A new multiple objectives optimization model of monthly generation scheduling

The efficient generation scheduling is an important task to maintain the economy and security of modern power systems. A new monthly generation scheduling model based on multiple objectives optimization is proposed to provide a feasible initial schedule for daily scheduling so that generation resources can be optimized. The proposed model is aiming at the evenness of dispatching monthly energy in spatio-temporal viewpoint. In such a condition, monthly generation schedule can provide continue operation state for each unit, and enough reserve capacity for real-time schedule to prevent accidents. Thus it can link up monthly schedule and daily schedule smoothly so as to ensure the power system against unsteady operation. The proposed multiple objectives optimization model for monthly generation scheduling proposed has four sub objectives as follows:(1) Leveling the daily loss of load probability (LOLP) in a certain month; (2) Minimizing the up/down times for all units;(3) Leveling the daily energy for each unit; (4) Leveling the daily exchange energy for each sub region. The monthly generation scheduling model will determine the optimal operation strategy for the specified month, including monthly unit commitment and daily energy of all units. The constraints of the optimization model include transmission capacity of power grid, unit generating capacity and unit maintenance schedule, and so on. The monthly generation scheduling model is decomposed into two main decision stages: monthly unit commitment problem (MUCP) and energy dispatch problem (EDP). The MUCP is a nonlinear optimization problem with high dimensionality, continuous and discrete variables, multi-objective function, as well as lots of equality and inequality constraints. In the genetic algorithm (GA) implementation, a new technique to represent candidate solutions is introduced, and a set of expert operators has been incorporated to improve the behavior of the algorithm. The proposed model has been put int- - o application in Shandong province. Reasonable result has been gained which is presented and discussed in this paper.