Dynamic Multi-area Generation Scheduling with Renewable Energy Sources Exploiting Optimistic Sine–Cosine Algorithm

The intent of this paper is to propose an optimistic sine–cosine algorithm (OSCA) that has more chances to target optimal schedules than its classical version. A successful attempt is made to solve dynamic multi-area hybrid generation dispatch models to meet hourly load, combining power generation from large-wind farms and solar power using photovoltaic systems with thermal power generating units. The dynamic multi-area power scheduling problem is undertaken, whereby the mixed-energy sharing problem meets the energy demand of every area by maintaining energy transfer through tie-lines for a time horizon. Thermal unit operating constraints, ramp-rate limits, and prohibited operating zones, along with valve point loading affecting the thermal unit cost characteristic equation, are incorporated in the model. Solar and wind units’ share is not allowed to exceed the certain limits of demand to meet their uncertainty, and then the commitment of units is done using a very optimistic method. The problem is decomposed into solar and wind units’ shares having quick starts and thermal units having slow starts. Economic and environmental objectives of thermal units are unified using a price penalty factor so that OSCA can be applied. A sample electric power system consisting of solar, wind, and thermal generators in multi-area connected through tie lines has been undertaken to validate the proposed method. The variation in objectives is shown for 30 trial runs with a box plot, which has no outliers. One forward approach takes 75,030 function evaluations, and the total function evaluations are 1,800,720 to achieve the solution for all the intervals. The results are validated through statistical analysis.