Resilient Fixed-Order Distributed Dynamic Output Feedback Load Frequency Control Design for Interconnected Multi-Area Power Systems

The paper proposes a novel H∞ load frequency control(LFC) design method for multi-area power systems based on an integral-based non-fragile distributed fixed-order dynamic output feedback(DOF) tracking-regulator control scheme. To this end, we consider a nonlinear interconnected model for multiarea power systems which also include uncertainties and timevarying communication delays. The design procedure is formulated using semi-definite programming and linear matrix inequality(LMI) method. The solution of the proposed LMIs returns necessary parameters for the tracking controllers such that the impact of model uncertainty and load disturbances are minimized. The proposed controllers are capable of receiving all or part of subsystems information, whereas the outputs of each controller are local. These controllers are designed such that the resilient stability of the overall closed-loop system is guaranteed. Simulation results are provided to verify the effectiveness of the proposed scheme. Simulation results quantify that the distributed(and decentralized) controlled system behaves well in presence of large parameter perturbations and random disturbances on the power system.

Robust H_∞ Load Frequency Control of Multi-area Power System With Time Delay:A Sliding Mode Control Approach

This paper is devoted to investigate the robust H∞sliding mode load frequency control(SMLFC) of multi-area power system with time delay. By taking into account stochastic disturbances induced by the integration of renewable energies,a new sliding surface function is constructed to guarantee the fast response and robust performance, then the sliding mode control law is designed to guarantee the reach ability of the sliding surface in a finite-time interval. The sufficient robust frequency stabilization result for multi-area power system with time delay is presented in terms of linear matrix inequalities(LMIs). Finally,a two-area power system is provided to illustrate the usefulness and effectiveness of the obtained results.

Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm

In this study, we present a Pareto-based chemicalreaction optimization(PCRO) algorithm for solving the multiarea environmental/economic dispatch optimization problems.Two objectives are minimized simultaneously, i.e., total fuel cost and emission. In the proposed algorithm, each solution is represented by a chemical molecule. A novel encoding mechanism for solving the multi-area environmental/economic dispatch optimization problems is designed to dynamically enhance the performance of the proposed algorithm. Then, an ensemble of effective neighborhood approaches is developed, and a selfadaptive neighborhood structure selection mechanism is also embedded in PCRO to increase the search ability while maintaining population diversity. In addition, a grid-based crowding distance strategy is introduced, which can obviously enable the algorithm to easily converge near the Pareto front. Furthermore,a kinetic-energy-based search procedure is developed to enhance the global search ability. Finally, the proposed algorithm is tested on sets of the instances that are generated based on realistic production. Through the analysis of experimental results, the highly effective performance of the proposed PCRO algorithm is favorably compared with several algorithms, with regards to both solution quality and diversity.

Multi-Area Unit Commitment Using Hybrid Particle Swarm Optimization Technique with Import and Export Constraints

This paper presents a novel approach to solve the Multi-Area unit commitment problem using particle swarm optimization technique. The objective of the multi-area unit commitment problem is to determine the optimal or a near optimal commitment strategy for generating the units. And it is located in multiple areas that are interconnected via tie lines and joint operation of generation resources can result in significant operational cost savings. The dynamic programming method is applied to solve Multi-Area Unit Commitment problem and particle swarm optimization technique is embedded for computing the generation assigned to each area and the power allocated to all committed unit. Particle Swarm Optimization technique is developed to derive its Pareto-optimal solutions. The tie-line transfer limits are considered as a set of constraints during the optimization process to ensure the system security and reliability. Case study of four areas each containing 26 units connected via tie lines has been taken for analysis. Numerical results are shown comparing the cost solutions and computation time obtained by using the Particle Swarm Optimization method is efficient than the conventional Dynamic Programming and Evolutionary Programming Method.

Ant Lion Optimization Approach for Load Frequency Control of Multi-Area Interconnected Power Systems

This work proposes a novel nature-inspired algorithm called Ant Lion Optimizer (ALO). The ALO algorithm mimics the search mechanism of antlions in nature. A time domain based objective function is established to tune the parameters of the PI controller based LFC, which is solved by the proposed ALO algorithm to reach the most convenient solutions. A three-area interconnected power system is investigated as a test system under various loading conditions to confirm the effectiveness of the suggested algorithm. Simulation results are given to show the enhanced performance of the developed ALO algorithm based controllers in comparison with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bat Algorithm (BAT) and conventional PI controller. These results represent that the proposed BAT algorithm tuned PI controller offers better performance over other soft computing algorithms in conditions of settling times and several performance indices.

Data-driven Surrogate-assisted Method for High-dimensional Multi-area Combined Economic/Emission Dispatch

Multi-area combined economic/emission dispatch(MACEED)problems are generally studied using analytical functions.However,as the scale of power systems increases,ex isting solutions become time-consuming and may not meet oper ational constraints.To overcome excessive computational ex pense in high-dimensional MACEED problems,a novel data-driven surrogate-assisted method is proposed.First,a cosine-similarity-based deep belief network combined with a back-propagation(DBN+BP)neural network is utilized to replace cost and emission functions.Second,transfer learning is applied with a pretraining and fine-tuning method to improve DBN+BP regression surrogate models,thus realizing fast con struction of surrogate models between different regional power systems.Third,a multi-objective antlion optimizer with a novel general single-dimension retention bi-objective optimization poli cy is proposed to execute MACEED optimization to obtain scheduling decisions.The proposed method not only ensures the convergence,uniformity,and extensibility of the Pareto front,but also greatly reduces the computational time.Finally,a 4-ar ea 40-unit test system with different constraints is employed to demonstrate the effectiveness of the proposed method.

基于衍生搜索政治优化算法解决含可再生能源的多区域经济调度问题

随着可再生能源并入多区域电力系统,其不确定性大大增加了电力系统多区域经济调度的复杂度。如何高效求解含有风力和太阳能的多区域经济调度(multi-areaeconomic dispatch containing wind and solar energy,MAEDWS)问题面临着严峻的挑战。针对现有优化算法在处理MAEDWS问题时存在收敛速度慢和求解精度低等不足,该文提出一种基于衍生搜索的政治优化(derivative search-based political optimizer,DSPO)算法。在政治优化算法的基础上,引入首脑引领策略和衍生搜索机制。前者引领候选解前往更有希望的区域,加快收敛速度;后者在区域获胜者周围衍生邻域解,丰富多样性。该文将DSPO算法和其他6种代表性算法应用于MAEDWS问题,并进行对比分析。收敛曲线和性能指标的结果表明DSPO算法在收敛效率、求解精确度、稳定性方面取得了整体最优。

京津多机场系统容量损失影响分析

全球范围内多机场系统数量和规模都在不断增长。由于终端区内有限资源的限制,邻近机场的运行存在一定的相关性,这导致多机场系统运行效率低下。为了估计多机场运行产生的限制,以北京终端区为例提出一种统计分析框架对多机场系统的容量损失进行整体分析。首先,根据理论容量模型分别计算出北京终端区各机场的理论容量,并进一步确定各机场独立运行下的实际容量;其次,以北京终端区的历史运行数据为基础,估计出3个机场及终端区系统的具有鲁棒性的Pareto容量包络曲线;最后,基于独立运行容量与相关运行容量量化出终端区各机场及多机场系统的实际容量损失。为进一步提高多机场终端区的运行效率提供建议与参考。

基于多源数据与随机森林方法的城市建成区提取——以郑州市为例

基于夜间灯光数据的阈值分割法在城镇建成区提取研究中被广泛应用,但由于夜间灯光数据分辨率低、灯光溢出和阈值分割法无法顾及区域差异等问题,一定程度上影响了该方法的提取精度。以郑州市为例,以LJ1-01与NPP/VIIRS两种夜间灯光影像为主要数据源,结合Landsat8中分辨率遥感影像、网络城市兴趣点(POI)及路网数据,利用随机森林分类方法对郑州市2018年建成区进行提取,参考土地利用数据,对RF分类法与NTL、VANUI、BANUI、PANUI、RANUI指数等阈值法进行对比实验和精度评价,评估基于多源数据的随机森林分类方法在城市建成区提取中的优势。实验表明,RF比阈值法提取的建成区更接近真实建成区且提取精度更高,具有更好适用性;LJ1-01数据提取的效果和精度总体优于NPP/VIIRS数据;在采用RF分类时,各类特征的重要性在不同夜光数据源中表现差异较大。

节日表达与文化共生:节日促进散杂居地区民族乡村民族交往交流交融研究

散杂居地区民族乡村在经济发展上互为补充、文化上相互吸纳、生活上互相尊重,其节日文化中烙刻着中华民族共有的文化基因,成为散杂居地区民族乡村各民族交往交流交融的载体和媒介。就节日符号而言,可划分为中华民族共有传统节日、少数民族特色传统节日和新型节日。就节日促进散杂居地区民族乡村交往交流交融的媒介价值与实践逻辑而言,在日常生活实践、社会互动和文化认同中表明节日可以促进散杂居地区民族乡村各民族交往交流交融,并以节日为媒介构建出经济空间、互动空间和仪式空间来展现其实践逻辑,维系了地方认同和民族内聚力,促进了民族交往交流交融。重视挖掘节日的共有共享媒介价值,促进散杂居地区民族乡村各民族群众的广泛交往、全面交流、深度交融。

多模式组合的居住区绿地对热环境影响的模拟研究

居住区作为城镇居民三生活动最主要的空间单元,其热环境质量直接决定了小区内居民的舒适感和幸福度.本文在归纳总结城镇居住区绿地组合模式的基础上,基于非静力流体力学技术和热力学原理,耦合有限差分及交替方向隐式算法对小区范围内不同模式结构组合的绿地生态系统进行热效应模拟研究,通过对比分析不同模式组合的绿地系统热环境效应特征,探寻多模式组合下的居住区绿地与局地热环境间的交互关系.结果表明:在相同的模拟条件下,“中心+宅间”绿地组合模式的热环境效应最好,“组团+宅间”模式次之,“宅间”模式热环境效应最差;模拟区域内三种绿地组合模式的最高最低温度差分别为2.36、2.31和2.34℃,且温度自西南向东北方呈现圈层式分布特征;多绿植类型的组合模式对局地热环境的改善效果依次为:草+灌+乔>草+乔>草+灌>草,灌木对绿地热环境舒适度的改善效果不显著.该研究能够为居住区绿地规划设计与实践提供科学参考.

城市多民族聚居区基层法治政府建设之我见

党的十八大以来,随着全面推进依法治国战略的逐步深化,城市多民族聚居区基层政府法治建设取得了长足进步,但是在实践中较之一般区域的法治建设仍存在选择性执法等明显短板。通过对城市多民族聚居区进行调研,发现影响区域法治政府建设的因素,既有法治政府建设过程中存在的共性问题如执法力量薄弱、执法机制不顺畅等,也有受区域内民族宗教问题影响等个性因素。立足城市多民族聚居区域实际,以问题为导向,一方面要通过加强整合执法力量、创新执法机制等方式提高基层政府的法治能力,另一方面要通过加强法治宣传教育,促进法治、德治、自治相结合,改善基层政府法治建设环境,做到既依法保护民族宗教利益、群众的合法权益,又维护法治权威。

“近零碳”目标下港区多能互补标准体系研究

利用多能互补技术推动能源结构调整是实现港口绿色低碳发展的有效手段。本研究以国内主要沿海港口为对象,聚焦港区建设、运营、管理等环节开展多能互补技术标准研究,基于系统工程学方法构建港区多能互补标准体系,利用港区承载的可再生能源自然禀赋与清洁能源应用,通过多能互补技术的能源结构优化减少交通运输行业碳排放,推动双碳目标实现。

基于自发数据传输的高效双LAN太赫兹无线局域网MAC协议

针对现有的双局域网(LAN)太赫兹无线局域网(Dual-LAN THz WLAN)相关介质访问控制(MAC)协议中存在的某些节点会在多个超帧内重复发送相同的信道时隙请求帧以申请时隙资源以及网络运行的一些时段存在空闲时隙等问题,提出一种基于自发数据传输的高效MAC协议——SDTE-MAC(high-Efficiency MAC protocol based on Spontaneous Data Transmission)。SDTE-MAC通过让各节点都维护一张或多张时间单元链表,使各节点与其余节点在网络运行时间上达到同步,从而获悉各节点应该在信道空闲时隙的什么位置开始发送数据帧,优化了传统的信道时隙分配和信道剩余时隙再分配的流程,提高了网络吞吐量和信道时隙利用率,降低了数据时延,能够进一步提升双LAN太赫兹无线局域网的性能。仿真结果表明,网络饱和时,相较于AHT-MAC(Adaptive High Throughout multi-pan MAC protocol)中的N-CTAP(Normal Channel Time Allocation Period)时段时隙资源分配新机制以及自适应缩短超帧时段机制,SDTE-MAC的MAC层吞吐量提升了9.2%,信道时隙利用率提升了10.9%,数据时延降低了22.2%。

基于推拉理论与多源数据的山东地区乡村景观吸引力评价体系研究

提升乡村吸引力是应对乡村衰退、实现乡村振兴的必由之路,本文选取山东地区10处景观建设项目,对其进行乡村吸引力的评估,运用多源数据支持的评价方法,建立科学的评价指标体系,以山东地区乡村的景观拉力和需求推力为评价内容,以提高乡村旅游吸引力为价值导向,为更好地推进山东地区乡村景观建设提供技术支撑和科学依据。

苏南水网地区蓝绿空间格局多情景模拟预测

【目的】模拟预测苏南水网地区蓝绿空间格局多情景发展趋势,探究促进地区可持续发展的情景方案。【方法】以江苏省苏州市吴江南片区为例,设置自然发展、生态保护优先和城镇发展优先等3种情景,借助CA-Markov模型,对2030年蓝绿空间格局变化趋势进行多情景模拟分析,并运用形态学空间格局分析(MSPA)和景观连通性评价解读蓝绿空间景观生态结构与生态格局特征。【结果】不同发展情景下蓝绿空间规模与格局变化差异显著。自然发展和城镇发展优先情景下,蓝绿空间面积呈现加速减少趋势,分别减少了3626.37、7145.74 hm^(2)。蓝绿空间核心区、孔隙等形态类型负向变化剧烈,蓝绿空间破碎度增加,连通性降低。生态保护优先情景与自然发展和城镇发展优先情景相比,蓝绿空间面积分别增加了2904.30、6423.67 hm^(2),蓝绿空间核心区等形态类型增幅明显,孔隙率显著降低,蓝绿空间破碎度降低,连通性增强。【结论】自然发展和城镇发展优先情景对水网地区蓝绿空间呈现负向影响趋势,生态保护优先情景在维持蓝绿空间面积与格局稳定,改善蓝绿空间连通性方面效果显著。

种植技术和种植密度对吉花2号主要农艺性状和产量的影响

研究不同种植技术和种植密度对吉林省多粒型花生吉花2号主要农艺性状和产量的影响,筛选适宜吉林省生态环境的种植技术和最佳种植密度,完善吉花2号配套高效栽培技术。采用2种种植技术及5个种植密度(1.79×10^(5)、2.02×10^(5)、2.30×10^(5)、2.69×10^(5)、3.23×10^(5)株/hm^(2)),研究特定时期花生光合指标及产量变化。结果显示,吉花2号采用小垄双行种植技术、种植密度为2.02×10^(5)株/hm^(2)时生育期最短,较双粒穴播种植技术生育期提前1~2 d;植株的株高最小,有利于地下部干物质积累;叶面积系数最大,总光合势最大;产量最高(3651.15 kg/hm^(2)),较双粒穴播种植技术增产10.17%。小垄双行种植技术在不同密度下,吉花2号产量都高于双粒穴播种植技术。因此,小垄双行种植技术在生产上应大力推广。

基于群体热感觉和区域占用率的多区域变风量空调系统优化控制方法

为优化多区域变风量空调系统的控制性能,同时使室内环境满足人员的热舒适需求,提出了一种基于群体热感觉和区域占用率的多区域变风量空调系统优化控制方法。根据室内人员的群体热感觉和各区域内的人员数量,采用调控算法调整室温设定值,进而调整各控制区域的末端送风量。搭建了仿真平台,对该控制方法与传统控制方法从控制效果、人员热舒适性、空调系统能耗等方面进行了对比分析。研究结果表明:加入群体热感觉后,该控制方法相较于传统控制方法空调系统节能率为7.5%以上;若同时考虑群体热感觉和区域占用率,该控制方法的节能率高于8.5%。

An Efficient Multi-area Networks-Merging Model for Power System Online Dynamic Modeling

To improve accuracy and efficiency in power systems dynamic modeling,the distributed online modeling approach is a good option.In this approach,the power system is divided into sub-grids,and the dynamic models of the sub-grids are built independently within the distributed modeling system.The subgrid models are subsequently merged,after which the dynamic model of the whole power system is finally constructed online.The merging of the networks plays an important role in the distributed online dynamic modeling of power systems.An efficient multi-area networks-merging model that can rapidly match the boundary power flow is proposed in this paper.The iterations of the boundary matching during network merging are eliminated due to the introduction of the merging model,and the dynamic models of the sub-grid can be directly“plugged in”with each other.The results of the calculations performed in a real power system demonstrate the accuracy of the integrated model under both steady and transient states.

考虑特殊区域的离散区域划分方法

基于多机器人系统的区域覆盖中的区域划分问题,分析现有区域覆盖任务发现,在任务区域中存在危险区域或优先级更高的特殊区域。针对特殊区域需要分配给最少的机器人的情况,设计了一种基于Morse分解的离散区域划分方法。该方法用放射状Morse分解来定义离散任务区域的空间结构,并提出一种改进回溯法来确定最优分割线,以避免分割特殊区域并保持多机器人工作量均衡。仿真给出了在特殊区域分布不同、机器人数量不同的场景下的区域划分结果,并与两种现有算法进行了比较。结果表明,所提方法能够生成稳定的解,有效减少特殊区域的分割,合理分配多机器人的工作量。