Shunt capacitor placement in radial distribution networks considering switching transients decision making approach

This paper provides a new approach in decision making process for shunt capacitor placement in distribution networks. The main core of the evaluation process is a multi-objective framework to allocate the capacitor banks. The power loss and the total harmonic distortion (THD) are the objective functions of the system under study in a long-term planning horizon. In order to select the executive plan introduced by using a multi-objective model, transient switching overvoltages have been considered. As the size and location of shunt capacitors may result in unacceptable overvoltages, the proposed technical decision making framework can be applied to avoid corresponding damages. In this paper, an iterative conventional power flow technique is introduced. This technique can be applied to evaluate THD for distribution networks as well as other power flow based objectives, such as power losses calculation and voltage stability assessment. The presented framework is a two stage one where at the first stage, a non-dominated sorting genetic algorithm (NSGA-II) augmented with a local search technique is used in order to solve the addressed multi-objective optimization problem. Then, at the second stage, a decision making support technique is applied to determine the best solution from the obtained Pareto front. In order to evaluate the effectiveness of the proposed method, two benchmarks are addressed in this paper. The first test system is a 9-bus distribution network and the second one is an 85-bus large scale distribution network. The simulation results show that the presented method is satisfactory and consistent with the expectation.     

Adaptive intelligent techniques for microgrid control systems: A survey

This paper introduces a survey on the adaptive and intelligent methods that have been applied to microgrids systems. Interestingly, the adaptive technique is effectively exercised in various control issues including stability, tracking error, and parameter uncertainties. Adaptive control has been extremely developed by using intelligent algorithms to automatically tune the control parameters namely fuzzy logic, particle swarm optimization, bacterial search algorithm, and etc. The objective is to evaluate and classify the design control methods and evaluation algorithms for the microgrid systems to maintain stability, reliability, and load variations by adjusting the controller parameters especially in standalone operation mode. The stability of islanded microgrids are constantly impacted by the related loads. A significant part of the research on an islanded microgrid involves droop control technique. In normal operation, distributed generation units and storage units provide power quality control. Once a shutdown is occurred, microgrid can be isolated from the main grid and operate in a local grid to support the local loads. Thus, distributed generations co-operate storage units to sustain the stability of the islanded microgrid.     

Optimal placement of piezoelectric patches over a smart structure

Control of structural vibrations has significant applications in manufacturing, infrastructure engineering, aerospace engineering and various consumer products. In last two decades, considerable attention has been focused to suppress structural vibrations using active vibration control technique. Various researchers have proposed various optimization criteria for optimal placement of piezoelectric patches over a smart structure to suppress vibrations using various optimization techniques. This paper presents a review of various optimization criteria and techniques that have been used by various researchers in the field of smart structures. Mathematical expressions of objective functions of twelve optimization criteria have been presented and their justifications have been reasoned. Step by step procedures of commonly used optimization techniques have also been presented.     

Antlion Algorithm Optimized Fuzzy PID Supervised On-line Recurrent Fuzzy Neural Network Based Controller for Brushless DC Motor

In this paper, Antlion algorithm optimized Fuzzy PID supervised on-line Recurrent Fuzzy Neural Network based controller is proposed for the speed control of Brushless DC motor. Learning parameters of the supervised on-line recurrent fuzzy neural network controller, i.e., learning rate (η), dynamic factor (α), and number nodes (N_i) are optimized using Genetic algorithm, Particle Swarm optimization, Ant colony optimization, Bat algorithm, and Antlion algorithm. The proposed controller is tested with different operating conditions of the Brushless DC motor, such as varying load conditions and varying set speed conditions. The time domain specifications such as rise time, overshoot, undershoot, settling time, recovery time, and steady state error and also integral performance indices such as root mean square error, integral of absolute error, integral of squared error, and integral of time multiplied absolute error are measured and compared for above optimized controller. Simulation results show Antlion algorithm optimized Fuzzy PID supervised on-line recurrent fuzzy neural network based controller has proved to be superior than other considered controllers in all aspects. In addition, the experimental verification of proposed control system is presented to test the effectiveness of the proposed controller with different operating conditions of the Brushless DC motor.     

A Heuristic Combinatorial Optimization Algorithm for Load-Leveling and Peak Demand Reduction using Energy Storage Systems

A method for applying combinatorial optimization algorithms to Energy Storage System (ESS) scheduling is presented in this paper. Scheduling is essential for the integration of ESS in electrical networks at grid level or at consumer level to achieve the objectives of integration such as constraint management or energy cost reduction and for efficient storage dispatch. It also shows that for a time-of-use (ToU) tariff scheme based on the shape of the demand profile with higher prices tied to peak periods, effective load-leveling, and peak demand reduction always leads to energy cost reduction. While other methods usually require more information such as generation cost curves or ToU tariffs to schedule ESS, the proposed method uses only demand profile information and ESS parameters to achieve load-leveling and peak demand reduction and also considers the entire optimization time horizon. This is done by combining heuristic bin packing and subset sum algorithms with specific modifications to the standard forms and through transformations. A case study is presented in which the algorithm is used to schedule household ESS with repurposed electric vehicle batteries and the results are compared to a demand response scheme on the same setup.     

主动配电网三相电压优化及校正控制方法

研究主动配电网三相电压的优化与校正控制技术,提出了全网集中优化、局部协调校正的控制方法。在长时间尺度内,协调全网有功和无功资源,基于半定规划理论建立计及本支路相间互感的主动配电网三相电压优化的数学模型,实现全网优化控制。在短时间尺度内,利用电压相量对节点注入功率的三相灵敏度建立电压相量校正二次规划模型,实现电压相量校正控制。IEEE 33节点三相标准测试系统的仿真表明,全网优化控制能有效降低网损,局部校正控制能利用最小的功率调整量快速校正越限节点的电压幅值,并减少三相不平衡度。     

微电网群功率优化控制

随着间歇性电源(分布式风电、光伏)在中、低压配电网中渗透率的提高,多个微电网可能共存于一个区域配电网中,各微电网间能量互济与协调控制的微电网群技术开始引起广泛的关注。以微电网研究为基础,分析了微电网群的典型特征及拓扑结构。以微电网群功率波动为研究对象,建立了微电网群功率波动熵值的动态调度模型,采用量子粒子群优化算法进行求解实现优化控制。仿真结果验证了所提微电网群功率优化控制方法的正确性和有效性。     

计及需求侧管理的热泵-储能型微电网能量优化策略

为减少储能总容量和蓄电池动作次数,提出一种计及需求侧管理的微电网能量优化策略。考虑热泵的负荷特性,根据产热量与热泵工质流速的关系建立相应的热泵系统模型。根据热负荷日需求曲线,对热泵的储热容量模型进行分析与计算;按照频率区间将微电网功率波动划分为高频成分与中低频成分,并采用模糊控制理论将波动功率在热泵、蓄电池与超级电容间进行分配。该策略对微电网进行削峰填谷,对功率波动进行抑制,实现了微电网的可靠、经济运行。算例验证了所提能量管理策略的正确性与有效性。     

风机中参数变化对变流器直流侧电容可靠性的影响分析

以风电机组功率变流器可靠性评估为背景,给出了一种直流侧电容的可靠性评估方法。基于电容的损耗计算方法,结合热网络结构,构建了直流侧电容的可靠性分析流程。综合考虑电容的可靠性影响因素,分析了环境温度、风速、电容等效串联电阻及热阻的变化对直流侧电容可靠性的影响。以某风电场2 MW双馈风电机组结合实际风速、气温数据为例进行验证,实例结果验证了理论分析的正确性。讨论了当风电变流器实际工作时,利用优化变流器直流侧设计或电容的散热环境等措施提高直流侧电容的可靠性,结果表明了所提方案的可行性。     

基于操作功最优的永磁机构参数控制优化

以永磁机构分、合闸操作功与真空断路器开断性能要求匹配最优为目标,基于四连杆传动规律将12 kV真空断路器本体及传动机构的反力特性归算至永磁机构的运动部件动铁芯上,构建永磁机构操动特性数学模型。利用ANSYS-Maxwell仿真得到配永磁机构真空断路器的动铁芯位移、线圈电流、电容电压变化曲线等操动特性,计算出机构平均合闸速度、操作功等参数。以真空断路器操作功最优为目标函数,以线圈匝数、线径、操动电流为约束条件,在仿真的基础上建立正交回归实验,利用遗传算法对线圈参数进行优化设计,并通过实验进行验证。结果表明,在保证永磁机构操动特性满足真空断路器动作特性需求条件下,线圈优化设计后的永磁机构操作功从970.41 J降低到362.26 J,降低了动铁芯碰撞速度,提高了机构的稳定性。