Abstract: Aimed at the power balance planning of power systems with power supply shortage, we develop a multi-objective optimization model for the supplementary power stations – hydropower or thermal power – to achieve its lowest present total cost in operation period and smallest installed capacity. To solve this model, a constrained method, limiting the capacity between its smallest and largest values, is used to transform the multi-objective problem into single-objective optimization for power system economic planning. We adopt an improved progressive optimality algorithm to solve the model, so that dimension disaster can be effectively alleviated to obtain uniformly distributed Pareto solution set. Then, the ideal point method is used to single out the optimal solution. Application to the Yunnan power grid shows the proposed model can consider different types of supplementary power stations and their installed capacities and the power system economic planning, thus helping supplementary power station planning.

Key words: power balance, supplementary power station planning, multi-objective, power system economic planning, improved progressive optimality algorithm