Nonlinear active noise control (NANC) systems employing Volterra filter suffer from the stability issues in the presence of impulsive noise. To solve this problem, we combine the second-order Volterra (SOV) filter and maximum correntropy criterion (MCC) in this paper. The Volterra filter-x maximum correntropy criterion (VFxMCC) algorithm and Volterra filter-x recursive maximum correntropy (VFxRMC) algorithm are applied to reduce the impulsive noise of NANC. We find that VFxMCC algorithm has a low computational complexity and VFxRMC algorithm converges fast. In order to extract their advantages, we further propose a hybrid algorithm based on the VFxMCC and VFxRMC algorithms. In addition, the normalize step-size version of VFxMCC (VFxnMCC) algorithm is developed to improve the robustness and performance. Meanwhile, we adaptively adjust the kernel size of MCC online based on the sample variance of reference signal to improve the performance of the proposed algorithms. Simulation results in the context of nonlinear active impulsive noise control demonstrate that the proposed algorithms achieve much better performance than the existing algorithms in various noise environments.

With the gradual liberalization of the energy market, the future integrated energy system will be composed of multiple agents. Therefore, this paper proposes an optimization dispatch method considering energy hub technology and multi-agent interest balance in an integrated energy system. Firstly, an integrated energy system, including equipment for cogeneration, renewable energy, and electric vehicles, is established. Secondly, energy hub technologies, such as demand response, electricity storage, and thermal storage, are comprehensively considered, and the integrated energy system is divided into three agents: Integrated energy service providers, renewable energy owners, and users, respectively. Then, with the goal of balancing the interests of each agent, the model is solved by the non-dominated sorting genetic algorithm-III (NSGA-III) to obtain the Pareto frontier. Since the Pareto frontier is a series of values, the optimal solution of each agent in the Pareto frontier is found by the technical for order preference with a similar to ideal solution (TOPSIS). Ultimately, taking an integrated energy demonstration park in China as a case study, the function of energy hub technology is analyzed by simulation, and the proposed method is verified to be effective and practicable.Energies 2019, 12, 3112 2 of 17 energy system. The proposed model and algorithm analyze the action of each unit in economic dispatch and wind-power accommodation effectively, verifying its efficiency and applicability; in [7], the two-stage optimization algorithm was used to optimize the park-level integrated energy system. The upper layer is aimed at the minimum total annual cost, annual pollution emission, and annual energy consumption, and the lower layer is aimed at the lowest operation and maintenance cost, which can effectively increase the overall benefit of the system. The authors of [8] established an integrated energy model for multi-energy complementary and coordinated development, proposed a distribution network planning strategy based on integrated energy system optimization, and looked to the future of integrated energy systems across regions.The ETH Zurich Institute first proposed the concept of an energy hub (EH) in the "Future Energy Network Vision" project in 2007 [9]. An energy hub is defined as an input-output port model that describes the exchange and coupling relationships between energy, load, and networks in a multi-energy system. The coupling matrix plays an important role in the planning and operation of multi-energy systems as it can briefly represent the various coupling relationships, such as transformation, storage, and transmission between electric, heat, and cooling [10,11]. As demand response technology plays an important role in promoting operational efficiency of the power system, the optimization dispatch model of integrated energy considering demand response technology is a continuous improvement [12,13]. Based the decentralized load-side demand response structure, some scholars proposed integrated demand ...

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