Research On Nonlinear Mathematical Models in Power Load Distribution and Their Engineering Applications
DOI:
https://doi.org/10.54097/7059m330Keywords:
Power load distribution, Nonlinear mathematical model, Engineering application, Power system planning, Power dispatching.Abstract
This paper focuses on the field of power load distribution, and devotes itself to the study of nonlinear mathematical model and its application in power engineering. By systematically analyzing the factors that affect the distribution of power load, such as user behavior, characteristics of electrical equipment, time and environment, a nonlinear mathematical model with strong pertinence is constructed. In the solution and verification, the model is trained by iterative method and the actual monitoring data. The results show that the model shows high accuracy in forecasting power load distribution, with an average absolute error (MAE) of 23.5kW and an average absolute percentage error (MAPE) of 3.15%. In the application of power engineering, this model helps to rationally arrange power supply and power grid in power system planning, realize the optimal utilization of energy in power dispatching, and ensure that the equipment adapts to the load demand when selecting power equipment. To sum up, the model is of great significance to improve the operation efficiency and reliability of power system.
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[1] Liu J, Yang H, Wei D, et al. Time Distribution Simulation of Household Power Load Based on Travel Chains and Monte Carlo–A Study of Beijing in Summer[J]. Sustainability, 2021, 13(12): 6651.
[2] Momen H, Abessi A, Jadid S. Using EVs as Distributed Energy Resources for Critical Load Restoration in Resilient Power Distribution Systems[J]. IET Generation, Transmission & Distribution, 2020, 14(18): 3750-3761.
[3] Tang Z, Hill D J, Liu T. Distributed Coordinated Reactive Power Control for Voltage Regulation in Distribution Networks[J]. IEEE Transactions on Smart Grid, 2020, 12(1): 312-323.
[4] Hu Wenjun, Zhou Xizhao. A Multi-mode Nonlinear Complementary Allocation Model under Supply and Demand Uncertainty[J]. Practice and Theory of Mathematics, 2020, 50(07): 243-251.
[5] Luo H, Liu J, Li X. A Neuron Fuzzy Identification System Based on a Complex Nonlinear Mathematical Model[J]. Wireless Networks, 2022, 28(5): 2299-2311.
[6] Simard J D, Astolfi A. Nonlinear Model Reduction in the Loewner Framework[J]. IEEE Transactions on Automatic Control, 2021, 66(12): 5711-5726.
[7] Mai V Q, Nhan T A, Hammouch Z. A Mathematical Model of Enzymatic Non-competitive Inhibition by Product and Its Applications[J]. Physica Scripta, 2021, 96(12): 124062.
[8] Xie W Y, Pan N X, Zeng H R, et al. Comparison of Nonlinear Models to Describe the Feather Growth and Development Curve in Yellow-feathered Chickens[J]. Animal, 2020, 14(5): 1005-1013.
[9] Li Yi, Wei Haichun, Sun Xinlei, et al. Mathematical Model of Chaotic Decoupling Control for Static Var Compensator in Distribution Networks with Nonlinear Loads[J]. Automation & Instrumentation, 2023, 38(8): 11-15.
[10] Liu Zengji, Wang Qi, Xue Tong, et al. Research on Security Threat Analysis and Countermeasures of Data-driven Algorithms in Power Systems[J]. Proceedings of the CSEE, 2023, 43(12): 4538-4553.
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