In this paper, a new method, based on firefly algorithm （FA） and extreme learning machine （ELM）, is proposed to control chaos in nonlinear system. ELM is an efficient predicted and classified tool, and can match a...In this paper, a new method, based on firefly algorithm （FA） and extreme learning machine （ELM）, is proposed to control chaos in nonlinear system. ELM is an efficient predicted and classified tool, and can match and fit nonlinear systems efficiently. Hence, mathematical model of uncertain nonlinear system is obtained indirectly. For higher fitting accuracy, a novel swarm intelligence algorithm FA is drawn in our proposed way. The main advantage is that our proposed method can remove the limitation that mathematical model must be known clearly and can be applied to unknown nonlinear chaotic system.展开更多
Residential flexible resource is attracting much attention in demand response(DR)for peak load shifting.This paper proposes a scenario for multi-stage DR project to schedule energy consumption of residential communiti...Residential flexible resource is attracting much attention in demand response(DR)for peak load shifting.This paper proposes a scenario for multi-stage DR project to schedule energy consumption of residential communities considering the incomplete information.Communities in the scenario can decide whether to participate in DR in each stage,but the decision is the private information that is unknown to other communities.To optimize the energy consumption,a Bayesian game approach is formulated,in which the probability characteristic of the decision-making of residential communities is described with Markov chain considering human behavior of bounded rationality.Simulation results show that the proposed approach can benefit all residential communities and power grid,but the optimization effect is slightly inferior to that in complete information game approach.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.51577046)the State Key Program of the National Natural Science Foundation of China(Grant No.51637004)the National Key Research and Development Plan"Important Scientific Instruments and Equipment Development"(Grant No.2016YFF0102200)
文摘In this paper, a new method, based on firefly algorithm （FA） and extreme learning machine （ELM）, is proposed to control chaos in nonlinear system. ELM is an efficient predicted and classified tool, and can match and fit nonlinear systems efficiently. Hence, mathematical model of uncertain nonlinear system is obtained indirectly. For higher fitting accuracy, a novel swarm intelligence algorithm FA is drawn in our proposed way. The main advantage is that our proposed method can remove the limitation that mathematical model must be known clearly and can be applied to unknown nonlinear chaotic system.
基金the Natural Science Research Project of Jiangsu Higher Education Institutions(No.20KJB470024).
文摘Residential flexible resource is attracting much attention in demand response(DR)for peak load shifting.This paper proposes a scenario for multi-stage DR project to schedule energy consumption of residential communities considering the incomplete information.Communities in the scenario can decide whether to participate in DR in each stage,but the decision is the private information that is unknown to other communities.To optimize the energy consumption,a Bayesian game approach is formulated,in which the probability characteristic of the decision-making of residential communities is described with Markov chain considering human behavior of bounded rationality.Simulation results show that the proposed approach can benefit all residential communities and power grid,but the optimization effect is slightly inferior to that in complete information game approach.
