Development and prospects of converged communications supporting customer-side interactive services in new-type power system

doi:10.3969/j.issn.2097-0706.2025.11.007

Abstract

Abstract:

With the rapid development of new-type power system， customer-side interactive services are flourishing. By deeply integrating communication technology to enhance the efficiency of information interaction， the intelligence level of the customer-side interactive services in the new-type power system can be improved. However， by analyzing the customer-side interactive service requirements of the new-type power system and the current information and communication technologies， it is found that many challenges remain， including the complexity of technology integration and data security. To solve the above problems， perspectives on the development of customer-side converged communication technology are proposed from the aspects of cloud-side collaboration technology， distributed intelligence， end-to-end QoS capacity assurance， data-oriented service， and security protection system， thereby supporting the comprehensive optimization of system performance to ensure data security and reliability， further enhance the development of customer-side converged communication， and support the diversified development of customer-side interactive services.

Key words: customer-side interactive service, converged communication technology, end-to-end QoS, capacity assurance, data orientation service, security protection system, new-type power system

CLC Number:

TK01：TM73

LI Bin, ZHANG Wenyan, WANG Qingyu, REN Jie, KANG Yi. Development and prospects of converged communications supporting customer-side interactive services in new-type power system[J]. Integrated Intelligent Energy, 2025, 47(11): 72-86.

Figures/Tables 8

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评估维度	分析方法	国内相关技术	国外相关技术
性能指标提取	响应延迟、资源利用率、SLA合规性	Pod扩容响应时间<30 s^[40]	边缘节点利用率达75%^[44];预扩容成功率92%^[45]
纵向演化	技术迭代分析	弹性规则引擎支持实时动态分片策略^[41];强化学习（Reinforcement Learning，RL）+阈值混合策略提升稳定性^[42]	LSTM多步预测框架^[45]
统计验收	显著性检验/可靠性测试	t-test（t为衡量“样本结果”与“假设”之间的偏离程度的变量）证明预测负载有效性（统计显著性的衡量指标p=0.003）^[40];资源分配方差降低42%^[42]	SLA达标率χ²检验（χ²为卡方检验，用于检验样本数据是否符合某种分布或模型）^[46]
综合评分	多指标加权评估	效率(50%) + QoS(50%)=0.91^[42]	协作效率(60%)+资源利用率(40%)=0.90^[44];预测(40%)+决策(60%)=0.89^[46]
敏感性分析	参数扰动影响	突发流量时自动扩容触发成功率>95%^[41];阈值±10%波动对决策影响<5%^[43]	网络延迟波动下决策稳定性>95%^[44];模型冷启动误差<8%^[46]
可视化呈现	拓扑热力图、时序曲线	自适应混合预测算法（Adaptive Hybrid Prediction Algorithm，AHPA）预测曲线VS实际负载叠加图^[40]	多智能体决策路径拓扑图^[44]

评估维度	分析方法	国内相关技术	国外相关技术
性能指标提取	延迟/资源利用率	端到端时延降低42%^[47]；带宽利用率89%^[48]	空口时延0.25 ms^[51];高优先级用户时延保障率98.7%^[52]
统计验收	显著性检验/可靠性测试	t-test p<0.01^[47]；方差分析 p<0.05^[48]；χ²检验 p<0.01^[48]	t-test显示优先级调度增益显著（p=0.002）^[52];95%置信区间：能耗降低[26%,31%]^[53]
性能优势	性能提升百分比	突发流量丢包率降低60%^[47]；突发流量响应速度提升3倍^[49]	可靠性(50%)+时延(30%)+能效(20%)=0.94^[51];公平性(40%)+QoS(40%)+能效(20%)=0.87^[52];性能(60%)+能效(40%)=0.91^[53]
敏感性分析	参数扰动影响	节点失效20%时投递率>90%^[50]；组规模>50时耗时增长斜率0.8^[48]；负载波动±40%时成本变化<15%^[49]	高优先级用户占比超50%时：低优先级用户QoS达标率下降至65%^[52];节点移动速度提升至20 m/s时：最佳方案路由开销增加了25%^[54]
可视化呈现	拓扑/性能图表	时延热力图+链路利用率曲线^[47]；组播树拓扑演化动画^[50]	用户优先级与QoS达标率关系热力图^[52];能效-时延散点矩阵图^[54]

评估维度	分析方法	国内相关技术	国外相关技术
性能指标提取	延迟/吞吐量/控制开销	链路成功率>95%^[56]；路由收敛时间缩短40%^[57]	链路利用率提升至85%^[61]；切片隔离度>99%^[62]；备份路径建立时间<15 ms^[63]
纵向演化	技术迭代改进点	空分复用+交错退避机制^[58]；洋葱路由+定向扩散融合^[57]；定向洪泛算法^[59]	动态权重多路径算法^[61]；动态切片资源再分配机制^[62]
统计验收	显著性检验/可靠性测试	蒙特卡罗模拟链路稳定性^[56]；多径成功率t检验^[60]	蒙特卡罗模拟链路稳定性^[61]；故障恢复率χ²检验^[64]
综合评分	多指标加权评估	吞吐量(50%)+时延(30%)+能耗(20%)=0.91^[58]；匿名性(50%)+效率(50%)=0.82^[57]	可靠性(60%)+效率(40%)=0.88^[63]
敏感性分析	参数扰动影响	恶意节点占比20%时仍有效^[57]；信道干扰时切换延迟<10 ms^[60]	拓扑变化时收敛时间增加<15%^[61]；切片需求突变时调整延迟<8 s^[62]
可视化呈现	拓扑/性能图表	匿名路径关系图^[57]；光链向误差曲线^[59]	切片资源占用3D图^[62]；备份路径覆盖网络图^[63]

评估维度	分析方法	国内相关技术	国外相关技术
性能指标提取	延迟/资源利用率	端到端时延降低42%^[65]；带宽利用率89%^[66]	空口时延0.25 ms^[67];高优先级用户时延保障率98.7%^[69]
统计验收	显著性检验/可靠性测试	t-test p<0.01^[65]；方差分析 p<0.05^[67]；χ²检验p<0.01^[66]	t-test显示优先级调度增益显著（p=0.002）^[69];95%置信区间：能耗降低[26%,31%]^[70]
性能优势	性能提升百分比	突发流量丢包率降低60%^[65]；突发流量响应速度提升3倍^[68]	p可靠性(50%)+时延(30%)+能效(20%)=0.94^[67];公平性(40%)+QoS(40%)+能效(20%)=0.87^[69];性能(60%)+能效(40%)=0.91^[70]
敏感性分析	参数扰动影响	节点失效20%时投递率>90%^[66]；组规模>50时耗时增长斜率0.8^[64]；负载波动±40%时成本变化<15%^[68]	高优先级用户占比超50%时：低优先级用户QoS达标率下降至65%^[69];节点移动速度提升至20 m/s时：最佳方案路由开销增加25%^[71]
可视化呈现	拓扑/性能图表	时延热力图+链路利用率曲线^[65]；组播树拓扑演化动画^[68]	用户优先级与QoS达标率关系热力图^[69];能效-时延散点矩阵图^[71]