Hydrothermal Scheduling With Demand Response Based On Improved Flower Pollination Algorithm

In order to enhance the searching ability of flower pollination algorithm(FPA),this paper proposes some strategies to improve the optimization ability of FPA,and applies the improved algorithm to the hydrothermal scheduling.At the same time,the optimal scheduling model of hydrothermal power based on demand response is also studied,and two hydrothermal scheduling models with the largest profit of the power supply company and the largest profit of consumers are proposed.Finally,the improved flower pollination algorithms are applied to the hydrothermal scheduling.The main work can be summarized as follows:Firstly,a double-direction learning flower pollination algorithm(DLFPA)is proposed,which adds three improved strategies to the standard flower pollination algorithm.The double-direction learning strategy strengthens the local search ability of the algorithm,improves the accuracy of solutions,the greedy strategy increases the diversity of the population and the global search ability,and the dynamic switching probability strategy balances the relationship between the global and local search.Then 12 test functions are used to test the algorithm and the results are compared with DE?BA?CS?ABC?FPA?EOFPA and MGOFPA.Secondly,a demand response model with the maximum profit of the power supply company is constructed,so that consumers can participate in the deployment of electric energy.And the proposed demand response model is combined with the hydrothermal scheduling model.That is,the power supply company can reduce the electricity consumption within a reasonable range by giving consumers some compensation incentive,which can reduce the power generation of the power plant to a certain extent,the cost of coal consumption,and the pollution to the environment.Lastly,an example is given to illustrate the validity and feasibility of the model.Futuremore,the multi-population mechanism is introduced into the flower pollination algorithm,and a multi-population flower pollination algorithm(MPFPA)is proposed.The pollen population is divided into three sub-populations according to the degree of superiority and inferiority,and each sub-population is optimized according to different ways,so as to improve the optimization ability of the algorithm.Then two structural engineering problems,the compression spring design problem and the pressure vessel design problem,are used to verify the proposed algorithm.Meanwhile,a demand response model with the maximum profit of consumers is proposed,and combined with hydrothermal scheduling model,and then the model is solved by MPFPA.