Adaptive H∞ event-triggered load frequency control in islanded microgirds with limited spinning reserve constraints

Using an islanded microgrid (MG) with large-scale integration of renewable energy is the most popular way of solving the reliable power supply problem for remote areas and critical electrical users. However, compared with traditional power systems, the limited spinning reserves and network communication bandwidth may cause weak frequency stability in the presence of stochastic renewable active outputs and load demand fuctuations. In this paper, an adaptive event-triggered control (ETC) strategy for a load frequency control (LFC) system in an islanded MG is proposed. First, a bounded adaptive event-triggered communication scheme is designed. This not only saves on network resources, but also ensures that the control center has a sensitive monitoring ability for the MG operating status when the frequency deviations have been efectively damped. Secondly, by fully considering the spinning reserve constraints and uncertain communication delays, the LFC system is described as a nonlinear model with saturation terms. Design criteria for ETC parameters are strictly deduced based on Lyapunov stability theory. Finally, an ETC parameter optimization algorithm based on random direction search is developed to reconcile the bandwidth occupancy and control performance. The efectiveness of the proposed method is verifed in an MG test system.     

微电网的电流均衡/电压恢复自适应动态规划策略研究

含多类型分布式电源的微电网已经成为了未来电力系统的重要发展方向,其中风能和光能在降低化石能源消耗和二氧化碳排放等方面有着极大优势,考虑二者之间强互补性的协同调度已被广泛研究.但风/光协同调度的微电网多关注分钟级的调度或优化问题而非风/光波动下秒级的实时电流按容量比例精准分担,简称电流均衡,而精准电流均衡有助于可再生能源的高比例消纳.因此,本文提出了基于自适应动态规划的微电网电流均衡和电压恢复控制策略.首先,构建包含风电整流型电能变换器和光电升压型电能变换器的广义风光拓扑同胚升压变换器模型,其提供了后续控制器设计的模型基础.其次,本文将电流均衡和电压恢复问题转化为最优控制问题,基于此,每个能源主体的目标函数转化为获取最优控制变量和最小电压/电流控制偏差,进而转化为求解哈密顿?雅克比?贝尔曼(Hamilton-Jacobi-Bellman,HJB)方程问题.基于此,提出了基于贝尔曼准则的分布式自适应动态规划控制策略以求取HJB方程的数值解,最终实现电流均衡和电压恢复.最后仿真结果验证了所提分布式自适应动态规划控制策略的有效性.     

智能微电网能量管理系统设计

尽管分布式发电系统的出现大大减轻了传统电网的负担,但与传统电网之间仍旧存在诸多矛盾.为协调传统电网与分布式电源的矛盾,提出了微电网的概念.由于微电网的特殊性,传统的大规模发电机组的能量管理系统不适合微电网能量管理.现有的微电网能量管理系统在运行和控制上略显臃肿和繁杂.在现有能量管理系统的基础上进行了改进,通过"组态王"软件对系统的操作控制和运行管理进行了优化,仿真运行证明了设计的先进性.     

Shifting of research trends in islanding detection method - a comprehensive survey

The augmentation in electricity demand, power system privatization as well as efficacy of renewable resources has paved the way for power system companies and researchers to exploit the field of grid connected distributed generation (DG) and its issues, islanding being a dominant one. Several research works have been conducted to mitigate the issues of islanding detection (ID). In context of this, the paper gives a comprehensive review of islanding issues, standard test systems, criteria and shifting of research trends in islanding detection methods (IDMs). The significant contributions pertain to categorization of IDMs, evaluation of non-detection zone (NDZ) for each test system, disquisition on evolution and advancement of IDMs and its comparisons based on criteria such as NDZ, run on time, nuisance tripping percentage, applicability in multi DG system and implementation cost to draw out the strength and shortcomings of individual methods that will come to aid to the companies or researchers for establishing the applicability and appropriateness of such method for their concerned domain.     

Intelligent power management in micro grids with EV penetration

Large deployment of Electric Vehicles (EVs) adds new challenges in the operation of a microgrid. Assuming that a number of EV owners allow their batteries to charge when their cars are parked, this paper proposes an approach that aims to find suitable individual active power set-points corresponding to the hourly charging rate of each EV battery connected to the microgrid. A multi agent system based controller is designed to find these active power set points for optimal power management of EVs, distributed energy resources in the microgrid, and the loads.     

A statistical approach for sub-hourly solar radiation reconstruction

This paper proposes a computational-statistics based approach for solar radiation reconstruction at sub-hourly intervals. A dimensionless form of stochastic variable, V, which is defined as the difference between the theoretical global solar radiation in clear-sky conditions and the actual solar radiation, normalized by the clear-sky global solar radiation, is introduced and adopted in this work. The probability density function of V is calculated from historical data using a Gaussian kernel density estimator. With the developed model, the only input information required for the reconstruction procedure is the cloud condition of the sky (i.e., fair, partly cloudy, overcast, and rain/snow etc.). A case study in simulating solar radiation in Singapore is conducted to validate the accuracy of the model. The calculated results agree well with the measured data. The normalized root mean square error (NRMSE) is on average 23.4% and 7.2% for the one-minute temporal resolution and hourly integral values, respectively.     

Optimal operation of autonomous microgrid including wind turbines

This paper gives a novel hybrid optimization method to find optimal sitting and operation of an autonomous MG at the same time. The operation is optimized via finding the optimal droop gain parameters of DGs. The optimization problem is formulated as a multi-objective problem where the objectives are applied to minimize the fuel consumption of DGs and to improve the voltage profile and stability of MG subject to operational and security constraints. A hybrid algorithm, named HS-GA, is developed to solve the paper optimization problem. A new formulation of power flow is derived to run the proposed algorithm where the steady state frequency of system, reference frequency, reference voltage and droop coefficients of DGs, based on a droop controller, are considered as optimization variables. The performance of the paper approach is compared with other optimization and non-optimization methods in MG with 33and 69 buses using MATLAB. The performance of the proposed method is compared with a method that the parameters of DGs are pre-determined without conducting any optimization process. The results show, which optimized droop parameters improves the operation of the MG.     

Microgrids formed by renewable energy integration into power grids pose electrical protection challenges

System parameters of a microgrid change in its two operating modes primarily due to output current limitation of PWM based inverters connected with renewable energy sources. The unavailability of an appropriate protection scheme, which must be compatible with both modes of a microgrid operation, is a major problem in the implementation of a microgrid. Two important properties of the microgrid components are peer-to-peer, and plug-and-play. It means that there is no component like a master controller which is critical for the operation of a system, and a distributed-generation unit can be installed at any location in a microgrid. These properties further complicate the protection of a microgrid. This paper reports the MATLAB/SIMULINK model of a microgrid along with the models of the conventional protection schemes and renewable energy distributed-generation resources. Malfunctioning in the conventional protection schemes in islanding mode is identified and models of newly proposed protection schemes are developed. Different types of faults are simulated in all the protection zones of the system and the system parameters are analysed to identify the possible fault detection methods. Based on the simulation results, a protection scheme is recommended that can meet the protection standards such as selectivity, co-ordination and reliability.     

Stochastic frequency-security constrained energy and reserve management of an inverter interfaced islanded microgrid considering demand response programs

This paper addresses a novel security constrained energy management system of a microgrid which considers the steady-state frequency. Microgrid frequency as a key control variable, continuously exposes to be excursed of its nominal value due to unpredictable intermittencies arise from renewable sources and/or load consumptions. Moreover, great utilization of inertia-less inverter-interfaced distributed energy resources intensifies potential frequency excursions. As a result, energy and reserve resources of a microgrid should be managed such that the microgrid frequency lies within secure margins. To that end, a new objective function on the basis of the frequency dependent behavior of droop-controlled distributed generations is formulated using a mixed integer linear programming. It is aimed to optimize the microgrid frequency according to the economic and environmental policies. Besides, to seek the active participation of the consumers into proposed frequency management approach, a linearized ancillary service demand response program is also proposed. In addition, to properly model the impacts of microgrid various uncertainties in the frequency management approach, a two-stage stochastic optimization algorithm is employed. Simulations are performed in a typical microgrid which operates in the islanded mode during a 24 h scheduling time horizon. The numerical results show the impressiveness of the proposed frequency aware energy management system while concurrently managing the microgrid security and economical aspects. Furthermore, it is demonstrated that utilization of demand response programs economizes the microgrid frequency management approach.     

A fuzzy logic-based droop control for simultaneous voltage and frequency regulation in an AC microgrid

Modern power systems require increasing intelligence and flexibility in the control and optimization to ensure the capability of maintaining balance between generation and load under violent disturbances. There are several inverter interfaced distributed generations (IIDGs) with local and global control loops in a microgrid (MG). Voltage and frequency of MGs are strongly impressionable from the active and reactive load fluctuations. A change in load leads to imbalance between generation and consumption. The output voltage and frequency of the IIDGs are primarily controlled by the droop characteristics. But, in case of severe changes in load, the IIDGs may be failed and the MG is collapsed. In this paper, for optimally tuning of a generalized droop control (GDC) structure and also secondary voltage and frequency controllers, the fuzzy logic technique is utilized. It is shown that the proposed fuzzy logic controller exhibits high performance and desirable response for different scenarios of change in load.