Intelligent Modeling of the Incineration Process in Waste Incineration Power Plant Based on Deep Learning

Abstract

The incineration process in waste-to-energy plants is characterized by high levels of inertia, large delays, strong coupling, and nonlinearity, which makes accurate modeling difficult. Therefore, an intelligent modeling method for the incineration process in waste-to-energy plants based on deep learning is proposed. First, the output variables were selected from the three aspects of safety, stability and economy. The initial variables related to the output variables were determined by mechanism analysis and the input variables were finally determined by removing invalid and redundant variables through the Lasso algorithm. Secondly, each delay time was calculated, and a multi-input and multi-output model was established on the basis of deep learning. Finally, the deep learning model was compared and verified with traditional models, including LSSVM, CNN, and LSTM. The simulation results show that the intelligent model of the incineration process in the waste-to-energy plant based on deep learning is more accurate and effective than the traditional LSSVM, CNN and LSTM models.

Artificial intelligence for waste management in smart cities: a review

“…Waste recycling involves collecting, treating, and reusing human-generated waste (Erkinay Ozdemir et al 2021 ). Waste incineration uses high-temperature and high-pressure pyrolysis oxidation to reduce the volume of waste and eliminate hazardous materials (Chen et al 2022a ). Waste composting involves the controlled decomposition of organic matter in waste and its conversion into substrates and fertilizers (Aydın Temel et al 2023 ; Wei et al 2022 ).…”

“…The complexity of waste incineration modeling arises from its nonlinear nature, strong coupling, significant delays, and high inertia. To overcome these difficulties, Chen et al ( 2022a ) developed an intelligent modeling approach based on deep learning models, which proved more accurate and effective in simulating waste incineration power plants. Wajda and Jaworski ( 2021 ) used an ant optimization algorithm after conducting laboratory experiments and practical tests, achieving satisfactory results.…”

Application of Artificial Intelligence in Power System Monitoring and Fault Diagnosis

“…This section provides a summary of this Special Issue of Energies, covering published articles [1][2][3][4][5][6][7][8][9][10] which address several topics related to AI technologies in power system performance monitoring.…”

“…In [9], Chen et al proposed a deep-learning-based method for the intelligent modeling of the incineration process in waste-to-energy plants. The output variables are selected regarding safety, stability, and economy.…”

Waste Management Framework Using Brainy Litter Basket

“…The researchers devised a waste management system in real-time that employed intelligent waste receptacles with the ability to detect the degree of waste build-up. The system facilitates remote access and comprehensive review of data pertaining to smart trash cans, thereby empowering individuals to make informed decisions based on the available information [13]. The implementation of the suggested approach resulted in advantages such as decreased costs, optimised allocation of resources, and improved utilisation of intelligent waste bins.…”