A multi-objective evolutionary approach for generator scheduling

• This research describes a two-phase approach for optimal generation scheduling.
• Hourly scheduling considers transmission loss, operation cost, emission allowance.
• 24-h schedules are performed using hourly schedules as inputs.
• All operation constraints of the power system are taken into account.
• This approach outperforms other evolutionary multi-objective optimization methods.

This paper presents a novel, two-phase approach for optimal generation scheduling, taking into account the environmental issue of emission allowance trading in addition to the economic issue of operation cost. In the first phase, hourly-optimal scheduling is done to simultaneously minimize operation cost, emission, and transmission loss, while satisfying constraints such as power balance, spinning reserve and power generation limits. In the second phase, the minimum up/down time and ramp up/down rate constraints are considered, and a set of 24-h optimal schedules is obtained using the outputs of the first phase. Simulation results indicate effectiveness of the proposed approach.