Optimal PMU placement considering topology constraints

A new optimization algorithm for optimal PMU configuration based on combination of graph theory and genetic algorithm is proposed. According to four topology reconstruction rules and three PMU configuration rules based on the graphic relationships between PMUs, constraints of PMU placement are put forward through topology constraint analysis, which dramatically limits the feasible solution space, thereby enhancing the algorithm speed. Meanwhile, an improved genetic algorithm based on serial number coding is presented to avoid infeasible solutions and improve the overall optimization performance. New corresponding crossover and mutation operator is also created. Examples show that the proposed algorithm performs very well and is highly valuable to large-scale networks.     

Analysis of the effect of voltage level requirements on an electricity market equilibrium model

This paper presents a conjectural-variation-based equilibrium model of a single-price electricity market. The main characteristic of the model is that the market equilibrium equations incorporate the effect of the voltage constraints on the companies’ strategic behavior. A two-stage optimization model is used to solve the market equilibrium. In the first stage, an equivalent optimization problem is used to compute the day-ahead market clearing process. In the second stage, some generation units have to modify their active and reactive power in order to meet the technical constraints of the transmission network. These generation changes are determined by computing an AC optimal power flow.     

Non-kinematic calibration of a six-axis serial robot using planar constraints

This paper describes a non-kinematic calibration method developed to improve the accuracy of a six-axis serial robot, in a specific target workspace, using planar constraints. Simulation confirms that the stiffness of the robot, as well as its kinematic parameters, can be identified. An experimental validation shows that the robot's accuracy inside the target workspace is significantly enhanced by reducing the maximum distance errors from 1.321 mm to 0.274 mm. The experimental data are collected using a precision touch probe, which is mounted on the flange of a FANUC LR Mate 200iC industrial robot, and a high precision 9-in. granite cube. The calibration method makes use of a linear optimization model based on the closed-loop calibration approach using multi-planar constraints. A practical validation approach designed to reliably evaluate the robot's accuracy after calibration is also proposed.     

Adaptive control of pure-feedback nonlinear systems with full-state time-varying constraints and unmodeled dynamics

This paper focuses on the problem of adaptive control for a class of pure-feedback nonlinear systems with full-state time-varying constraints and unmodeled dynamics. By introducing a one-to-one nonlinear mapping, the constrained pure-feedback nonlinear system with state and input unmodeled dynamics is transformed into unconstrained pure-feedback system. The controller design based on the transformed novel system is proposed by using a modified dynamic surface control method. Dynamic signal and normalization signal are designed to handle dynamical uncertain terms and input unmodeled dynamics, respectively. By adding nonnegative normalization signal into the whole Lyapunov function and using the introducing compact set in the stability analysis, all signals in the whole system are proved to be semiglobally uniformly ultimately bounded, and all states can obey the time-varying constraint conditions. A numerical example is provided to demonstrate the effectiveness of the proposed approach.     

Adaptive fuzzy control for nontriangular form systems with time-varying full-state constraints

This article investigates an adaptive fuzzy tracking control problem for a class of nontriangular form systems with asymmetric time-varying full state constraints. Unknown functions are approximated by the fuzzy logic systems. A domination approach is employed to tackle the nontriangular form structure. Time-varying asymmetric barrier Lyapunov functions (ABLFs) are adopted to ensure full-state constraints satisfaction. Based on the backstepping technique and time-varying ABLFs, an adaptive controller is proposed and guarantees that all the signals in the closed-loop system are ultimately bounded and the time-varying full state constraints are met. Simulation examples are presented to further demonstrate the effectiveness of the proposed approach.     

Robustness analysis and distributed control of a networked system with time-varying delays

This paper is concerned with the robustness analysis and distributed output feedback control of a networked system with uncertain time-varying communication delays. This system consists of a collection of linear time-invariant subsystems that are spatially interconnected via an arbitrary directed network. Using a dissipation inequality that incorporates dynamic hard IQCs (integral quadratic constraints) for the delay uncertainties, we derive some sufficient robustness conditions in the form of coupled linear matrix inequalities, in which the coupled parts reflect the interconnection structure of the system. We then provide a procedure to construct a distributed controller to ensure the robust stability of the closed-loop system and to achieve a prescribed $\ell_2$-gain performance. The effectiveness of the proposed approach is demonstrated by some numerical examples.     

集中管理模式下的政府投资工程委托代理机制研究

随着我国政府投资工程项目管理模式改革不断深入,集中管理模式得到广泛应用。以深圳市为例阐述了集中管理模式下的政府投资工程项目运行机制及治理结构,运用仿真建模和博弈分析的方法对这种模式下的两个层次的委托代理关系进行了研究,从基于契约合同的委托代理方向建立效用函数对激励与约束进行分析,得出这种模式能够建立起有效的激励相容和自我约束的结论,从基于行政管理模式下的权力寻租和激励与约束方向进行分析,提出了建立长效监督管理机制的措施建议,具有一定的理论意义和现实意义。     

同城化视角下湖北小池空间优化策略研究

同城化是"从区域论城市"基础上形成的一种新的城市区域发展观。在湖北小池滨江新区上升为"省级战略"之际,从政策主导、内生驱动、外借助推、资源聚合等4个方面分析小池南望融入九江同城发展的动力。结合相关数据分析指出,在"中四角"地理中心与"鄂东门户"耦合的特殊区位条件下,小池发展面临区位优势转化难、产业定位游离、城镇化动力不足、空间风貌特色欠缺等问题,并从九江、黄梅"同城共建、拥江共享、错位共赢"3个维度指出,位于鄂东前沿阵地的小池城镇空间需要重点从构建完善的公共服务设施体系和基础设施网络、提升拥江发展的梯次空间品质、聚合错位发展的产业布局等方面调控优化,以彰显两地的同城化效应,带动鄂东门户地带的发展。     

深度学习辅助约束辨识的电力市场快速出清方法

日前电力市场出清需要求解大规模安全约束经济调度问题,尽管实际采用线化处理方法,但需要考虑N－1场景下的大量安全约束,导致其规模庞大,难以快速求解。提出了一种深度学习辅助的日前市场快速出清方法,以满足快速出清计算场合的应用需求。首先,设计基于深度神经网络的安全约束经济调度模型计算框架,将深度学习技术应用于日前电力市场出清计算过程,兼顾安全约束经济调度模型的求解速度和求解精度;其次,提出面向起作用约束辨识的深度学习策略,从特征向量、深度神经网络结果处理2个方面,实现安全约束经济调度起作用约束集的辨识,并将其纳入日前市场出清模型,以简化模型的复杂度;最后,在接入新能源的IEEE 30标准测试系统中验证了所述方法的有效性。利用深度神经网络预辨识安全约束经济调度模型的起作用约束,有利于降低模型复杂度,提高日前市场出清的计算效率。     

考虑经济安全性的有源配电网供电能力研究

与传统配电网不同,接入有源配电网的可控分布式电源能够参与配电网的经济运行。可控分布式电源的出力分配由主动配电网的经济调度策略确定。为实现供电能力最大化,可控分布式电源通常运行在额定状态,这与经济运行的目标相背离。而且配电网运行需满足N-1安全准则,而现有文献中的分布式电源(DG)优化运行模型均未计及N-1准则,所得出力策略未必满足系统安全要求。综上所述,为解决这一问题,提出了一种考虑经济调度和N-1安全约束的供电能力模型。以供电能力经济比最小和安全距离均衡比最小为多目标,算例表明所提模型能保证N-1安全,实现了综合考虑系统经济性、安全性下的最优,验证了所提模型是合理、有效的。