Optimal dispatch of electric power with ambient air quality constraints

A method is given for allocating power loads for a system of electric generating units in a way which meets the time-dependent demand and minimizes the sum of the fuel cost and a penalty function for pollution. The method takes into account explicitly the dynamic nature of ambient air pollution which depends on the topography of a region and on the past performance of the system. With suitable and reasonably realistic approximations, the problem is reduced to a linear-quadratic optimal control problem for which a linear feedback control rule is obtained. In addition, a discrete version of the problem is given which has the form of a quadratic programming problem, and thus can accommodate, in a straightforward manner, additional constraints such as fuel limitations and upper bounds on emission.     

An approach to on-line power dispatch with ambient air pollution constraints

An on-line optimal environmental/economic dispatch methodology for electric power generation is developed in this paper. Aside from the conventional economic dispatch, constraints on air quality (such as those specified by the U.S. Environmental Protection Agency) are added to the minimum fuel cost problem. Using the integrated Gaussian puff model based on the statistical turbulent theory, rapid dynamic features of pollutant dispersion and its forecast surrounding the plants are emphasized. By applying a convex programming algorithm repeatedly, a set of marginal environmental imposts for the power plants at different times are obtained. Such imposts are incorporated with the fuel cost in the ordinary short-term economic dispatching program to indirectly account for the environmental impact of power generation on the quality of the ambient air. The approach is specifically taken to have little modification for existing economic dispatch programs and be implemented for real power networks. The proposed approach has been simulated in a power system with three plants and three monitoring points.     

A hierarchical approach to dynamic optimization of power systems

The power production system in The Netherlands is characterized by a relatively large number of thermal power-generating units, the presence of autonomous power stations, a strong national grid and a fluctuating daily load. The calculation of the most economic production policy for one or two days ahead, given all cost functions and the predicted demand for electricity, leads to a nonlinear mixed-integer optimization problem. A real solution can only be found at the expense of rather unrealistic values for computing time and memory. To cope with this problem, a hierarchical approach is described that is able to solve problems with up to 100 units and 24 periods.     

Recollections of the evolution of realtime control applications to power systems

Paralleling the extensive growth and expansion of interconnected electric power systems in the United States and Canada during the past 60 years, has been the related need to regulate generation in the constituent areas, and the power flow between them, to achieve equitable, reliable and economic system and area operation. Many individuals and groups have made contributions to these objectives. These contributions constitute the evolution of the system and area realtime control art from modest, tentative beginnings to the comprehensive, broadly scoped and highly capable present day on-line digital control systems. This paper presents one individual's view, based largely on personal experience and observation, of significant steps in this evolutionary process. The paper deals primarily with the analog phases of these developments, many of the philosophies and techniques of which remain basic to current digital executions.     

Gbest guided artificial bee colony algorithm for environmental/economic dispatch considering wind power

The current energy consumption in most of the countries is weighing heavily on fossil fuels, which account for about 70–90% of total energy used. The ecological concerns about air pollution and global warming are encouraging wider use of clean renewable technologies such as wind and solar energy. In this paper, Gbest guided artificial bee colony algorithm (GABC) is applied to optimize the emission and overall cost of operation of wind–thermal power system. The random nature of wind power is modeled using weibull probability distribution function (PDF). Moreover, the uncertainty in wind power is considered in the cost model by including the power imbalance terms such as overestimation and underestimation costs of available wind power. To validate the effectiveness of proposed method, it is first applied to three standard test systems considering different technical constraints such as valve loading effect, prohibited zones, ramp rate limits, etc. In second part, the effect of wind power generation on dispatch cost and emission is analyzed for IEEE-30 bus test system. A comparative analysis with other similar optimization techniques reveals that the proposed technique has better solution accuracy and convergence results.     

基于SIP 算法的暂态稳定约束最优潮流计算

提出一种基于约束转换方法的建立暂态稳定约束最优潮流(OTS)的算法.运用函数转换技术等价变换OTS为半无限优化(SIP)问题,转换后的SIP问题与常规的最优潮流(OPF)具有相同的维数;基于有效集策略设计了转换后SIP问题的迭代法,该方法减少了子问题中不等式约束的个数.电力系统的2个数值仿真例子验证了所提出算法的有效性.     

Optimal sulfur dioxide gas discharge control for Osaka city,Japan

This paper, using actual data, establishes a dynamical model of sulfur dioxide pollution and gives an optimal discharge control policy for Osaka city in Japan.From a mass balance of the gas, a linear scalar state equation is obtained. In spite of the simplicity of the model, it can represent the effect of wind speed, inversion layer, diffusion, boundary concentration and discharge intensity of the pollutant sources. Six unknown parameters in the model and system noise variance are identified by maximizing likelihood function by Flexible Polyhedron Search. This makes the model reasonably representative.A quadratic loss function for the control problem is the weighted sum of two terms; the loss caused by the discharge control and the loss due to the air pollution. The wind speed varies at random according to a Markov transition matrix, considering actual emergency control situations. The optimal control policy is obtained by Dynamic Programming, resulting in linear feedback control dependent on the wind speed, involving a Riccati equation. A practical method of the determination of the weighting coefficient in the loss function is proposed.Since the model is a scalar state system, the whole calculation can be performed with a relatively small computer. This ease of computation and the Markov property of the wind speed suggest that the proposed method is applicable to the actual emergency discharge control.     

Optimal management of an urban road network with an environmental perspective

Within the framework of numerical simulation and optimal control of partial differential equations, in this work we deal with the mathematical modelling and optimal management of urban road networks. In particular, we are interested in finding the optimal management of the network intersections in order to reduce traffic congestion and atmospheric pollution. So, we consider two different multi-objective control problems (the former from a cooperative viewpoint, the latter within a hierarchical paradigm), propose a complete numerical algorithm to solve them, and, finally, present several numerical tests for a realistic case posed in the Guadalajara Metropolitan Area (Mexico), where the possibilities of our methodology are shown.     

Optimal transmission power with delay constraints in 2D and 3D MANETs

Given the mobile node (MN) density and transmission power, this paper estimates the per-hop advancement toward destination with a single transmission, assuming that MNs are uniformly distributed. Based on this esteem, we calculate required hop count between two given MNs. In homogeneous mobile ad hoc networks (MANETs) where all MNs utilize the same transmission power, the hop count between any two MNs is proportional to the distance between them. Given the distance between each pair of MNs, this paper suggests the optimal transmission range (OTR) of MNs, which is the minimum possible power to guarantee end-to-end delay constraints of requested connections in the entire network. Packet collision is also considered in computing the OTR. All problems are investigated in both a two-dimensional (2D) and a three-dimensional (3D) area. Simulation results substantiate the accuracy of proposed estimation methods. The errors of the per-hop advancement estimation are just 0.88% and 2.33% in a 2D and 3D areas.     

Adaptive optimal dynamic surface control of strict‐feedback nonlinear systems with output constraints

In this paper, an adaptive optimal control strategy is proposed for a class of strict‐feedback nonlinear systems with output constraints by using dynamic surface control. The controller design procedure is divided into two parts. One is the design of feedforward controller and the other is the design of optimal controller. To guarantee the satisfaction of output constraints in feedforward controller, nonlinear mapping is utilized to transform the constrained system into an unconstrained system. Neural‐network based adaptive dynamic programming algorithm is employed to approximate the optimal cost function and the optimal control law. By theoretical analysis, all the signals in the closed‐loop system are proved to be semi‐globally uniformly ultimately bounded and the output constraints are not violated. A numerical example illustrates the effectiveness of the proposed scheme.     

不对称约束多人非零和博弈的自适应评判控制

本文针对连续时间非线性系统的不对称约束多人非零和博弈问题, 建立了一种基于神经网络的自适应评判控制方法. 首先, 本文提出了一种新颖的非二次型函数来处理不对称约束问题, 并且推导出最优控制律和耦合Hamilton-Jacobi方程. 值得注意的是, 当系统状态为零时, 最优控制策略是不为零的, 这与以往不同. 然后, 通过构建单一评判网络来近似每个玩家的最优代价函数, 从而获得相关的近似最优控制策略. 同时, 在评判学习期间发展了一种新的权值更新规则. 此外, 通过利用Lyapunov理论证明了评判网络权值近似误差和闭环系统状态的稳定性. 最后, 仿真结果验证了本文所提方法的有效性     

带可变事故切除时间的暂态稳定约束最优潮流计算

在暂态稳定约束最优潮流（OTS）研究的基础上,提出了电力系统事故切除时间为变量的暂态稳定约束最优潮流（OPF-TSCC）模型.根据约束转换方法,建立了OPF-TSCC对应的一类广义半无限优化（GSIP）;基于GSIP现有理论和算法,提出了求解GSIP的一类新算法.电力系统数值仿真结果验证了所提出的模型和算法的有效性.新模型还可用于求解系统故障的临界切除时间（CCT）.     

智能水滴算法与SQP相混合的电力环境经济调度

电力环境经济调度对于降低发电过程中煤耗成本和污染气体排放有着重要意义。本文给出一种智能水滴算法（intelligent water drops,IWD）和序列二次规划（sequential quadratic programming,SQP）相混合求解电力环境经济调度问题的方法（IWD-SQP）。针对SQP全局搜索弱的缺点,将智能水滴算法应用于求解连续优化问题,同时将每次迭代过程中水滴所产生的解作为序列二次规划初始解进行微调以得到更好的解。将提出的方法应用于一个10机组测试系统进行实验,与其他方法求解考虑阀点效应的电力环境经济调度问题相比,验证了IWD-SQP的可行性和有效性。     

异构网中具有服务质量约束的高能效微基站部署方法

针对异构密集网络中基站密度增大带来的网络能耗过高问题,提出一种异构网络中高能效的微基站部署方法。首先,考虑微基站候选位置可行性以减轻环境条件的影响;其次,在不同的用户分布状态下对优化目依概率进行加权,增强了对不同用户分布场景的适应性;最后,通过对微基站部署数目、位置和功率配置的联合优化来提升系统能效,并提出了一种高能效的微基站部署算法。仿真表明,与仅优化微基站数量和部署位置的方法相比,所提方法提升能效最高达26%。实验结果表明,相对于不考虑功率的部署方法,所提出的联合优化方法能够有效提升系统能效,同时验证了微基站功率对异构网络能效的影响。     

Investigation of load modulated inverse Class‐F power amplifier with extended conduction angle

A novel design space of load modulated (LM) inverse Class‐F power amplifiers (PAs) with extended conduction angle is proposed. The effects of the driven level factor β and the biasing operation factor ρ on the third‐harmonic generation are discussed. The harmonic generation mechanism shows that the knee voltage effects are the source of third‐harmonics for LM inverse Class‐F PAs. The definition of the inverse Class‐F mode is consistently valid under the circumstance of load modulation in a limited output power back‐off (OPBO) range. Meanwhile, the conduction angle θ₀ can be extended from π/2 to a limited value (<110°) to keep the standard waveforms of inverse Class‐F mode and maintain high efficiency. After introducing the “continuous concept” and the second harmonic manipulation method, the mathematical design space of inverse Class‐F PAs with extended conduction angle is derived. Calculation shows that the purely conductive load modulation can enable high back‐off efficiency operation for LM inverse Class‐F PAs. As proof of concept, a demonstrator amplifier is fabricated and measured. The experimental results show that the power added efficiency (PAE) with optimum V_ctrl is improved by 5% over an OPBO range of 6 dB compared with the same PA with fixed V_ctrl.     

带分布式电源的有源滤波器的模糊自适应控制

由于分布式电源逆变并网发电与有源电力滤波器(active power filter,APF)在结构功能上具有相似性,本文提出了结合绿色分布式电源的有源电力滤波器拓扑结构,这种结构使APF除了能够滤除谐波外,还可以向负载供能,拓展了APF的应用范围,有利于电网的绿化和供能的多元化.分布式电源通过逆变升压整流来维持APF直流侧的电容电压的稳定,而不需要消耗电网中的能量.针对畸变电压的工况,设计了自适应dq检测算法;在APF控制上采用了自适应模糊控制的策略,不仅能快速跟踪谐波电流,而且具有较强的鲁棒性.仿真结果验证了该系统设计的可行性和可靠性,证明了本文所提算法的有效性和正确性.     

Multi-objective inventory models of deteriorating items with some constraints in a fuzzy environment

In this paper, multi-item inventory models of deteriorating items with stock-dependent demand are developed in a fuzzy environment. Here, the objectives of maximizing the profit and minimizing the wastage cost are fuzzy in nature. Total average cost, warehouse space, inventory costs, purchasing and selling prices are also assumed to be vague and imprecise. The impreciseness in the above objective and constraint goals have been expressed by fuzzy linear membership functions and that in inventory costs and prices by triangular fuzzy numbers (TFN). Models have been solved by the fuzzy non-linear programming (FNLP) method based on Zimmerman [Zimmermann, H.-J., Fuzzy linear programming with several objective functions. Fuzzy Sets and Systems, 1978, 1, 46-55] and Lee and Li [Lee, E. S. and Li, R. J., Fuzzy multiple objective programming and compromise programming with Pareto optima. Fuzzy Sets and Systems, 1993, 53, 275-288]. These are illustrated with numerical examples and results of one model are compared with those obtained by the fuzzy additive goal programming (FAGP) [Tiwari, R. N., Dharmar, S. and Rao, J. R., Fuzzy goal programming: an additive model. Fuzzy Sets and Systems, 1987, 24, 27-34] method.     

Dissipativity and nonlinear systems with finite power gain

In this paper we present a generalization of the concept of dissipativity to include systems which exhibit finite power gain. Included in this is a generalization of supply rate, available storage, and the integral and differential forms of the appropriate dissipation inequality. We show that under certain conditions, systems which are power dissipative are also stable in the sense that the trajectory is eventually bounded. © 1998 John Wiley & Sons, Ltd.     

基于大变异遗传算法进行参数优化整定的负荷频率自抗扰控制

本文将自抗扰控制(active disturbance rejection control,ADRC)应用到两区域互联电力系统的负荷频率控制(load frequency control,LFC)中,从具有非再热式汽轮机机组的电力系统模型推广到具有水轮机机组的以及考虑发电速率约束和调速器死区的再热式汽轮机组的电力系统模型,涉及线性、非线性和非最小相位特性3种控制对象,并使用大变异遗传算法对控制器的参数进行整定,与基于大变异遗传算法的PI控制进行仿真比较研究,仿真表明本文所提基于大变异遗传算法的负荷频率自抗扰控制动态响应快、偏差小、鲁棒性好、抗干扰能力强,对于LFC系统更为有效。