a computing tool for the determination of secure operation limits, together with methods for contingency filtering. Examples from two very different real-life systems are provided. We outline extensions in the field of preventive control
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