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基于AP相似日选取与FISOA-RBF的短期负荷预测
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作者 于军琪 王佳丽 +3 位作者 赵安军 解云飞 冉彤 赵泽华 《深圳大学学报(理工版)》 EI CAS CSCD 北大核心 2021年第3期315-323,共9页
为提高建筑电力负荷的预测精度,在考虑天气信息和日期类型等影响因素的基础上,提出基于吸引子传播(affinity propagation,AP)相似日选取和改进搜索者优化算法-径向基(fusion improvement seeker optimization algorithm-radial basis fu... 为提高建筑电力负荷的预测精度,在考虑天气信息和日期类型等影响因素的基础上,提出基于吸引子传播(affinity propagation,AP)相似日选取和改进搜索者优化算法-径向基(fusion improvement seeker optimization algorithm-radial basis function,FISOA-RBF)神经网络的建筑用电短期负荷预测模型.采用AP算法对短期电力负荷进行相似日选取,以克服外界环境对建筑电力负荷预测精度的影响;以RBF神经网络的网络参数为优化对象,采用搜索者优化算法(seeker optimization algorithm,SOA)进行参数寻优,并引入融合改进策略提高传统人群算法的寻优性能,以进一步提高RBF神经网络的预测精度和学习速度;根据FISOA算法优化后的RBF神经网络对相似日数据进行训练,建立最优参数下的建筑短期电力负荷预测AP-FISOA-RBF模型.在相同数据集和气候特征条件下,与传统RBF、PSO-RBF和SOA-RBF预测模型相比,AP-FISOA-RBF模型平均预测绝对百分比误差分别降低了93.05%、83.60%和71.13%,平均预测速度分别提高了54.34%、39.25%和23.96%,表明AP-FISOA-RBF模型在预测精度和预测速度上的表现更好. 展开更多
关键词 计算机神经网络 吸引子传播 相似日选取 搜索者优化算法 径向基 建筑用电 短期负荷预测
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Sensitivity to electricity consumption in urban business and commercial area buildings according to climatic change
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作者 LEE Kang-guk KIM Sung-bum HONG Won-hwa 《Journal of Central South University》 SCIE EI CAS 2012年第3期770-776,共7页
Recently, urban high temperature phenomenon has become a problem which results from human activities, the increase in energy consumption, and land-cover change in urban areas. As extremely hot weather caused by urban ... Recently, urban high temperature phenomenon has become a problem which results from human activities, the increase in energy consumption, and land-cover change in urban areas. As extremely hot weather caused by urban high temperature continues, demand for power is increased and results in the degradation of electricity reserves. The current trend in climate change, regardless of the summer and winter power demand, is likely to have much effect on the power demand. Thus, sensitivity to electricity consumption in urban areas due to climate change was researched. The results show that, 1) the basic unit of the sensitivity to electricity consumption in the target areas is 1.25-1.58W/(m2.℃); 2) The maximum sensitivity is recorded at around 8:00 pm in the area crowded with commercial and business area. And in the business area, electricity consumption load is even from 9:00 am to 6:00 pm. 展开更多
关键词 electricity consumption electricity load electricity reserves energy
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