Load distribution method for hydrothermal power system based on multi-target distribution estimation

Abstract

The invention provides a load distribution method for a power system based on multi-target distribution estimation, which mainly solves the problem of load distribution of the power system. The implementation steps are as follows: initializing a parent population; repairing infeasible individuals in the parent population; calculating the fitness value of the parent population; obtaining a first new population by local learning; obtaining a second new population by modeling and sampling; combining the two new populations to obtain a filial population; repairing infeasible individuals in the filial population; calculating the fitness value of the filial population; and combining the filial population with the parent population, obtaining a next iterated parent population by means of quick non-domination sequencing selection, and taking non-domination individuals in the next iterated parent population as a final load distribution scheme if reaching the maximum iterated times, otherwise, continuing iterating. The load distribution scheme obtained by the invention has the advantages that the amount of the discharge of pollution gas and the amount of the consumption of fuels of the power system are reduced, and more optional load distribution schemes are provided.

Description

technical field [0001] The invention belongs to the technical field of power dispatching, relates to load distribution of water and thermal power systems, and can be used for optimal allocation of existing resources in the power system. Background technique [0002] Load distribution of hydrothermal power system is an important branch of power system analysis. It means that the thermal power units and hydropower units participating in the operation of the power system have been pre-determined, and under the condition of satisfying the operating constraints of the power system, the power load is allocated to each Generator sets, so that the fuel consumption and pollutant gas emissions of the whole system can be minimized at the same time. Because it can minimize economic losses and environmental losses without increasing any engineering costs, it has attracted widespread attention from the industry. At present, the methods to solve this problem mainly include: simulated anne...

AI Technical Summary

Problems solved by technology

Although this method can obtain multiple solution values ​​through a single operation, it has incomparable advantages over traditional single-objective methods. However, since NSGA-II uses traditional cross-mutation operators to generate new solutions, this new solution generation method will Limit the search range of the algorithm, resulting in limited load distribution options after optimization, and large emissions of polluting gases and fuel consumption in the power system

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