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As full CSIT and data sharing are assumed in CI which indicates that the CU gathers the whole information, the optimal solution is exhaust search.
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Sensitivity information of the optimal solution to the control design problem is utilized to identify the most influential design parameters on static controllability performance, hence providing the guideline for improving the disturbance rejection properties of the flowsheet.
The second approach is based on an integer programming formulation with a huge number of variables, whose linear programming relaxation can be solved by column generation, typically requiring a considerable time, but obtaining extensive information about the optimal solution of the problem.
It seems counter-intuitive to allocate power in the outage region and indeed when full channel information is available, the optimal solution is to not allocate any power in the outage region.
In general, there is no information about the optimal solutions except the optimum problem parameters.
Recent economical researches suggest that the actual human decisions are based on very limited local information, hence the optimal solutions primarily exist in very confined spaces of limited dimensions.
PSO is a global optimization method, it does not need any prior information when it seeks the optimal solution in the solution space.
It is based on simulation of samples of the design variables from an auxiliary probability density function, and uses this information to identify subsets for the optimal solution.
Better reporting of paired data is, nonetheless, the optimal solution.
The FCS agents store the line parameters and the load information for their assigned FCS, so the optimal solution for a section may not be the optimal solution for the entire feeder.
Similar result is obtained in [5], which further considers the optimal solution with causal information.
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