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Economic Power Dispatch of Independent Power Producer Using Gray Wolf Optimization
K. Kathiravan and Dr. N. Rathina Prabha
Economic Power Dispatch (EPD) is a useful tool for optimal operation and planning of a modern power system. Optimal generation is made to cost effective. Conventional methods have the assumption on fuel cost characteristics of a generating unit which is a continuous and convex function that results fairly satisfied. This proposed work is to design and apply efficient Gray Wolf Optimization (GWO) technique for the solution of optimal generation. Here the non-convex characteristics of the generator along with the ramping limits of the practical generator operation are considered for the computation. By using optimal generation of the conventional method is carried out for 26 bus system with six generating units having ramp rate limits are taken for computation in Matlab environment. The performance of the GWO algorithm is estimated by multi-line contingency and combined bilateral and multilateral wheeling transactions conditions. The results are compared with Autonomous Group of Particle Swarm Optimization (AGPSO) and found GWO method performs better in solving Economic power dispatch problem.
Keywords: Power Flow, Ramp Rate limits, Autonomous Group of Particle Swarm Optimization, Gray Wolf Optimization, Piecewise Linear Ramp Rate
The power industries have the conventional EPD problem involves a location of different thermal generating units to minimize the operating cost subjected to equality and inequality constraints. The EPD problem is a large scale highly non-linear constrained optimization problem such as linear programming, quadratic programming, non-linear programming, interior point and Newton-based method. All these methods are made in an assumption that the generation of fuel cost characteristics of a power producer is a smooth and convex function. For example, this situation originates when ramp rate limit and valve-point loading are present in these condition to represent the unit’s operating fuel cost characteristics are as convex. So far, the accurate global optimum of the problem could not be reached simply. A novel method is needed to survive with these technique complication and those with high pace search to the optimal and not being fascinated in local minima. In order to optimize the operational cost of power system subjected to the system operating constraints such non- linear problem had explored by Computational Artificial Intelligence (CAI) by many researchers to get optimal solution.
K. Kathiravan (Corresponding Author)