Partition Optimization of Hydroelectricity Power System and Appropriate Option of Renewable Energy Source in Terms of Probabilistic Multi-Objective Optimization

The partition optimization and option of renewable energy source for specific place are basic problems which include multiple objectives, such as cost, benefit, and adjustable performance, etc. Particularly, partition optimization is a specific optimal design under the constraint condition of the summation of the proportion of each component being 100%, i.e., a “mixture design” problem in principle. In this paper, the combination of probabilistic multi-objective optimization (PMOO) with uniform design for mixture (UDM) is employed to solve the problems of partition optimization and the option of renewable energy source for specific place. In the study, PMOO is used to converse the multi-objective optimization problem (MOO) into a mono-objective one, and UDM with discretization treatment is used to provide a greatly simplified assessment with a set of homogeneous sampling points in the optimization design with the constraint condition of the summation of total partition ratios being 100% specifically. In the optimization of partition ratios of a hydroelectricity power system, the total estimated expenditure is minimized, and the annual average power generation of three hydropower stations is maximized in the system. It gives the rounding-off optimum partitions of the three hydropower stations as 66 kW, 55 kW and 109 kW under the condition of a total installed capacity of 230 kW, respectively; the total cost and annual power generation are 4.3251 billion yuan and 127.7356 billion degrees correspondingly. Subsequently, the study on the selection of renewable energy source in specific place in India results in solar energy as the appropriate option.