Bargaining‐Based Smart Grid Pricing Model for Demand Side Management Scheduling

A smart grid is a modernized electrical grid that uses information about the behaviors of suppliers and consumers in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. In the operation of a smart grid, demand side management (DSM) plays an important role in allowing customers to make informed decisions regarding their energy consumption. In addition, it helps energy providers reduce peak load demand and reshapes the load profile. In this paper, we propose a new DSM scheduling scheme that makes use of the day‐ahead pricing strategy. Based on the Rubinstein–Stahl bargaining model, our pricing strategy allows consumers to make informed decisions regarding their power consumption, while reducing the peak‐to‐average ratio. With a simulation study, it is demonstrated that the proposed scheme can increase the sustainability of a smart grid and reduce overall operational costs.     

D型微孔光纤偏振响应特性研究

本文对D型微孔光纤的偏振响应特性进行了实验测试和理论上的数值计算,表明其出射光的偏振度依赖于入射光的偏振方向,存在着明显的极化效应,这种效应是由于其特有的D型微孔结构破坏了光纤结构的旋转对称性而引起的,数值计算的结果和实验值基本相符合。     

Demand Side Management for Thermally Activated Building Systems Based on Multiple Linear Regression

The building sector and its heating and cooling represent one of the major consumer of energy worldwide. Simultaneously, the share of fluctuating generation of renewable energies in the energy mix increases. Therefore storage and demand side management technologies are required. The new adaptive and predictive control algorithm for thermally activated building systems (TABS) based on multiple linear regression (AMLR) presented in this paper enables the application of demand side management (DSM) strategies. Based on simulations, different strategies have been compared with each other. By applying the AMLR algorithm, electricity energy cost savings of 38% could be achieved compared to the conventional control strategy for TABS, while increasing the thermal comfort. At the same time, thermal energy demand can be reduced in the range between 4% to 8%, and pump operation time from 86% to 89%.     

基于微网并网的智能电网用户用电福利研究

考虑需求侧响应的微网并网运行机制能够引导用户合理用电,对研究智能电网用户用电福利具有重要意义。综合光伏、风能发电的不稳定性,提出微网并网运行机制下需求侧响应策略,以微网运行成本最小和需求侧用电效用最大为目标,建立了考虑需求侧响应的微网并网运行福利模型。仿真结果表明所建立的模型可达到用户最大用电福利,且有利于削峰填谷,降低供电压力,提升用户参与建设微网的积极性。     

An Adaptive Smart Grid Management Scheme Based on the Coopetition Game Model

Recently, the idea of the smart grid has been gaining significant attention and has become a hot research topic. The purpose of this paper is to present a novel smart grid management scheme that uses game theory principles. In our proposed scheme, power appliances in the smart grid adaptively form groups according to the non‐cooperative hedonic game model. By exploiting multi‐appliance diversity, appliances in each group are dynamically scheduled in a cooperative manner. For efficient smart grid management, the proposed coopetition game approach is dynamic and flexible to adaptively respond to current system conditions. The main feature is to maximize the overall system performance while satisfying the requirements of individual appliances. Simulation results indicate that our proposed scheme achieves higher energy efficiency and better system performance than other existing schemes.     

基于需求响应的风电-抽水蓄能系统调度模型

针对大规模风电并网影响电网稳定运行的问题,基于日前用户侧电力负荷预测和实时电价预测,文中提出了一种电网吸纳风能的新模型。以最小化风电—抽水蓄能联合系统发电成本为目标,在目标求解过程中确定最佳自弹性系数和互弹性系数,运用基于实时电价的需求价格来弹性引导电力用户以实现负荷转移。考虑到用户侧电价弹性限制的约束,该方法采用遗传优化算法编程求解。仿真结果表明,需求侧资源主动参与优化调度可降低负荷峰谷差,利于系统稳定运行,并且可以减少发电成本,提高联合系统经济性。     

基于智能天线和动态虚拟簇的均衡节能路由

为WSN提出了一种能量节省与能耗均衡相结合的路由算法SaDVC-Routing。该算法在辅助中继和智能天线的波束范围内构建虚拟簇,从簇内选择中继加权值最大的节点充当路由中继。根据节点能耗情况和节点间距离,利用波束扩展法对虚拟簇进行动态更新。如果波束宽度超过阈值或者中继节点死亡,则依据加权距离矩阵重新发起路由请求。仿真表明,算法既能有效降低能量消耗,也可以在局部和全局实现能耗均衡。     

公众移动通信网应急能力需求模型与网络方案研究

本文建立了自然灾害和突发事件下公众移动通信网应急能力需求模型,提出并探讨了针对该需求模型的公众移动通信网应急能力建设方向和网络技术实现方案.     

An Optimal Power Scheduling Method Applied in Home Energy Management System Based on Demand Response

In this paper, we first introduce a general architecture of an energy management system in a home area network based on a smart grid. Then, we propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real‐time electricity price, which is transferred to an energy management controller (EMC). Referring to the DR, the EMC achieves an optimal power scheduling scheme, which is delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost‐effective way possible. In our research, to avoid the high peak‐to‐average ratio (PAR) of power, we combine the real‐time pricing model with the inclining block rate model. By adopting this combined pricing model, our proposed power scheduling method effectively reduces both the electricity cost and the PAR, ultimately strengthening the stability of the entire electricity system.     

超级电容吸收再生电能和抵御供电断续的试验研究

在某些恶劣电网环境下运行的变频传动系统,可以利用超级电容(SC)优异的充放电性能,既吸收利用传动系统产生的大量再生电能,又维持其在电压暂降、供电中断时平稳运行,一举两得。笔者给出了简单实用的控制策略,经仿真和试用证明是行之有效的。