Grid reliability enhancement by peak load forecasting with a PSO hybridized ANN model

机译：通过PSO杂交的ANN模型通过峰值负荷预测提高网格可靠性

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Raised complexity levels of conventional grids, ever increasing load demands, elevated reliability issues, limitations of conventional power generating units and quality issues associated with sustainable energy resources all highlight the need to adapt specific demand management techniques to augment grid reliability. The stability of grids is hampered by varying loads, intermittent supply of the renewable resources and the inability of conventional plants to deal with them making the grids extremely vulnerable during peak load times. In this study we propose the utilization of a hybrid load forecasting tool based on Artificial Neural Network and Particle Swarm Optimization (PSO) as the solution. The tool would forecast futuristic load and would be specifically effective for the peak load times enabling utilities to optimize grid performance.

机译：提高了传统网格的复杂性水平，不断增加负载需求，高昂的可靠性问题，传统发电单元的限制以及与可持续能源相关的质量问题突出了适应特定需求管理技术以增加电网可靠性的必要性。通过不同的负荷，可再生资源的间歇性供应以及传统植物无法处理它们的稳定性，使网格的稳定性受到阻碍，使得网格在峰值负荷时间内极其脆弱。在这项研究中，我们提出了基于人工神经网络和粒子群优化（PSO）作为解决方案的混合负荷预测工具。该工具将预测未来派负载，并专门对峰值加载时间有效，使实用程序能够优化网格性能。

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《nternational Conference on Reliability, Infocom Technologies and Optimization》|2015年||共6页
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Takiyar Swati;
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中图分类计算技术、计算机技术;
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Artificial neural networks; Load forecasting; Load modeling; Power generation; Power system reliability; Power system stability; Reliability; Artificial Neural Network (ANN); Demand Response; Demand Side Management; Load Forecasting; Peak Load; Power Grid; Reliability; Varying Load Demand;

机译：人工神经网络;负载预测;发电;电力系统可靠性;电力系统稳定性;可靠性;人工神经网络（ANN）;需求响应;需求侧管理;负载预测;峰值负荷;可靠性;可靠性;可靠性;可靠性;可靠性;变化要求;

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专利

1. PSO Based Combinations of ANNs for Short Term-Daily Peak Load Forecasting [J] . P. Subbaraj, V. Rajasekaran Asian Journal of Information Technology . 2007,第2期

机译：基于PSO的ANN组合用于短期每日峰值负荷预测
2. A proposed intelligent short-term load forecasting hybrid models of ANN, WNN and KF based on clustering techniques for smart grid [J] . Aly Hamed H. H. Electric power systems research . 2020,第May期

机译：基于智能电网聚类技术的ANN，WNN和KF的建议智能短期负荷预测混合模型
3. Hybridization of seasonal chaotic cloud simulated annealing algorithm in a SVR-based load forecasting model [J] . Geng Jing, Huang Min-Liang, Li Ming-Wei, Neurocomputing . 2015,第mara3pta3期

机译：基于SVR的负荷预测模型中季节混沌云模拟退火算法的混合
4. Grid reliability enhancement by peak load forecasting with a PSO hybridized ANN model [C] . Takiyar Swati nternational Conference on Reliability, Infocom Technologies and Optimization . 2015

机译：通过PSO混合ANN模型进行峰值负荷预测来增强电网可靠性
5. Annual electrical peak load forecasting methods with measures of prediction error. [D] . Loredo, Elvira Nieves. 2001

机译：带有预测误差的年度电力峰值负荷预测方法。
6. A Comparison between Finite Element Model (FEM) Simulation and an Integrated Artificial Neural Network (ANN)-Particle Swarm Optimization (PSO) Approach to Forecast Performances of Micro Electro Discharge Machining (Micro-EDM) Drilling [O] . Mariangela Quarto, Gianluca D’Urso, Claudio Giardini, 2021

机译：有限元模型（FEM）模拟与综合人工神经网络（ANN） - 群综合优化（PSO）方法的比较预测微电路电气放电加工（微EDM）钻井的性能
7. Hybridizing DEMD and Quantum PSO with SVR in Electric Load Forecasting [O] . Li-Ling Peng, Guo-Feng Fan, Min-Liang Huang, 2016

机译：DEmD和量子psO与sVR在电力负荷预测中的应用

Grid reliability enhancement by peak load forecasting with a PSO hybridized ANN model

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