Optimal Generation Scheduling Considering Distributed Generator for Cost Minimization based on Adaptive Modified Firefly Algorithm

The increasing load and the decreasing availability of non-renewable energy sources have encouraged the development of renewable energy utilization. This condition increases the complexity of the power system. Distributed generator (DG) connection causes a significant change in power flow. On the other hand, the load on the power system is dynamic, so it is necessary to adjust the power generation. Proper scheduling of generating units to improve the reliability of the power system is crucial. Scheduling optimization is the key in power system operation planning and control to achieve optimal power system operation, with minimal cost and power loss. This paper presents the optimization of generating unit scheduling by applying the Adaptive Modified Firefly Algorithm (AMFA). The performance of AMFA in optimizing generator scheduling for minimal generation costs and power losses is tested by using a modified IEEE 30-bus system. The simulation results show that AMFA has a better performance than the firefly algorithm (FA), with a convergence speed of 4 times faster. Additionally of optimization by applying a distributed generator shows an improvement in the condition of the bus voltage in the system, lower costs, and power losses. In a system without DG which is loaded with 130% baseload, the optimization results indicate that 67% of the buses are under voltage, the generation cost is 1458.702 $\$/hour$ and the power loss is 23.345 MW. The integration of DG into the system is able to improve the system where only 3% of the buses are under voltage, the cost of generating 1143.111 $\$/hour$, and power loss 1333.521 MW.