In the framework of liberalized deregulated electricity market, dynamic competitive environment exists between wholesale and retail dealers for energy supplying and management. Smart Grids topology in form of energy m...In the framework of liberalized deregulated electricity market, dynamic competitive environment exists between wholesale and retail dealers for energy supplying and management. Smart Grids topology in form of energy management has forced power supplying agencies to become globally competitive. Demand Response (DR) Programs in context with smart energy network have influenced prosumers and consumers towards it. In this paper Fair Emergency Demand Response Program (FEDRP) is integrated for managing the loads intelligently by using the platform of Smart Grids for Residential Setup. The paper also provides detailed modelling and analysis of respective demands of residential consumers in relation with economic load model for FEDRP. Due to increased customer’s partaking in this program the load on the utility is reduced and managed intelligently during emergency hours by providing fair and attractive incentives to residential clients, thus shifting peak load to off peak hours. The numerical and graphical results are matched for intelligent load management scenario.展开更多
智能电网利用新一代信息技术实现网络安全、可靠、高效地运行。智能电网邻域网(Smart Grid Neighborhood Area Network,SGNAN)负责处理终端发送到数据集中单元的数据,对数据传输有较高的实时性和可靠性要求。采用5G uRLLC(Ultra-reliabl...智能电网利用新一代信息技术实现网络安全、可靠、高效地运行。智能电网邻域网(Smart Grid Neighborhood Area Network,SGNAN)负责处理终端发送到数据集中单元的数据,对数据传输有较高的实时性和可靠性要求。采用5G uRLLC(Ultra-reliable and Low Latency Communication)技术建立SGNAN的上行链路资源调度模型,并给出解决方案。该方案依据优先级动态分配资源,定义分配矩阵、速率矩阵表示系统吞吐量(目标函数),使用改进的人工蜂群算法求得系统的最优资源分配方案。实验结果表明,该方案能够有效保证终端实时性、公平性,并改善系统的吞吐量。展开更多
为了满足用户在各类场景下对无线业务日益增长的要求,高密集部署的无线局域网(wireless local area network,WLAN)是未来发展的趋势。但由于频率资源有限,相同信道必然存在多个WLAN无线接入点(access point,AP),然而处于同一信道的AP会...为了满足用户在各类场景下对无线业务日益增长的要求,高密集部署的无线局域网(wireless local area network,WLAN)是未来发展的趋势。但由于频率资源有限,相同信道必然存在多个WLAN无线接入点(access point,AP),然而处于同一信道的AP会互相干扰,造成网络中小区间吞吐量的公平性下降,无法为用户提供良好的服务质量。为了提高网络公平性,改善用户体验,需要制定合理的网络参数调优方法,给出了一种基于神经网络和遗传算法对WLAN参数优化的方法。采用神经网络构建网络参数与网络吞吐量公平性之间的映射,将训练完成的模型作为遗传算法的适应度评估函数,通过遗传算法求解优化参数组合配置来改善WLAN吞吐量公平性问题。仿真结果表明所提出算法能够使得高密集WLAN吞吐量公平性得到提升。展开更多
终端直通技术(Device-to-Device,D2D)引入LTE-A蜂窝网络虽然能够提高蜂窝系统性能,但是却带来了很大的干扰。为了降低干扰,提升系统性能,如何进行资源分配成为研究的重点。首先,为了降低资源分配算法的复杂度和干扰强度,提出了D2D通信...终端直通技术(Device-to-Device,D2D)引入LTE-A蜂窝网络虽然能够提高蜂窝系统性能,但是却带来了很大的干扰。为了降低干扰,提升系统性能,如何进行资源分配成为研究的重点。首先,为了降低资源分配算法的复杂度和干扰强度,提出了D2D通信限制区域和D2D用户限制复用蜂窝用户(Cellular User Equipmen,CUE)资源区域的概念。其次,为了保证蜂窝系统服务质量(Quality of Service,Qo S)需求并提升系统性能,提出了一种D2D资源分配算法。最后,使用非线性规划问题中的乘子法来确定D2D用户和CUE的最佳发射功率,以最大化系统吞吐量。仿真结果表明,所提算法与已有方案相比能够显著提升系统的吞吐量和公平性。展开更多
文摘In the framework of liberalized deregulated electricity market, dynamic competitive environment exists between wholesale and retail dealers for energy supplying and management. Smart Grids topology in form of energy management has forced power supplying agencies to become globally competitive. Demand Response (DR) Programs in context with smart energy network have influenced prosumers and consumers towards it. In this paper Fair Emergency Demand Response Program (FEDRP) is integrated for managing the loads intelligently by using the platform of Smart Grids for Residential Setup. The paper also provides detailed modelling and analysis of respective demands of residential consumers in relation with economic load model for FEDRP. Due to increased customer’s partaking in this program the load on the utility is reduced and managed intelligently during emergency hours by providing fair and attractive incentives to residential clients, thus shifting peak load to off peak hours. The numerical and graphical results are matched for intelligent load management scenario.
文摘智能电网利用新一代信息技术实现网络安全、可靠、高效地运行。智能电网邻域网(Smart Grid Neighborhood Area Network,SGNAN)负责处理终端发送到数据集中单元的数据,对数据传输有较高的实时性和可靠性要求。采用5G uRLLC(Ultra-reliable and Low Latency Communication)技术建立SGNAN的上行链路资源调度模型,并给出解决方案。该方案依据优先级动态分配资源,定义分配矩阵、速率矩阵表示系统吞吐量(目标函数),使用改进的人工蜂群算法求得系统的最优资源分配方案。实验结果表明,该方案能够有效保证终端实时性、公平性,并改善系统的吞吐量。
文摘为了满足用户在各类场景下对无线业务日益增长的要求,高密集部署的无线局域网(wireless local area network,WLAN)是未来发展的趋势。但由于频率资源有限,相同信道必然存在多个WLAN无线接入点(access point,AP),然而处于同一信道的AP会互相干扰,造成网络中小区间吞吐量的公平性下降,无法为用户提供良好的服务质量。为了提高网络公平性,改善用户体验,需要制定合理的网络参数调优方法,给出了一种基于神经网络和遗传算法对WLAN参数优化的方法。采用神经网络构建网络参数与网络吞吐量公平性之间的映射,将训练完成的模型作为遗传算法的适应度评估函数,通过遗传算法求解优化参数组合配置来改善WLAN吞吐量公平性问题。仿真结果表明所提出算法能够使得高密集WLAN吞吐量公平性得到提升。
文摘终端直通技术(Device-to-Device,D2D)引入LTE-A蜂窝网络虽然能够提高蜂窝系统性能,但是却带来了很大的干扰。为了降低干扰,提升系统性能,如何进行资源分配成为研究的重点。首先,为了降低资源分配算法的复杂度和干扰强度,提出了D2D通信限制区域和D2D用户限制复用蜂窝用户(Cellular User Equipmen,CUE)资源区域的概念。其次,为了保证蜂窝系统服务质量(Quality of Service,Qo S)需求并提升系统性能,提出了一种D2D资源分配算法。最后,使用非线性规划问题中的乘子法来确定D2D用户和CUE的最佳发射功率,以最大化系统吞吐量。仿真结果表明,所提算法与已有方案相比能够显著提升系统的吞吐量和公平性。