Self-adaptive differential evolution approach to solving economic load dispatch problem with renewable energy: Nigerian case study

Renewable energy penetration in power systems comes with many inherent challenges that pose a significant problem with coordination and scheduling with other conventional generation sources. These challenges if not mitigated instantly could affect the reliable operation of power systems and may even lead to a system collapse in severe cases. Therefore, the development of improved and faster economic dispatch is imperative to effectively and reliably integrate renewable energy into the power system. In this paper, four different methods namely: gradient descent, genetic algorithm, differential evolution, and self-adaptive differential evolution were utilized to coordinate the wind–thermal generation dispatch and to minimize the total production cost in the economic dispatch considering the generator ramp rate. The Nigerian grid was modeled consisting of four thermal units’ system incorporating wind power plants in each of the five different locations was utilized for the numerical simulations. Different simulation scenarios with and without losses were simulated and the results show that the self-adaptive method gives the least production cost as compared to other methods. Also, considering the case with losses, the self-adaptive differential evolution gives the least transmission losses as compared to others.