电网安全调度中输电阻塞管理的演化策略

输电阻塞是电力系统运行中的常见问题 .本文建立了用于电网安全调度中输电阻塞管理的数学模型——带线性约束的多目标模糊优化问题模型 ,给出了求解该模型的演化策略 .实际的计算结果表明 ,演化策略解决输电阻塞问题是有效的 .     

Improved time varying inertia weight PSO for solved economic load dispatch with subsidies and wind power effects

This article presents a new approach to economic load dispatch (ELD) problems by the considering the cost functions, impact renewable energy as wind turbin and subsidies. Economic dispatch is the short‐term determination of the optimal output of a number of electricity generation facilities, to meet the system load, at the lowest possible cost, subject to transmission and operational constraints. The main goal in the deregulated system is subsidies and analysis performance on government to minimize the total fuel cost while satisfying the load demand and operational constraints. The practical ELD problems have nonsmooth cost functions with equality and inequality constraints, which make the problem of finding the global optimum difficult when using any mathematical approaches. Accordingly, particle swarm optimization with time‐varying inertia weight (PSO‐TVIW) used for solving this problem. The effectiveness of the proposed strategy is applied over real‐world engineering problem and highly constrained. Obtained results indicate that PSO‐TVIW can successfully solve this problem. © 2014 Wiley Periodicals, Inc. Complexity 21: 40–49, 2016     

冷藏车内部流场的数值研究

冷藏车厢内部的空气流场是冷藏运输和冷藏车设计与应用中的要点,因此以一台冷藏车为研究对象,建立了一个冷藏车内部气流组织特性的数学模型,分析了各种因素对内部气流的影响。该研究结果对促进中国冷藏汽车技术的发展有重要的意义。     

机械式冷藏车蒸发器结霜特性的研究

机械冷藏车蒸发器结霜会增加传热热阻和减小换热量,必须对结霜过程进行深入了解。建立了一个机械冷藏车蒸发器结霜的数学模型,并计算了结霜量、蒸发器换热量随时间的变化过程。获得了各个入口空气参数对蒸发器结霜厚度和换热量的影响规律。研究发现结霜严重地影响了蒸发器换热性能。     

New approach for the identification of power system economic dispatch parameters

It is well known that the coefficients of the input-output characteristics of the thermal steam-turbine model as well as the network model parameters have a great effect on the optimal economic operation of all thermal-electric power systems. Until today, these coefficients, the loss formula coefficients, theB-coefficients, and the active-reactive power loss models have been estimated using the well-known least-square estimation algorithm.In this paper, we present a new algorithm to estimate the power system parameters for economic dispatch calculation (EDC); this algorithm is based on the least absolute-value approximation (LAV)l ₁-norm. We compare the results obtained using the proposed algorithms with those obtained using the least-square error algorithm (LS). Optimal costs as well as overall network performance resulting from the implementation of each technique provide the basis of our conclusion.This work was supported by the Natural Science and Engineering Research Council of Canada, Grant No. A4146.     

Distribution sensitivity for certain classes of chance-constrained models with application to power dispatch

Using results from parametric optimization, we derive for chance-constrained stochastic programs quantitative stability properties for locally optimal values and sets of local minimizers when the underlying probability distribution is subjected to perturbations in a metric space of probability measures. Emphasis is placed on verifiable sufficient conditions for the constraint-set mapping to fulfill a Lipschitz property which is essential for the stability results. Both convex and nonconvex problems are investigated. For a chance-constrained model of power dispatch, where the power demand enters as a random vector with incompletely known probability distribution, we discuss consequences of our general results for the stability of optimal generation costs and optimal generation policies.The authors thank P. Kleinmann (formerly with the Humboldt-Universität, Berlin, Germany) for his active cooperation in designing the power dispatch model and J. Mayer (MTA SZTAKI, Budapest, Hungary) for his insight into energy optimization. Further thanks are due to the referees for their constructive criticism.This research was developed in the course of a contract study between the International Institute for Applied Systems Analysis, Laxenburg, Austria and the Humboldt-Universität, Berlin, Germany.     

Solving nonconvex economic load dispatch problem using particle swarm optimization with time varying acceleration coefficients

This article presents the design and application of an efficient hybrid heuristic search method to solve the practical economic dispatch problem considering many nonlinear characteristics of power generators, and their operational constraints, such as transmission losses, valve‐point effects, multi‐fuel options, prohibited operating zones, ramp rate limits and spinning reserve. These practical operation constraints which can usually be found at the same time in realistic power system operations make the economic load dispatch (ELD) problem a nonsmooth optimization problem having complex and nonconvex features with heavy equality and inequality constraints. A particle swarm optimization with time varying acceleration coefficients is proposed to determine optimal ELD problem in this paper. The proposed methodology easily takes care of solving nonconvex ELD problems along with different constraints like transmission losses, dynamic operation constraints, and prohibited operating zones. The proposed approach has been implemented on the 3‐machines 6‐bus, IEEE 5‐machines 14‐bus, IEEE 6‐machines 30‐bus systems and 13 thermal units power system. The proposed technique is compared with solve the ELD problem with hybrid approach by using the valve‐point effect. The comparison results prove the capability of the proposed method give significant improvements in the generation cost for the ELD problem. © 2015 Wiley Periodicals, Inc. Complexity 21: 299–308, 2016     

Optimal economic load dispatch based on wind energy and risk constrains through an intelligent algorithm

This article focus on optimal economic load dispatch based on an intelligent method of shark smell optimization (SSO). In this problem, the risk constrains has been considered which has root in uncertainity and unpredictable behavior of wind power. Regarding to increasing of this clean energy in power systems and un‐dispatchable behavior of wind power, its conditional value at risk index considered in this article which consists of loss from load and "spilling" wind energy connected with unpredictable imbalances among generation and load. This problem has been considered as an optimization problem based on SSO that evaluate the balance between cost and risk. This algorithm is based on distinct shark smell abilities for localizing the prey. In sharks' movement, the concentration of the odor is an important factor to guide the shark to the prey. In other words, the shark moves in the way with higher odor concentration. This characteristic is used in the proposed SSO algorithm to find the solution of an optimization problem. Effectiveness of the proposed method has been applied over 30‐bus power system in comparison with other techniques. © 2016 Wiley Periodicals, Inc. Complexity 21: 494–506, 2016     

Noise emission assessment of a hybrid electric mid-size truck

In the attempt to improve urban environmental conditions, city or national incentives encourage the use of cleaner vehicles, including hybrid electric vehicles. This paper explores the actual noise impact of this alternative drivetrain technology on the noise emission of a mid-size delivery truck powered by a parallel hybrid powertrain, compared with an equivalent internal combustion engine truck on the basis of pass-by noise measurements. It investigates jointly the overall emission, the main noise sources and the vertical directivity of the vehicle. The essential benefit results from the existence of a full-electric mode below 50 km/h, with a significant noise reduction which may exceed 8 dB(A) at low constant speed. Even if smaller, this noise advantage is still valuable when the vehicle is accelerating or braking. Due to weaker noise emitted upwards, the benefit should be even greater for residents living on upper building floors. The rolling noise associated with the drive wheel/road contact is the main noise source in all driving situations in electric mode, and beyond 50 km/h in the configurations with engine.     

Branch-and-price and constraint programming for solving a real-life technician dispatching problem

We consider a real problem faced by a large company providing repair services of office machines in Santiago, Chile. In a typical day about twenty technicians visit seventy customers in a predefined service area in Santiago. We design optimal routes for technicians by considering travel times, soft time windows for technician arrival times at client locations, and fixed repair times. A branch-and-price algorithm was developed, using a constraint branching strategy proposed by Ryan and Foster along with constraint programming in the column generation phase. The column generation takes advantage of the fact that each technician can satisfy no more than five to six service requests per day. Different instances of the problem were solved to optimality in a reasonable computational time, and the results obtained compare favorably with the current practice.