Optimal Long-term Reactive Power Planning Using Decomposition Techniques

Abstract

This paper is to solve an optimal long-term reactive power planning problem. The long-term planning problem is decomposed into three levels using three decomposition techniques. First, the multiyear planning problem is decomposed into yearly Hamiltonian minimization problems using Pontryagin's maximum principle. Then, the yearly Hamiltonian minimization problem is decomposed into investment and operation problems using Benders' decomposition method. Finally, the operation problem is decomposed into real (P) and reactive (Q) power optimization problems using the P-Q decomposition technique. This results in three optimization modules, investment, real power and reactive power, each with far fewer variables to optimize than in the original problem. Another feature of this paper is the linear programming (LP) formulation for all three optimization modules. The LP formulation makes the transfer of variables between modules efficient, speeds up computation, and allows the use of one standard LP package for all modules