Modelling demand response in organized wholesale energy markets

We propose a bi-level optimization model for demand response in organized wholesale energy markets. In this model, the lower level performs the economic dispatch of energy and generates the price and the upper level minimizes the total amount of demand response subject to a net benefit requirement. In an economic sense, demand response is a trade of ‘consuming rights’ instead of a sale of energy. Therefore it must be traded separately from the energy market. Although a bi-level optimization model is very hard to solve in general, we demonstrate that realistic power networks have characteristics that can be exploited to reduce the effective size of the problem instance. In particular, we transform the nonconvex net benefit test constraint to an equivalent linear form, and reformulate the nonconvex complementarity conditions of doubly bounded variables using SOS2 constraints. For realistic instances of the MPEC, we employ a three-phase approach that exploits the fast local solution from a nonlinear programming solver as well as LP-based bound strengthening within a mixed integer/SOS2 formulation. The model is tested against various data cases and settings, and generates useful insight for demand response dispatch operations in practice.     

Agro-ecosystem modeling can aid in the optimization of biomass feedstock supply

Recent European Directives promoted the development of biofuels, requesting mandatory limits to their emissions ot greenhouse gases (GHG). Second-generation biofuels based on lignocellulosic biomass are prime candidates but their GHG emissions are variable and uncertain. Agro-ecosystem modeling can capture them and the performance of biofuel feedstocks.This study aimed at optimizing feedstock supply for a bioethanol unit in France, from agricultural residues, annual and perennial crops. Their productivity and environmental impacts were modelled on a regional scale using geo-referenced data on soil properties, crop management, land-use and future weather data. Several supply scenarios were tested. Cereal straw was the most efficient feedstock but had a low availability, and only miscanthus could meet the bioethanol plant's demand. Sorghum combined poor yields and high GHG emissions compared by miscanthus and triticale. A mix of three biomass sources used less than 3% of the regional agricultural land while abating GHG emissions by 60%.     

A detection problem: Sensitivity and uncertainty analysis of a land surface temperature approach to detecting dynamics of water use by groundwater-dependent vegetation

Sustainable management of groundwater-dependent vegetation (GDV) requires the accurate identification of GDVs, characterisation of their water use dynamics and an understanding of associated errors. This paper presents sensitivity and uncertainty analyses of one GDV mapping method which uses temperature differences between time-series of modelled and observed land surface temperature (LST) to detect groundwater use by vegetation in a subtropical woodland. Uncertainty in modelled LST was quantified using the Jacobian method with error variances obtained from literature. Groundwater use was inferred where modelled and observed LST were significantly different using a Student's t-test. Modelled LST was most sensitive to low-range wind speeds (<1.5 m s⁻¹), low-range vegetation height (<=0.5 m), and low-range leaf area index (<=0.5 m² m⁻²), limiting the detectability of groundwater use by vegetation under such conditions. The model-data approach was well-suited to detection of GDV because model-data errors were lowest for climatic conditions conducive to groundwater use.     

Tracking Performance Bound with Finite Control Energy and Erasure Channel Energy Constraint

This paper studies the tracking performance of the single‐input single‐output (SISO), finite dimensional, linear and time‐invariant (LTI) system under the channel input energy constraint over the Erasure channel. A new performance index is proposed which is minimized over all two‐degree‐of‐freedom stabilizing controllers. The explicit expressions of the lower bound of the performance index and the minimum of the signal‐to‐noise ratio are obtained. The results show that the performance bound is correlated to unstable poles, non‐minimum phase zeros and the packet loss probability. Finally, examples are given to validate the conclusions derived.     

微型之字形压电式能量收集器输出电压的建模和仿真

为了有效解决无线传感器网络节点的供电难题,提出之字形结构的微型压电式能量收集器。相比于传统的直悬臂梁,此结构等效加大了压电梁的长度,降低了系统的固有振动频率。建立了之字形压电梁的本构方程和受迫振动方程,推导得到其输出电压的频域表达式。基于之字形压电梁的结构,利用ANSYS软件对其进行了谐响应分析。仿真结果表明,压电梁的输出电压在各阶固有振动频率处存在极值,符合理论分析的结果;输出电压大小随压电梁长度增加而降低,随压电梁宽度增加而升高,但均为非线性关系;压电梁末端质量块的长度和厚度、基体层厚度减小时,会导致输出电压的增大。在论文中所提出的结构尺寸下,10根直梁构成的之字形结构压电梁,在其一阶固有振动频率处,输出电压可达10 V以上,符合无线传感器网络节点的实际供电需求,证明了之字形压电梁结构的有效性。     

基于停车诱导系统的能量均衡可靠路由协议的设计

无线传感器网络中节点的能量是有限的,如何设计一个能有效节能的路由协议是其研究的热点之一.针对实际的停车位诱导系统提出了一种能量均衡的可靠路由协议.该协议在网络的初始阶段先建立全局网络拓扑,然后根据能量代价函数选择下一跳转发的节点,节点上方有障碍物的时候更新节点的可靠度信息.由于综合考虑了节点的剩余能量、跳数、邻居节点的距离以及可靠度等因素,使得网络节点能量的消耗得以均衡,达到延长网络生命周期的目的.在仿真平台对能量均衡的可靠路由协议进行了仿真分析,并且和最短路径路由进行了对比,从网络生命周期、网络能量均值以及网络能量方差三个方面分别分析,验证了本协议的优越性.最后将协议应用到实际的停车位诱导系统中,取得了较显著的效果.     

一种基于有限信道的能量高效节点调度机制

在低负载、低功耗无线传感器网络中,节点状态切换的能量消耗因为用于数据传输的能量较小而变得不可忽略。针对此问题,提出了结合多信道技术与时分多路访问( TDMA)技术的节点调度算法。该算法设计了基于接收端的连续时隙分配策略以减少节点状态切换次数,并且在可用无线信道有限的约束条件下,提出了信道分配与时隙调整机制,实现了时隙重用并最小化有限信道约束对优化节点状态切换次数的影响。仿真实验结果表明,当可用无线信道数为3~5时,算法能够有效地改善节点能量效率。当可用无线信道数大于3之后,算法能够获得优化的数据汇聚时间。     

基于博弈理论的农田能量异构网络节点协同资源利用

针对无线传感器网络中耗能不均问题,以及可再生能源节点在农田无线传感器网络中应用的具体情况,将博弈理论引入无线传感器网络能耗问题研究中,建立了基于博弈理论的节点成簇方法,实现提高可再生能源利用率、均衡非可再生能源节点能耗的目标。方法首先建立簇收益与簇内节点收益评估模型,进行簇收益计算、簇内的两类能量异构节点个体收益的计算。在计算簇收益和节点收益的基础上进行节点成簇博弈,使得成簇方案向收益更高的策略空间进行跳转,最终达到博弈中的均衡状态。仿真实验表明,通过博弈进行无线传感器网络成簇,能够充分利用可再生能源节点能量,降低和均衡非可再生能源节点能耗,最终达到延长网络寿命的目标。     

基于三角模算子的RPL协议路由优化算法

针对当前低功耗有损网络拓扑构建及路径选择的参考度量单一,能量均衡性差的问题,提出了一种基于三角模算子的RPL协议路由优化算法。本文阐述了低功耗有损网络路由协议的网络拓扑构建机理和路由过程,基于三角模融合算法,重新定义了网络节点的能量指标和逻辑距离隶属度并进行了融合,更为合理地进行父节点选定,实现数据采集传输业务可靠性和有效性的进一步提升,最后通过实验仿真验证了改进后的路由协议性能。