Orthogonal PSO algorithm for optimal dispatch of power of large-scale thermal generating units in smart power grid under power grid constraints

We propose a novel approach called, an orthogonal particle swarm optimization (OPSO) algorithm, for economic dispatch (ED) of thermal generating units (TGUs) in smart electric power gird (SEPG) environment. The characteristics of TGUs are nonlinear and the generation system becomes more and more complicated when these TGUs are subjected to ramp rate constraints and prohibited operating zones. In such case, the cost functions become non-smooth and non-convex due to the discontinuities in the cost curves. Moreover, for large-scale TGUs, the high dimensions used in ED problem become a big challenge to find global minimum and to avoid falling into local minima. The proposed OPSO algorithm has the ability to solve such complex problems including ED. The OPSO algorithm applies an orthogonal diagonalization process. It makes d particles (out of total m particles, m ≥ d) that have the possible solutions by constructing orthogonal vectors in the d-dimensional search space. These orthogonal vectors are generated and updated in each iteration and are utilized to guide the d particles to fly in one direction toward global minimum. The OPSO algorithm is evaluated and tested through 40 TGUs and its performance is compared with several other optimization methods. We found that the OPSO algorithm provides better results in term of cost under power grid constraints. Furthermore, we have shown that the OPSO algorithm significantly improves the PSO algorithm in terms of high solution quality, robustness and convergence.