Peak Shaving Optimization Model for Wind-Photovoltaic-Hydro Joint Scheduling based on Artificial Fish Swarm Optimization
With the problem of wind and light loss,this paper proposes an artificial fish swarm algorithm based on multi-agent(MAAFAS),and constructs a short-term peak shaving optimization dispatching model of cascade water and scenery with the minimum residual load mean square error as the objective function.This model fully combines the autonomy of multi-agent algorithm and the global optimization of artificial fish swarm algorithm,reducing the complexity of constraints and making it easy to obtain the op-timal solution for complex problem solving.Taking the wind power and water power complementary sys-tem composed of 6 hydropower stations,11 wind farms and 4 photovoltaic power stations in a certain ba-sin in Southwest China as the research object,the case analysis is carried out under different water inflow scenarios(flood season and dry season).The results show that the model can effectively utilize the peak shaving capacity of hydropower energy,significantly increase the average reduction rate of load peak val-ley difference to 44.65%,reduce the original load peak valley difference of 3 300 MW,and stabilize the residual load,facilitating better consumption of wind and solar energy.It is an effective algorithm with strong practicability to solve the short-term joint optimization of peak shaving scheduling of wind-solar complementary power generation system.
wind-photovoltaic-hydro hybrid power systemshort-term optimal operationmulti-a-gent artificial fish swarm optimizationpeak shavingcascade hydropower plants
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