A COMPUTER PACKAGE FOR OPTIMAL MULTIOBJECTIVE VAR PLANNING IN LARGE-SCALE POWER-SYSTEMS

This paper presents a simulated annealing based computer package for multi-objective, VAR planning in large scale power systems - SAMVAR. This computer package has three distinct features. First, the optimal VAR planning is reformulated as a constrained, multi-objective, non-differentiable optimization problem. The new formulation considers four different objective functions related to system investment, system operational efficiency, system security and system service quality. The new formulation also takes into consideration load, operation and contingency constraints. Second, it allows both the objective functions and equality and inequality constraints to be non-differentiable; making the problem formulation more realistic. Third, the package employs a two-stage solution algorithm based on an extended simulated annealing technique and the epsilon-constraint method. The first-stage of the solution algorithm uses an extended simulated annealing technique to find a global, non-inferior solution. The results obtained from the first-stage provide a basis for planners to prioritize the objective functions such that a primary objective function is chosen and trade-off tolerances for the other objective functions are set. The primary objective function and the trade-off tolerances are then used to transform the constrained multi-objective optimization problem into a single-objective optimization problem with more constraints by employing the epsilon-constraint method. The second-stage uses the simulated annealing technique to find the global optimal solution. A salient feature of SAMVAR is that it allows planners to find an acceptable, global non-inferior solution for the VAR problem. Simulation results indicate that SAMVAR has the ability to handle the multi-objective VAR planning problem and meet with the planner's requirements.