Optimal siting and sizing of demand response in a transmission constrained system with high wind penetration

This paper describes algorithms that use demand-side management to address large-scale integration of wind power. In particular, demand response (DR) is used to manage wind power intermittency by shifting the time that electrical power system loads occur in response to real-time prices and wind availability. An economic dispatch with transmission, DR capacity and operational constraints is used to model the operation of a transmission constrained system with a high penetration of wind power. This optimization model is used to determine the optimal sizing and distribution of DR given a fixed budget for customer incentives and the installation of enabling technology. We demonstrate the effectiveness of the operational model based on a simple PJM 5-bus system and an IEEE 118-bus system. Simulation results show that transmission constraints have a greater effect on sizing of DR capacity than the location of wind power, which means that buses electrically close to congested lines tend to have higher incentives to deploy DR resources than other buses. The second part of the work examines optimal siting of technology that enables DR based on the frequency of DR based load changes, which are generally a function of the network location.     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.     

Distributed wireless power transfer in sensor networks with multiple Mobile Chargers

We investigate the problem of efficient wireless power transfer in wireless sensor networks. In our approach, special mobile entities (called the Mobile Chargers) traverse the network and wirelessly replenish the energy of sensor nodes. In contrast to most current approaches, we envision methods that are distributed and use limited network information. We propose four new protocols for efficient charging, addressing key issues which we identify, most notably (i) what are good coordination procedures for the Mobile Chargers and (ii) what are good trajectories for the Mobile Chargers. Two of our protocols (DC, DCLK) perform distributed, limited network knowledge coordination and charging, while two others (CC, CCGK) perform centralized, global network knowledge coordination and charging. As detailed simulations demonstrate, one of our distributed protocols outperforms a known state of the art method, while its performance gets quite close to the performance of the powerful centralized global knowledge method.     

泛在电力物联网在北京经济技术开发区的应用探索

泛在电力物联网是物联网在电力领域的具体体现，建设泛在电力物联网是推进"三型两网"建设的关键环节，也是实现能源转型的必要手段。阐述了泛在电力物联网的定义，从供电公司角度出发，根据北京经济技术开发区实际情况，讨论了依托地区特点的泛在电力物联网实施策略和实际应用场景，分析了可能遇到的问题。得出结论：随着泛在电力物联网的深入建设，供电公司能够为电力客户提供多元化服务，提高客户满意度；地市供电公司能够依托泛在电力物联网开展更多电力相关业务；泛在电力物联网的安全性、实用性、有效性是发展面临的首要问题。     

摇摆运动下多环路主冷却剂系统自然循环流量的稳定性分析

海洋核动力平台因其突出的安全性已成为当今核能领域热点研究问题之一，但在海洋等非惯性条件下会使一回路系统的热工特性发生变化。针对此问题，本文对几种典型的一回路系统在摇摆条件下的自然循环流量波动特性进行计算分析。分别建立典型的双环路、三环路、四环路的一回路系统模型布置方案，并同时考虑摇摆中心的位置，根据流体动量守恒方程，得到不同状态下一回路系统内的流量变化规律。对于单堆双环路系统，摇摆中心在船上/中/下部位置时，环路流量波动幅度分别为13.2%/11.2%/9.5%，堆芯流量波动幅度分别为0.9%/0.8%/0.6%；对于单堆三环路系统，摇摆中心在船下部时，环路流量和堆芯流量波动幅度分别为9.2%和0.8%；对于单堆四环路系统，摇摆中心在船下部时，布置方案1和方案2的环路流量波动幅度分别为9.5%和9.2%，堆芯流量波动幅度分别为0.9%和0.7%。计算结果表明：采用单堆双环路的设计布置方案是最有利于系统稳定性的。     

Global optimization for power dispatch problems based on theory of moments

Non-convex of an optimal power dispatch problem makes it difficult to guarantee the global optimum. This paper presents a convex relaxation approach, called the Moment Semidefinite Programming (MSDP) method, to facilitate the search for deterministic global optimal solutions. The method employs a sequence of moments, which can linearize polynomial functions and construct positive semidefinite moment matrices, to form an SDP convex relaxation for power dispatch problems. In particular, the rank of the moment matrix is used as a sufficient condition to ensure the global optimality. The same condition can also be leveraged to estimate the number of global optimal solution(s). This method is effectively applied to {0,1}-economic dispatch (ED) problems and optimal power flow (OPF) problems. Simulation results showed that the MSDP method is capable of solving {0,1}-ED problems with integer values directly, and is able to identify if more than one global optimal solutions exist. In additional, the method can obtain rank-1 moment matrices for OPF’s counterexamples of existing SDP method, this ensures the global solution and overcomes the problem that existing SDP method cannot meet the rank-1 condition sometimes.     

Application of higher order spectral features and support vector machines for bearing faults classification

Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals.     

Research on phase shift characteristics of electromagnetic wave in plasma

The phase shift characteristics reflect the state change of electromagnetic wave in plasma sheath and can be used to reveal deeply the action mechanism between electromagnetic wave and plasma sheath. In this paper, the phase shift characteristics of electromagnetic wave propagation in plasma were investigated. Firstly, the impact factors of phase shift including electron density,collision frequency and incident frequency were discussed. Then, the plasma with different electron density distribution profiles were employed to investigate the influence on the phase shift characteristics. In a real case, the plasma sheath around the hypersonic vehicle will affect and even break down the communication. Based on the hypersonic vehicle model, we studied the electromagnetic wave phase shift under different flight altitude, speed, and attack angle. The results indicate that the phase shift is inversely proportional to the flight altitude and positively proportional to the flight speed and attack angle. Our work provides a theoretical guidance for the further research of phase shift characteristics and parameters inversion in plasma.     

含齿形裂隙类岩石材料单轴压缩试验研究

为研究含齿形裂隙岩石在单轴压缩下的破坏特征及强度特性，制作了含不同裂隙倾角和起伏角的齿形裂隙类岩石材料试件，并采用岩石力学伺服试验机进行单轴压缩试验。试验结果表明：（1）试件主要产生拉伸、剪切和拉剪复合裂纹，且根据裂纹的扩展路径可划分为A型（拉伸破坏）、B型（剪切破坏）、C型（复合破坏）3种破坏模式，裂隙倾角对试件最终破坏模式影响显著；（2）当裂隙倾角较小时，试件应力—应变曲线为多峰曲线，随着裂隙倾角的增大，曲线呈单峰形式，表现为延性减弱，脆性增强，而裂隙倾角相同但起伏角不同的试件应力—应变曲线大致相同；（3）当裂隙起伏角相同时，试件当量峰值强度随裂隙倾角的增大呈先减小后增大的规律，且裂隙起伏角对试件当量峰值强度的影响小于裂隙倾角。     

Screening of frozen-thawed conditions for keeping nutritive compositions and physicochemical characteristics of goat milk

Frozen milk can help producers overcome the seasonality of goat milk production, low goat production and short lactation periods, and avoid discarding milk during some special periods. We investigated effects of combination between freezing (cryogenic refrigerator of ?16 to ?20°C or ultra-cryogenic refrigerator of ?76 to ?80°C) and thawing (homeothermy of 20 to 25°C or refrigeration of 2 to 4°C) on nutritive compositions and physicochemical characteristics of raw goat milk during storage period (80 d). Compared with fresh goat milk, the frozen-thawed milk decreased contents of fat, protein, and lactose, as well as surface tension and stability coefficient, whereas increased effective diameter and polydispersity index. The average values of color values (L*, a*, and b*) in 4 group samples changed from 83.01 to 82.25, ?1.40 to ?1.54, 3.51 to 3.81, respectively, and the ΔE of most samples did not exceed 2. In contrast to the other 3 frozen-thawed treatments, goat milk treated with ultra-cryogenic freezing-homeothermic thawing (UFHT) possessed higher fat (5.20 g/100 g), smaller effective particle diameter (0.32 µm), and the lowest polydispersity index value (0.26). The color and confocal laser scanning microscopy images of UFHT were similar to those of fresh goat milk, illustrating UFHT was the optimal approach to maintain the natural quality of goat milk. Our finding provides a theoretical basis for producers to freeze surplus milk.