Efficient harmony search algorithm for multi-stages scheduling problem for power systems degradation

Usually power energy demand increases randomly with time. To enhance system performance, expansion-planning to adapt the power system capacity to the demand is predicted. This paper uses a harmony search meta-heuristic optimization method to solve the multi-stage expansion problem for multi-state series-parallel power systems. The study horizon is divided into several periods. At each period the demand distribution is forecasted in the form of a cumulative demand curve. A multiple-choice of additional components from a list of available products can be chosen and included into any subsystem component at any stage to improve the system performance. The components are characterized by their cost, performance (capacity), and availability. The objective is to minimize each investment over its study period while satisfying availability or performance constraints. A universal generating function technique is applied to evaluate power system availability. The harmony search approach is required to identify the optimal combination of adding components with different parameters to be allocated in parallel at each stage.