This paper makes use of advances in mixed integer linear programming (MILP) to conduct a preliminary design study on the combinatorial optimal placement of thyristor controlled phase shifter transformers (TCPSTs) in large-scale power systems. The procedure finds the number, network location, and settings of phase shifters that maximize system loadability under the DC load flow model, subject to limits on the installation investment or total number of TCPSTs. It also accounts for active flow and generation limits, and phase shifter constraints. Simulation results are presented for the IEEE 24-, 118-, and 300-bus systems, as well as a 904-bus network. The principal characteristics of our approach are compared with those of other published flexible AC system transmission (FACTS) allocation methods
This paper presents a methodology to improve the power system economical dispatch from a voltage stability margin perspective. The time horizon under discussion is the short-term operation planning. The proposed method is based on active/reactive power re-dispatch for normal operation, and also minimum load shedding strategies in case of critical contingencies. The actions are taken in the direction provided by modal participation factors computed for generator and load buses. The generators with negative impact on system margin, which are indicated by the modal index, are penalized with high costs on the objective function of the optimal power flow program used to run the re-dispatch process. Results of this work show a decrease on system losses and significant increase on voltage stability margin as well as on system reactive reserves. In addition, this work presents a study considering critical contingencies, for which is proposed an optimal load shedding strategy also based on modal participation factors to identify the most adequate buses for load shedding purposes. Finally, the proposed methodology is applied considering a typical hour-to-hour daily load curve, and the method presented very good performance since it considerably increases voltage stability margin for the insecure intervals.
This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.
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