Abstract:Energy internet (EI) can alleviate the arduous challenges brought about by the energy crisis and global warming and has aroused the concern of many scholars. In the research of EI control systems, the access of distributed energy causes the power system to exhibit complex nonlinearity, high uncertainty and strong coupling. Traditional control and optimization methods often have limited effectiveness in solving these problems. With the widespread application of distributed control technology and the maturity of… Show more
“…Each individual in the population is coded and corresponds to a candidate solution in the feasible region of the optimization problem. As a consequence, the population is a solution set made up of several viable alternatives (Zhong et al, 2005;Bevrani et al, 2016;Hua et al, 2018;Javaid et al, 2018;Hua et al, 2021;Perera et al, 2021). The fitness feature is a yardstick for measuring the advantages and disadvantages of individuals in the evolutionary phase (Li and Wang, 2019;Luo et al, 2019;Elmouatamid et al, 2020;Hussain et al, 2020;Wang et al, 2020b;Zand et al, 2020).…”
The old economic and social growth model, characterized by centralized fossil energy consumption, is progressively shifting, and the third industrial revolution, represented by new energy and Internet technology, is gaining traction. Energy Internet, as a core technology of the third industrial revolution, aims to combine renewable energy and Internet technology to promote the large-scale use and sharing of distributed renewable energy as well as the integration of multiple complex network systems, such as electricity, transportation, and natural gas. This novel technology enables power networks to save energy. However, multienergy synchronization optimization poses a significant problem. As a solution, this study proposed an optimized approach based on the concept of layered control–collaborate optimization. The proposed method allows the distributed device to plan the heat, cold, gas, and electricity in the regional system in the most efficient way possible. Moreover, the proposed optimization model is simulated using a real-number genetic algorithm. It improved the optimal scheduling between different regions and the independence of distributed equipment with minimal cost. Furthermore, the inverse system and energy and cost saving rate of the proposed method are better than those of existing methods, which prove its effectiveness.
“…Each individual in the population is coded and corresponds to a candidate solution in the feasible region of the optimization problem. As a consequence, the population is a solution set made up of several viable alternatives (Zhong et al, 2005;Bevrani et al, 2016;Hua et al, 2018;Javaid et al, 2018;Hua et al, 2021;Perera et al, 2021). The fitness feature is a yardstick for measuring the advantages and disadvantages of individuals in the evolutionary phase (Li and Wang, 2019;Luo et al, 2019;Elmouatamid et al, 2020;Hussain et al, 2020;Wang et al, 2020b;Zand et al, 2020).…”
The old economic and social growth model, characterized by centralized fossil energy consumption, is progressively shifting, and the third industrial revolution, represented by new energy and Internet technology, is gaining traction. Energy Internet, as a core technology of the third industrial revolution, aims to combine renewable energy and Internet technology to promote the large-scale use and sharing of distributed renewable energy as well as the integration of multiple complex network systems, such as electricity, transportation, and natural gas. This novel technology enables power networks to save energy. However, multienergy synchronization optimization poses a significant problem. As a solution, this study proposed an optimized approach based on the concept of layered control–collaborate optimization. The proposed method allows the distributed device to plan the heat, cold, gas, and electricity in the regional system in the most efficient way possible. Moreover, the proposed optimization model is simulated using a real-number genetic algorithm. It improved the optimal scheduling between different regions and the independence of distributed equipment with minimal cost. Furthermore, the inverse system and energy and cost saving rate of the proposed method are better than those of existing methods, which prove its effectiveness.
“…Serrano et al address the problems of low electrical energy utilization and waste in library lighting systems by analyzing the data collected from seated readers and designing a zoning lighting system that meets the behavior habits of readers while saving resources and reducing waste [ 10 ]. The research results were successfully applied to the secondary planning and renovation of the commercial street by using behavior models and computer simulation methods and based on the virtual visitation data of the online Expo, they obtained the behavior data of the visitors and carried out the temporal and spatial simulation of the multi-individual visitation behavior through the model, achieving the prediction and guidance of the number of visitors, the flow of people and the demand for facilities at the Expo [ 11 ]. The average accuracy of a single unit segment of the layout model without the word embedding layer is calculated to be 89.75%, and the average accuracy of the entire sequence of units is 73.48%; the average accuracy of a single unit segment of the layout model with the word embedding layer added is 98.60%.…”
This paper analyses the design of a healthy interior environment using big data intelligence. The application of big data intelligence in the design of healthy interior environments is necessary because the traditional interior design approaches consume a lot of energy and other problems. Benefited by its strong ability of computation and analytics, artificial intelligence can well improve a series of problems in the field of interior design. The proposal summarizes the sources, classifications, and expressions of behavioral data in interior spaces, carries out analysis and research on behavioral data from two aspects: display space and supermarket space, summarizes the interior methods based on behavioral data, and analyses the visualization application of behavioral data in different interior scenes, to explore the application value of behavioral data in interior design. In contrast to it is the unconscious behavioral response, the biggest characteristic of which is that it is regulated by the behavioral subject’s physiological factors or habits of the behavior issuer. In this paper, we convert the layout recommendation problem of a space into a functional classification problem of segmented segments and household segments on a plane. The scene layout features are extracted by binary coding, the abstraction of the cross features between the vector segments is achieved by using a word embedding algorithm, the feature matrix is reduced in dimensionality, and finally, the segmentation network model and the layout network model are constructed, respectively, by using a bidirectional LSTM. The experiments show that the accuracy of the layout recommendation model in this paper is 98%, which can meet the demand for real-time online layouts.
“…Those techniques offer the advantage of being robust and efficient because they do not require exact knowledge of the mathematical model of the system. Moreover, those algorithms are characterized by good behavior in transitional regime [15].…”
In this paper, we deal with control performance and power qualityimprovement of Microgrid connected Photovoltaic System (PVS) withstorage. A comparative study was conducted between two versions of Fuzzy Logic Controllers: Type 1 (T1FLC) and Type 2 (T2FLC). DCside of the proposed microgrid system is composed of a photovoltaic systemand battery storage. Both are controlled by fuzzy logic algorithmsto extract maximum power from solar panels, and guarantee optimalmanagement of battery storage. AC side is composed of a two-level MultifunctionalVoltage Source Inverter (MVSI) associated with a ShuntActive Power Filter (SAPF) connected to the grid and supplies a nonlinearload. This side is controlled by a Direct Power Control strategyassociated with Space Vector-Modulation technique (DPC-SVM),and an Fuzzy Logic Controller (FLC) algorithm to inject the extractedactive power into the network and compensate the reactive power.The growing integration of Renewable Energy Sources (RES) poses several challenges to Microgrid systems. The T2FLC structureis proposed to better handle those challenges and enhance performance.Simulation of the proposed solution is validated under MATLAB/Simulink. The obtained simulation results show that T2FLC technique provides the best solution in terms of good tracking andoptimization performance, reactive power compensation, Total HarmonicDistortion (THD) elimination caused by non-linear loads,and robustness against irradiance and nonlinear load variations.
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