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Harnessing Trend Theory to Enhance Distributed Proximal Point Algorithm Approaches for Multi-Area Economic Dispatch Optimization 认领 引用
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作者 Yaming Ren Xing Deng 《Computers, Materials & Continua》 SCIE EI 2025年第3期4503-4533,共31页
The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution,particularly within multi-area interconnected power grids.This complexity necessi... The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution,particularly within multi-area interconnected power grids.This complexity necessitates the employment of distributed solution methodologies,which are not only essential but also highly desirable.In the realm of computational modelling,the multi-area economic dispatch problem(MAED)can be formulated as a linearly constrained separable convex optimization problem.The proximal point algorithm(PPA)is particularly adept at addressing such mathematical constructs effectively.This study introduces parallel(PPPA)and serial(SPPA)variants of the PPA as distributed algorithms,specifically designed for the computational modelling of the MAED.The PPA introduces a quadratic term into the objective function,which,while potentially complicating the iterative updates of the algorithm,serves to dampen oscillations near the optimal solution,thereby enhancing the convergence characteristics.Furthermore,the convergence efficiency of the PPA is significantly influenced by the parameter c.To address this parameter sensitivity,this research draws on trend theory from stock market analysis to propose trend theory-driven distributed PPPA and SPPA,thereby enhancing the robustness of the computational models.The computational models proposed in this study are anticipated to exhibit superior performance in terms of convergence behaviour,stability,and robustness with respect to parameter selection,potentially outperforming existing methods such as the alternating direction method of multipliers(ADMM)and Auxiliary Problem Principle(APP)in the computational simulation of power system dispatch problems.The simulation results demonstrate that the trend theory-based PPPA,SPPA,ADMM and APP exhibit significant robustness to the initial value of parameter c,and show superior convergence characteristics compared to the residual balancing ADMM. 展开更多
关键词 Multi-area economic dispatch problem proximal point algorithm trend theory
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Robust H_∞ Load Frequency Control of Multi-area Power System With Time Delay:A Sliding Mode Control Approach 认领 引用 被引量：10
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作者 Yonghui Sun Yingxuan Wang +2 位作者 Zhinong Wei Guoqiang Sun Xiaopeng Wu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2018年第2期610-617,共8页
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 re... 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. 展开更多
关键词 Index Terms--Load frequency control （LFC） multi-area powersystem robust control sliding mode control （SMC） time delay.
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Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm 认领 引用 被引量：10
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作者 Junqing Li Quanke Pan +2 位作者 Peiyong Duan Hongyan Sang Kaizhou Gao 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2019年第5期1240-1250,共11页
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.,... 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. 展开更多
关键词 Chemical-reaction optimization algorithm gridbased crowding distance multi-area environmental/economic dispatch (MAEED) problem multi-objective optimization
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Resilient Fixed-Order Distributed Dynamic Output Feedback Load Frequency Control Design for Interconnected Multi-Area Power Systems 认领 引用 被引量：6
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作者 Ali Azarbahram Amir Amini Mahdi Sojoodi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2019年第5期1139-1151,共13页
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 cont... 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. 展开更多
关键词 Dynamic output feedback control interconnected multi-area power systems load frequency control linear matrix inequalities power system control
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Multi-Area Unit Commitment Using Hybrid Particle Swarm Optimization Technique with Import and Export Constraints 认领 引用 被引量：2
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作者 S. R. P. CHITRA SELVI R. P. KUMUDINI DEVI C. CHRISTOBER ASIR RAJAN 《Engineering（科研）》 2009年第3期140-150,共11页
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 ... 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. 展开更多
关键词 Multi-Area Unit Commitment Evolutionary Programming Dynamic Programming Method
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Ant Lion Optimization Approach for Load Frequency Control of Multi-Area Interconnected Power Systems 认领 引用
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作者 R. Satheeshkumar R. Shivakumar 《Circuits and Systems》 2016年第9期2357-2383,共27页
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 ... 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. 展开更多
关键词 Load Frequency Control (LFC) Multi-Area Power System Proportional-Integral (PI) Controller Ant Lion Optimization (ALO) Bat Algorithm (BAT) Genetic Algorithm (GA) Particle Swarm Optimization (PSO)
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Unit Commitment with Joint Chance Constraints in Multi-area Power Systems with Wind Power Based on Partial Sample Average Approximation 认领 引用 被引量：2
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作者 Jinghua Li Hongyu Zeng Yutian Xie 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2025年第1期241-252,共12页
Joint chance constraints(JCCs)can ensure the consistency and correlation of stochastic variables when participating in decision-making.Sample average approximation(SAA)is the most popular method for solving JCCs in un... Joint chance constraints(JCCs)can ensure the consistency and correlation of stochastic variables when participating in decision-making.Sample average approximation(SAA)is the most popular method for solving JCCs in unit commitment(UC)problems.However,the typical SAA requires large Monte Carlo(MC)samples to ensure the solution accuracy,which results in large-scale mixed-integer programming(MIP)problems.To address this problem,this paper presents the partial sample average approximation(PSAA)to deal with JCCs in UC problems in multi-area power systems with wind power.PSAA partitions the stochastic variables and historical dataset,and the historical dataset is then partitioned into non-sampled and sampled sets.When approximating the expectation of stochastic variables,PSAA replaces the big-M formulation with the cumulative distribution function of the non-sampled set,thus preventing binary variables from being introduced.Finally,PSAA can transform the chance constraints to deterministic constraints with only continuous variables,avoiding the large-scale MIP problem caused by SAA.Simulation results demonstrate that PSAA has significant advantages in solution accuracy and efficiency compared with other existing methods including traditional SAA,SAA with improved big-M,SAA with Latin hypercube sampling(LHS),and the multi-stage robust optimization methods. 展开更多
关键词 Unit commitment joint chance constraint renewable energy multi-area power system wind power sample average approximation partial sample average approximation
Decentralized Optimization of Multi-area Power-transportation Coupled Systems Based on Variational Inequalities 认领 引用 被引量：1
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作者 Shiwei Xie Zhidong Chen +2 位作者 Yachao Zhang Shuai Cao Kaiyue Chen 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2025年第5期2386-2398,共13页
Current urban transport and energy systems are gradually being integrated and developed towards a state of multi-area interconnection.This paper proposes a decentralized optimization approach of multi-area power-trans... Current urban transport and energy systems are gradually being integrated and developed towards a state of multi-area interconnection.This paper proposes a decentralized optimization approach of multi-area power-transport coupled systems(PTCSs)based on this change.To begin with,models concerning optimal power flow and mixed equilibrium flow are defined to describe flow patterns,respectively.Considering the traffic assignment model is non-linear and challenging to solve,this paper converts it into an equivalent variational inequality(Ⅵ).With this foundation,a decentralized optimization model is proposed,and decoupling strategies are investigated.To solve the problem effectively,an improved algorithm applicable to the decentralized optimization of PTCSs,supported by theⅣtool,is proposed.In addition,a rigorous convergence analysis of the proposed algorithm was conducted.Simulations indicate the proposed algorithm solves the problem with good results and can guarantee convergence within a reasonable time frame. 展开更多
关键词 Decentralized optimization electric vehicle multi-area power-transport coupled system variational inequality
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Double-Layer Optimization Mechanism for Multi-Area OPF Considering Valve-Point Loading Effect 认领 引用 被引量：1
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作者 Jizhong Zhu Cong Zeng +1 位作者 Yun Liu Xuancong Xu 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2025年第2期683-691,共9页
In terms of the multi-area optimal power flow (OPF) problem, the optimized objectives are always a fuel cost function expressed by a second-order polynomial. However, the valve-point loading effect, whose cost curve i... In terms of the multi-area optimal power flow (OPF) problem, the optimized objectives are always a fuel cost function expressed by a second-order polynomial. However, the valve-point loading effect, whose cost curve is a transcendental function formed by the superposition of the sine and polynomial function, will make the objective function non-convex and non-differentiable. Conventional distributed optimization technologies can hardly make a solution directly. Therefore, it is necessary to realize a distributed solution for multi-area OPF from another point of view. In this paper, we constitute a new double-layer optimization mechanism. The proposed distributed meta-heuristic optimization (DMHO) algorithm is put on the top layer to optimize the dispatching of each area, and in each iteration a distributed power flow calculation method is embedded as the bottom layer to minimize the mismatch of power balance. Numerical experiments demonstrate that the proposed approach not only implements a multi-area OPF distributed solution but also accelerates the convergence rate, improves the solution accuracy and enhances the robustness. In addition, a fully decentralized computation experiment is performed in an actual distributed environment to test its practicability and computation efficiency. 展开更多
关键词 Distributed computation platform distributed meta-heuristic optimization algorithm double-layer optimization mechanism multi-area optimal powerflow
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Robust Two-stage Dispatch of Multi-area Integrated Electric-gas Systems: A Decentralized Approach 认领 引用 被引量：1
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作者 Nan Jia Cheng Wang +2 位作者 Yao Li Nian Liu Tianshu Bi 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2025年第2期850-860,共11页
This paper proposes a decentralized robust two-stage dispatch framework for multi-area integrated electric-gas systems (M-IEGSs), with the consideration of Weymouth and linepack equations of tie-pipelines. The overall... This paper proposes a decentralized robust two-stage dispatch framework for multi-area integrated electric-gas systems (M-IEGSs), with the consideration of Weymouth and linepack equations of tie-pipelines. The overall methodology includes the equivalent conversion for the robust two-stage program and the decentralized optimization for the equivalent form. To obtain a tractable and equivalent counterpart for the robust two-stage program, a quadruple-loop procedure based on the column-and-constraint generation (C&CG) and the penalty convex-concave procedure (P-CCP) algorithms is derived, resulting in a series of mixed integer second-order cone programs (MISOCPs). Then, an improved I-ADMM is proposed to realize the decentralized optimization for MISOCPs. Moreover, three acceleration methods are devised to reduce the computation burden. Simulation results validate the effectiveness of the proposed methodology and corresponding acceleration measures. 展开更多
关键词 Decentralized robust dispatch improved iterative alternating direction multiplier method multi-area integrated electric-gas systems robust two-stage programs
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Demand response for frequency control of multi-area power system 认领 引用 被引量：10
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作者 Yu-Qing BAO Yang LI +2 位作者 Beibei WANG Minqiang HU Peipei CHEN 《Journal of Modern Power Systems and Clean Energy》 SCIE EI 2017年第1期20-29,共10页
Over the last few years, lots of attentions have been given to the demand response(DR) for the frequency control. DR can be incorporated with traditional frequency control method and enhance the stability of the syste... Over the last few years, lots of attentions have been given to the demand response(DR) for the frequency control. DR can be incorporated with traditional frequency control method and enhance the stability of the system. In this paper, the frequency control strategy of DR for a multiarea power system is specially designed. In order to quickly stabilize the frequency of different areas, the tie-line power is adopted as the additional input signal of DR. To get the optimal parameters of the control system, the frequency control problem is formulated as a multi-objective optimization problem, and the parameters such as the integral gains of secondary frequency control, the frequency bias parameters, and coefficients of DR are optimized. Numerical results verify the effectiveness of the proposed method. 展开更多
关键词 Demand response Frequency control Multi-area Genetic algorithm
A Multi-time Scale Tie-line Energy and Reserve Allocation Model Considering Wind Power Uncertainties for Multi-area Systems 认领 引用 被引量：4
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作者 Jian Xu Siyang Liao +7 位作者 Haiyan Jiang Danning Zhang Yuanzhang Sun Deping Ke Xiong Li Jun Yang Xiaotao Peng Liangzhong Yao 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2021年第4期677-687,共11页
Continued expansion of the power grid and the increasing proportion of wind power centralized integration leads to requirements in sharing both energy and reserves among multiple areas under a hierarchical control str... Continued expansion of the power grid and the increasing proportion of wind power centralized integration leads to requirements in sharing both energy and reserves among multiple areas under a hierarchical control structure,which successively requires a correction between schedule plans within multi-time scale.In order to address this problem,this paper develops an information integration method integrating complicated relationships among fuel cost,total thermal power output,reserve capacity,owned reserves and expectations of load shedding and wind curtailment,into three types of time-related relationship curves・Furthermore,a multi-time scale tieline energy and reserves allocation model is proposed,which contains two levels in the control structure,two time scales in dispatch sequence and multiple areas integrated within wind farms as scheduling objects・The efficiency of the proposed method is tested in a 9-bus test system and IEEE 118-bus system.The results show that a cross-regional control center is able to approach the optimal scheduling results of the whole system with the integrated uploaded relationship curves.The proposed model not only relieves energy and reserve shortages in partial areas but also allocates them to more urgent need areas in a high effectivity manner in both day-ahead and intraday time scales. 展开更多
关键词 Energy and reserve allocation hierarchical control structure multi-area system multi-time scale economic dispatch wind power
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Multi-area Frequency-constrained Unit Commitment for Power Systems with High Penetration of Renewable Energy Sources and Induction Machine Load 认领 引用 被引量：2
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作者 Leibao Wang Hui Fan +5 位作者 Jifeng Liang Longxun Xu Tiecheng Li Peng Luo Bo Hu Kaigui Xie 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2024年第3期754-766,共13页
The increasing penetration of renewable energy sources(RESs)brings great challenges to the frequency security of power systems.The traditional frequency-constrained unit commitment(FCUC)analyzes frequency by simplifyi... The increasing penetration of renewable energy sources(RESs)brings great challenges to the frequency security of power systems.The traditional frequency-constrained unit commitment(FCUC)analyzes frequency by simplifying the average system frequency and ignoring numerous induction machines(IMs)in load,which may underestimate the risk and increase the operational cost.In this paper,we consider a multiarea frequency response(MAFR)model to capture the frequency dynamics in the unit scheduling problem,in which regional frequency security and the inertia of IM load are modeled with high-dimension differential algebraic equations.A multi-area FCUC(MFCUC)is formulated as mixed-integer nonlinear programming(MINLP)on the basis of the MAFR model.Then,we develop a multi-direction decomposition algorithm to solve the MFCUC efficiently.The original MINLP is decomposed into a master problem and subproblems.The subproblems check the nonlinear frequency dynamics and generate linear optimization cuts for the master problem to improve the frequency security in its optimal solution.Case studies on the modified IEEE 39-bus system and IEEE 118-bus system show a great reduction in operational costs.Moreover,simulation results verify the ability of the proposed MAFR model to reflect regional frequency security and the available inertia of IMs in unit scheduling. 展开更多
关键词 Decomposition algorithm frequency response frequency-constrained unit commitment induction machine multi-area mixed-integer nonlinear programming(MINLP)
面向点与区域目标联合成像侦察的多无人机协同任务规划 认领 引用 被引量：1
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作者 洪芳宇 张涛 +1 位作者 杨昊 伍国华 《控制与决策》 EI CSCD 北大核心 2026年第4期1122-1134,共13页
无人机在成像侦察领域的应用是提升战场侦察效能的重要手段.研究一种多无人机协同的点与区域目标联合成像侦察任务规划问题,其中区域侦察任务可由多架性能各异的无人机联盟协同侦察.鉴于此,建立以最小化侦察任务执行时间和侦察失败任务... 无人机在成像侦察领域的应用是提升战场侦察效能的重要手段.研究一种多无人机协同的点与区域目标联合成像侦察任务规划问题,其中区域侦察任务可由多架性能各异的无人机联盟协同侦察.鉴于此,建立以最小化侦察任务执行时间和侦察失败任务数量为优化目标的混合整数规划模型,重点考虑机载成像设备能力、侦察任务成像质量要求以及时间窗等多重约束,提出一种领域知识驱动的多无人机协同侦察任务规划方法求解.首先,根据解空间结构重塑问题理解,将原问题分解为多机任务分配和单机任务规划两阶段求解.为加快算法求解,依据问题特征设计基于最优联盟的多机任务分配算法和联盟优先的单机任务调度算法产生高质量的初始解.然后,在迭代优化阶段,从最优性条件出发,设计4种问题领域知识驱动的多机任务调整因子以及包含4种特殊邻域结构的改进变邻域下降算法,向最优解方向搜索高质量多机任务分配方案和单机任务调度方案.最后,通过大量仿真实验验证所提出方法在优化任务完成率和侦察任务执行时间上的优势.此外,通过一系列敏感性分析识别点/区域侦察任务比例、无人机数量和成像传感器能力等3个关键因素对结果的影响. 展开更多
关键词 多无人机协同 点/区域目标覆盖 成像侦察 无人机任务规划方法
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榆神府矿区多煤层重复采动覆岩裂隙带高度预测研究 认领 引用 被引量：1
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作者 王红伟 左开永 +5 位作者 陈玉涛 董国良 李延军 焦建强 白金源 王力涛 《采矿与岩层控制工程学报》 EI 北大核心 2026年第2期284-298,共15页
榆神府矿区煤层埋深浅、上覆基岩薄、松散层厚,多数矿井涉及多煤层重复采动,受煤层采高、间距等多因素影响,上下采场围岩空间相互作用,导致裂隙带高度难以精准预测。以榆神府矿区典型煤矿多煤层重复采动裂隙带高度为研究对象,采用物理... 榆神府矿区煤层埋深浅、上覆基岩薄、松散层厚,多数矿井涉及多煤层重复采动,受煤层采高、间距等多因素影响,上下采场围岩空间相互作用,导致裂隙带高度难以精准预测。以榆神府矿区典型煤矿多煤层重复采动裂隙带高度为研究对象,采用物理相似模拟、理论分析以及深度学习相结合的方法,分析了多煤层重复采动裂隙发育规律,构建了煤层采高、间距、埋深、倾角、工作面长度及间隔岩层坚固性系数与裂隙带高度的多因素耦合非线性回归模型,建立了基于SSA-BP神经网络的多煤层重复采动裂隙带高度预测方法,并验证了其准确性。研究结果表明:瓷窑塔煤矿重复采动下裂隙发育呈现“局部缓慢增长—贯通非线性跃升—动态稳定”三阶段特征,最终裂隙带发育高度为139.0 m;煤层采高、间距、间隔岩层坚固性系数及工作面长度耦合下的非线性回归模型拟合系数R2为0.880,为裂隙带发育高度关键影响因素;对比传统经验公式与BP模型预测结果,SSA-BP模型预测MAPE值分别降低了22.96%、6.70%,RMSE值低至1.79,稳定性更优;以榆神府矿区中汇富能煤矿14205工作面为验证模型,预测高度与实测高度相对误差为1.3%,小于5%。研究对榆神府矿区多煤层开采导水裂隙带高度预测具有较强普适性,可为该矿区多煤层开采水害防治提供有益借鉴。 展开更多
关键词 榆神府矿区 多煤层开采 裂隙带高度 非线性回归 SSA-BP神经网络
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基于联合备用容量的新型多区域电力系统经济调度 认领 引用
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作者 尹艳玲 任旭阳 +1 位作者 卜旭辉 李轩 《太阳能学报》 EI CAS CSCD 北大核心 2026年第5期91-97,共7页
在资源条件固定的情况下,为进一步提高新型多区域电力系统的灵活调度能力,提出一种基于联合备用容量的新型多区域电力系统经济调度模型。首先,通过综合考虑多区域新能源消纳,提出多区域联合备用容量计算理论。其次,基于多区域联合备用容... 在资源条件固定的情况下,为进一步提高新型多区域电力系统的灵活调度能力,提出一种基于联合备用容量的新型多区域电力系统经济调度模型。首先,通过综合考虑多区域新能源消纳,提出多区域联合备用容量计算理论。其次,基于多区域联合备用容量,构建针对高比例新能源引入的多区域互联电力系统经济调度模型,并使用基于排序分组的自适应多策略差分进化算法求解该调度模型,同时针对模型中的约束条件,提出一种修补策略与罚函数方法相结合的约束处理方法。最后,将所提出方法与传统个体备用容量分别在三区域和四区域电力系统中进行比较,证明基于联合备用容量的新型多区域电力系统经济调度模型的有效性。 展开更多
关键词 互联电力系统 调度 旋转备用容量 新能源 差分进化算法 多区域联合备用容量
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街区尺度下高校多层宿舍区建筑群能耗模拟与形态因素研究 认领 引用
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作者 刘启波 赵涓汝 +1 位作者 曹房轩 颜雨恒 《西安建筑科技大学学报（自然科学版）》 北大核心 2026年第1期120-129,共10页
随着对建筑能耗研究的视角逐渐由单体尺度扩大到街区尺度下的群体建筑,建筑群体的不同形态会对建筑能耗产生影响.为研究在街区尺度视角下高校多层宿舍区形态与能耗的影响规律,将西安地区高校宿舍建筑组成的宿舍区视为功能统一的街区,从... 随着对建筑能耗研究的视角逐渐由单体尺度扩大到街区尺度下的群体建筑,建筑群体的不同形态会对建筑能耗产生影响.为研究在街区尺度视角下高校多层宿舍区形态与能耗的影响规律,将西安地区高校宿舍建筑组成的宿舍区视为功能统一的街区,从单体、群体的角度分析总结宿舍区的形态特征,建立其典型模型.进而通过对典型模型中宿舍区建筑的布局形式、建筑间距、建筑高度、朝向等因素调整衍生,利用UMI(Urban Modeling Interface)工具对不同形态特征的宿舍区典型模型进行能耗模拟.研究发现:有利于西安地区高校多层宿舍区节能的建筑形态分别为多层行列式布局形式;建筑间距系数为1.35和1.35~1.39的行列式布局和围合式布局;正南北朝向的行列式布局和南偏西30°朝向的围合式布局;较小的山墙间距和较高的建筑高度.本研究结果可以为高校多层宿舍区的规划设计与建筑节能提供参考与借鉴. 展开更多
关键词 街区尺度 多层宿舍区 形态因素 能耗模拟
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陆海多要素匹配对陆海统筹影响的组态路径——基于动态QCA的面板数据分析 认领 引用
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作者 狄乾斌 张洁 +2 位作者 陈小龙 孟庆义 刘一鸣 《人文地理》 CSSCI 北大核心 2026年第3期25-35,120,共11页
本文运用动态模糊集定性比较分析法(QCA)探究2012—2022年中国沿海11省(自治区、直辖市)陆海多要素匹配对陆海统筹影响。结果表明:①各省陆海多要素匹配、陆海统筹水平随时间提升,空间差异显著。②高陆海统筹水平组态路径包括“人口科... 本文运用动态模糊集定性比较分析法(QCA)探究2012—2022年中国沿海11省(自治区、直辖市)陆海多要素匹配对陆海统筹影响。结果表明:①各省陆海多要素匹配、陆海统筹水平随时间提升,空间差异显著。②高陆海统筹水平组态路径包括“人口科技复合驱动型”“科技资金复合驱动型”和“全面匹配协调型”3种;低水平组态路径有“资金失衡主导型”“人口科技陆海失衡型”“科技资金陆海失衡型”3类。③影响路径在沿海经济圈存在空间差异,东部海洋经济圈科技和资金匹配度优势突出,北部海洋经济圈环境匹配度更为优越,南部海洋经济圈依靠资源和环境匹配度相互作用推动陆海统筹。研究为制定差异化陆海统筹政策提供理论依据和实践指导。 展开更多
关键词 陆海统筹 沿海地区 多要素匹配 组态路径 动态QCA
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基于产量-环境-经济多目标协同的覆膜旱作稻田氮肥优化策略 认领 引用 被引量：1
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作者 任健 陈少卿 +5 位作者 胡诚 张智 刘东海 刘海涛 吕世华 胡克林 《农业工程学报》 EI CAS CSCD 北大核心 2026年第6期87-95,共9页
为解决水稻覆膜旱作模式化肥一次性基施导致的前期生长过旺而后期缺氮问题,该研究于2021—2022年在川中丘陵区开展了2种水分处理(W1,传统淹水;W2,覆膜旱作)和3种氮肥处理(N1,0;N2,135 kg/hm2尿素一次性基施;N3,传统淹水,施用135 kg/h... 为解决水稻覆膜旱作模式化肥一次性基施导致的前期生长过旺而后期缺氮问题,该研究于2021—2022年在川中丘陵区开展了2种水分处理(W1,传统淹水;W2,覆膜旱作)和3种氮肥处理(N1,0;N2,135 kg/hm2尿素一次性基施;N3,传统淹水,施用135 kg/hm2尿素,基追比3:2;覆膜旱作,尿素和鸡粪各67.5 kg/hm2一次性基施)的田间试验,以经济效益最大化为目标,并以产量最佳和环境影响最低为约束条件,结合WHCNS(soil water heat carbon nitrogen simulator)模型在不同施氮总量和有机肥替代率情景的模拟结果,构建了基于产量-环境-经济多目标协同的覆膜旱作稻田氮肥管理模型,确定了有机无机最佳配施比例及数量。结果表明:构建的氮肥管理模型模拟值与实测值的决定系数均高于0.95(P<0.001),说明模型拟合效果很好。以2022年为例,与原有机肥替代率50%(总施氮量135 kg/hm2)方案相比,有机肥替代率64%(总施氮量157.9 kg/hm2)优化方案的氮素损失量保持不变,产量和净收益分别提高了41 kg/hm2和45元/hm2。该研究可为覆膜旱作水稻实现高产高效绿色生产提供科学施氮依据与技术支撑。 展开更多
关键词 产量 水稻 覆膜旱作 丘陵山区 氮肥 多目标协同 模型
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多民族聚居地区民众获得感量表的编制及信效度检验 认领 引用
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作者 关香丽 张雅琪 李雪皎 《西部学刊》 2026年第13期22-25,共4页
结合多民族聚居地区的文化特色与社会特征,通过文献梳理确定量表理论结构并生成初始条目。采用项目分析、探索性因素分析、验证性因素分析及信效度检验等方法,逐步优化量表。结果显示:量表包含5个维度(经济条件提高、公共服务完善、生... 结合多民族聚居地区的文化特色与社会特征,通过文献梳理确定量表理论结构并生成初始条目。采用项目分析、探索性因素分析、验证性因素分析及信效度检验等方法,逐步优化量表。结果显示:量表包含5个维度(经济条件提高、公共服务完善、生活环境舒适、国家认同壮大、身心和谐健康),共21个题;量表结构模型拟合良好(χ2/df=4.25,NFI=0.91,RMSEA=0.069,IFI=0.92,CFI=0.92),且各维度间区分效度理想;总量表Cronbach’sα系数为0.95,分半信度为0.86,表明测量结果稳定可靠;总量表与生活满意度量表、整体幸福感量表的相关系数分别为0.53(p<0.01)、0.32(p<0.01),效标效度显著。结论:该量表符合预期理论建构,信效度指标均满足心理测量学要求,可作为多民族聚居地区民众获得感的测量工具。 展开更多
关键词 多民族聚居地区 获得感 信效 效度
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