Managing a hybrid energy smart grid with a renewable energy source

The aim of this work is to develop tools for optimal power flow management control in a micro grid (MG). The latter consists of a wind turbine, energy storage system, two gas turbines (GTs), and the main grid. Unlike the traditional approach, which is limited to the distribution of active power, this paper models an electrical system to coordinate and optimize the flow of both active and reactive power using discrete controls. The proposed optimal power distribution strategy has two objectives. First, it aims at forecasting over a time horizon of 24 hours the optimal distribution of the active and reactive power required for each power source connected to the MG. The proposed management incorporates the forecasts of consumption, weather, and tariffs. Second, it aims at reducing the CO₂ emissions rate by optimizing both the operating point of the two GTs and the usage of the storage unit. The proposed optimization problem for the energy management system is solved using the Bellman algorithm through dynamic programming. Its effectiveness is illustrated with various simulations carried out in the Matlab environment. The supremacy of the proposed management algorithm is highlighted by comparing its performance with conventional (restricted) management.     

电动汽车复合储能系统能量管理策略及其 快速控制原型验证

纯电动汽车储能系统需同时满足高功率密度与高能量密度的要求,但现阶段单一储能单元往 往难以同时具备这两种特点。将高能量密度的锂电池与高功率密度的超级电容进行合理搭配,形成复 合储能系统,是解决以上问题的一个有效方案。该文以宝马 I3 纯电动汽车作为目标车型,设计了锂电 池/超级电容复合储能系统,并制定了一种基于规则的能量管理策略,综合考虑了外部工况要求、锂电 池与超级电容的荷电状态,自动规划工作模式,充分发挥各储能单元自身优势,在极端状况下可自动 启动保护模式;同时,基于快速控制原型的思想,设计搭建了以 dSPACE 为控制中心的复合储能系统 能量管理策略快速控制验证平台,搭配可编辑电力参数的外部电子负载设备,完成了能量管理策略的 半实物实验验证。实验结果表明,电动汽车锂电池/超级电容复合储能系统搭配合理的能量管理策略, 能够充分发挥锂电池的能量特性与超级电容的功率特性,更好地满足了现代纯电动汽车对续航里程与 动力性能的要求,同时可节约能源,在一定程度上起到延长储能系统使用周期的作用。     

Enhancement of hybrid renewable energy systems control with neural networks applied to weather forecasting: the case of Olvio

In this paper, an intelligent forecasting model, a recurrent neural network (RNN) with nonlinear autoregressive architecture, for daily and hourly solar radiation and wind speed prediction is proposed for the enhancement of the power management strategies (PMSs) of hybrid renewable energy systems (HYRES). The presented model (RNN) is applicable to an autonomous HYRES, where its estimations can be used by a central control unit in order to create in real time the proper PMSs for the efficient subsystems’ utilization and overall process optimization. For this purpose, a flexible network-based design of the HYRES is used and, moreover, applied to a specific system located on Olvio, near Xanthi, Greece, as part of Systems Sunlight S.A. facilities. The simulation results indicated that RNN is capable of assimilating the given information and delivering some satisfactory future estimation achieving regression coefficient from 0.93 up to 0.99 that can be used to safely calculate the available green energy. Moreover, it has some sufficient for the specific problem computational power, as it can deliver the final results in just a few seconds. As a result, the RNN framework, trained with local meteorological data, successfully manages to enhance and optimize the PMS based on the provided solar radiation and wind speed prediction and make the specific HYRES suitable for use as a stand-alone remote energy plant.     

A multiple model approach for predictive control of nonlinear hybrid systems

This paper presents modeling and control of nonlinear hybrid systems using multiple linearized models. Each linearized model is a local representation of all locations of the hybrid system. These models are then combined using Bayes theorem to describe the nonlinear hybrid system. The multiple models, which consist of continuous as well as discrete variables, are used for synthesis of a model predictive control (MPC) law. The discrete-time equivalent of the model predicts the hybrid system behavior over the prediction horizon. The MPC formulation takes on a similar form as that used for control of a continuous variable system. Although implementation of the control law requires solution of an online mixed integer nonlinear program, the optimization problem has a fixed structure with certain computational advantages. We demonstrate performance and computational efficiency of the modeling and control scheme using simulations on a benchmark three-spherical tank system and a hydraulic process plant.     

Predictive and interactive controllers for solar absorption cooling systems in buildings

A predictive control approach is proposed for a solar powered hot water storage (SHWS) system which interacts with a simple thermal building control. The primary objective of this first controller is to optimize the use of the solar energy in order to ensure the cooling requirement of the building. The main difficulties are related to the presence of safety constraints and the nonlinearity as well as the hybrid nature of the system. The resulting optimization problem is simplified using various relaxations. The second controller is dedicated to the control of the building temperature. Using a model of the building thermal behavior, it sends its predicted operating profile to the SHWS controller. The performances of these two interacting controllers are illustrated by various simulations on a TRNSYS model of the building and its subsystems.     

基于 PLC 的风电混合动力系统

针对以往工业生产中对风力资源利用的不足,设计了基于PLC控制的风电混合动力系统,开辟了风能发展的新空间。系统以风力机为主、电动机为辅带动空压机,并将空压机产生的压缩气体存储在储气罐内,再由储气罐内的气体驱动作为执行机构的气缸按要求稳定的工作,以达到节约能源的目的。系统以PLC为控制核心,机械部分为基础,气动系统对外输出能量,通过系统测试得到典型结果。具有安全性好,运行成本低,维护容易,无噪音污染等明显优点,可以广泛普及推广,适应节能减排的需求,大有市场前景。     

基于动态模拟技术的混动车辆发动机电控单元检测系统设计

电控单元是混动车辆发动机中的重要组成部分,对于发动机以及混动车辆的行驶性能产生直接影响,为保证电控单元的运行正常,利用动态模拟技术,优化设计了混动车辆发动机电控单元检测系统。改装温度、转速等传感器设备以及信号处理器设备,调整系统电路的连接方式,实现硬件系统的优化。利用动态模拟技术模拟混动车辆发动机电控过程,结合不同故障类型下电控单元的运行特征,设置系统的检测标准。采集电控单元输出信号,从时域和频域两个方面提取信号特征,最终通过特征匹配确定电控单元状态、故障类型以及故障位置,实现系统的电控单元检测功能。综合混动车辆发动机的三种运行场景,通过系统测试实验得出结论：与传统检测系统相比,优化设计系统的漏检率和误检率分别降低了2.59%和2.05%,由此证明优化设计系统具有良好的检测功能。     

积灰条件下光伏阵列最优倾角问题研究

在光伏发电系统设计中,安装倾角的选择对光伏发电效率具有重要影响.针对太阳能光伏阵列常见的表层积灰现象,改变传统的只考虑最大辐射量的倾角确定方法,提出了综合考虑表层积灰情况下的最优发电倾角计算方法,使倾角的确定更加合理与完善.建立了积灰辐射量统一发电模型,并基于Matlab对模型进行了仿真验证.以福建某光伏电站为例,搭建实验平台,通过相关数据的检验与预测,得到了光伏电池板的综合最优倾角.实验结果证明该模型所确定的倾角比传统模型可以得到更大的发电量,提高了光伏利用效率.     

基于NSGA-II的并网型风光互补发电系统协调控制

针对并网型风光互补发电系统中,系统最大输出功率大于给定功率时,风力发电子系统和光伏发电子系统功率如何协调的问题,提出了一种功率协调控制方法.在该方法中,根据系统并网收益最大和输出电流谐波最小构建目标函数,采用带精英策略的快速非支配排序遗传算法对风力发电子系统和光伏发电子系统的输出功率进行多目标优化,协调控制子系统的发电功率;并以甘肃华电阿克赛风光互补发电项目为例进行了仿真验证.仿真结果表明,与传统的光伏优先接入方式相比,基于NSGA-Ⅱ的并网型风光互补发电系统协调控制方法可以更加合理地利用风能和太阳能,提高新能源电能的电网友好性.     

A two-level control strategy with fuzzy logic for large-scale photovoltaic farms to support grid frequency regulation

This study proposes a two-level coordinated control strategy with fuzzy logic for appropriately adjusting the total active power supplied to a grid by large-scale photovoltaic (PV) farms in order to regulate grid frequency. For a solar farm, the strategy includes a central coordinating controller and many local controllers at PV power assemblies, treated as agents. In detail, the central controller uses a frequency regulation module based on a new automatic-tuning fuzzy-logic controller scheme to compute the appropriate reference values according to the total power needed. Then, the individual reference value for each local controller is determined. Each local controller governs all power-electronic converters installed at the PV agent to inject power into the grid according to the individual reference value received. Additionally, each local controller uses an algorithm to manage the state-of-charge of the battery bank installed at the agent so that it remains in the safe range of 20–80% while operating and close to the desired idle value of 50% at the steady state. Besides, a special control mode is developed and integrated into the overall strategy to aid rapid recovery of the grid frequency under emergency conditions. Numerical simulations demonstrate that the suggested strategy has the good response in terms of injecting an appropriate amount of power into the grid to regulate the frequency deviation into acceptable ranges of ±0.2 (Hz) in the transient state and ±0.05 (Hz) at the steady state, even when the weather conditions (solar radiation, air temperature), AC system load, and important control parameters of the grid suddenly change. Furthermore, the effectiveness in improving the grid-frequency stabilization by using the proposed strategy is validated within a four-area power system, where four PV farms are connected and the operating parameters of the grids at the areas are fairly different.     

Optimization and control of a stand-alone hybrid solid oxide fuel cells/gas turbine system coupled with dry reforming of methane

This paper presents the hybrid solid oxide fuel cells (SOFC)/gas turbine (GT) system coupled with dry reforming of methane (DRM). The DRM is a syngas producer by consuming greenhouse gas. The stand-alone (off-the-grid) power system is developed by using a combination of a post-burner, recuperators and pressurized recycles in place of external energy supplies. To address the stand-alone operation and meet the complete combustion condition for the burner, the optimal operating conditions are initially determined by solving a constrained optimization algorithm for maximizing the hybrid power efficiency, and the dynamic control loops are implemented in a plantwide environment. In the proposed plantwide control strategy, the inventory control framework is added to regulate the plant component inventory, an air/fuel cross-limiting combustion control is added to ensure complete combustion and reduce heat loss, and the power and CO₂ emission control configuration is added to achieve the quality control performance. Finally, the simulation shows that the IMC-based multi-loop control scheme can efficiently regulate the total system power and control CO₂ emissions per kWh of electricity as well.     

系统控制单元数据存储更新算法探讨

系统控制单元的有限存储空间被系统运行数据写满时,新产生的数据就需替换旧数据完成更新。通过采用逐条替换法、分块替换法、间歇删除法和抢断删除法,比较替换过程中最少存储数据的数量和实时性的滞后时间,找出一种最优的数据更新方法。试验结果表明,抢断删除替换算法更能快速有效实时完成数据的更新。     

A two-layer memory network architecture for a pattern classifier

Although memory based pattern classification systems are attractive in terms of structural simplicity, flexibility of application and potential operating speed, most practical applications involve a trade-off between attainable performance and storage required for implementation, which can be considerable. This letter introduces a novel system architecture which allows improved performance at marginal increase in storage cost, thereby allowing overall memory savings for a given performance index when compared with a conventional classifier structure.     

New MPPT algorithm for PV applications based on hybrid dynamical approach

This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.     

太阳能电池板发电效率的实验研究

为了更好的利用太阳能资源,针对南京地区太阳能发电的应用问题,设计并实验分析了太阳能电池板在不同波长光照下发电效率的规律,并进行了不同照射角度下发电效率的实验研究.文中设计了太阳能电池板发电效率的测试方案,采用滤光片分别进行了四种波长太阳光线的获取;针对太阳能电池板的组合排列,分别设计了五种组合方式,并对每一种组合方式进行了实验研究.实验结果表明,在南京地区的天气中,中午12到14点太阳能发电效率最高;在波长方面,大于600nm的光线的发电效率最大;在实用性方面,四个太阳能电池板并联方式提供的电流最强,四个串联方式提供的电压能量最大.研究结果能为更好地利用太阳资源能提供良好的借鉴.     

风光气储发电控制系统

针对风能能量密度低和风力发电系统供电稳定性差的难题,提出了新型的风光气蓄组合发电系统,并根据此系统设计了基于PLC的控制系统。该发电系统是在原有风光互补系统上增加了气压储能以及相应的控制装置,按照既定的控制策略,以提高持续供电的品质。通过对新型发电系统进行数学建模和相关的实验研究,证明了该发电系统有效改善了风电系统持续供电的能力以及其控制系统发电的合理性与实用性。     

Fuzzy predictive PI control for processes with large time delays

This paper presents the design, tuning and performance analysis of a new predictive fuzzy controller structure for higher order plants with large time delays. The designed controller consists of a fuzzy proportional-integral (PI) part and a fuzzy predictor. The fuzzy predictive PI controller combines the advantages of fuzzy control while maintaining the simplicity and robustness of a conventional PI controller. The dynamics of the prediction term are adaptive to the system's time delay. The prediction term has two parts: a fuzzy predictor that uses the system time delay as an input for calculating the prediction horizon and an exponential term that uses the prediction horizon as its positive power. The prediction term also introduces phase lead into the system which compensates for the phase lag due to the time delay in the plant, thereby stabilizing the closed-loop configuration. The performance of the proposed controller is compared with the responses of the conventional predictive PI controller, showing many advantages of the new design over its conventional counterpart.     

A hybrid method for hydroelectric generation scheduling using an artificial neural network

This paper presents a decomposition method for finding an optimal operating policy of interconnected hydroelectric power plants using an artificial neural network. The coupling constraints on reservoir storage at the end of the planning horizon are relaxed using coordinating multipliers that result in interval wise decomposition of the overall problem. Resulting subproblems are solved sequentially, which reduces the complexity of the problem. Each subproblem is solved using a two-phase neural network approach. An efficient heuristic algorithm is developed to find the feasible solution. A case study considering scheduling of the Bhakra-Beas reservoir system is also presented in this paper. The new method demonstrates the potential of achieving an improved performance.     

卫星姿态的状态转移控制

本文面向卫星的应用需求,对卫星姿态的运动学和动力学进行了分析与建模.利用反馈线性化,将姿态运动的高阶非线性项包含在姿态控制中,通过局部动态线性化,将动力学系统近似为定常系统.通过幂级数法对系统进行了状态转移过程的求解.采用模型预测的方法获得姿态角和姿态角速度的预期偏差.通过广义逆变换构造关于偏差的最小范数、最小二乘控制器.提出了一种基于状态转移的卫星姿态机动、跟踪与稳定控制的新方法.控制器的参数具有根据系统采样周期和当前状态时变自适应的特点.考虑帆板挠性及多种偏差和噪声影响,仿真验证了方法的可行性和有效性.     

Stability analysis of a multi-model predictive control algorithm with application to control of chemical reactors

We study a stabilizing multi-model predictive control strategy for controlling nonlinear process at different operating conditions. The control algorithm is a receding horizon scheme with a quasi-infinite horizon objective function that has finite and infinite horizon cost components. The finite horizon cost consists of free input variables that direct the system towards a terminal region which contains the desired operating point. The infinite horizon cost has an upper bound and steers the system to the desired operating point. The system is represented by a sequence of piecewise linear models. Based on the condition of the system states, the sequence of piecewise linear models is updated and the controller’s objective function switches form quasi-infinite to infinite horizon objective function. This results in a hybrid control structure. A recent approach in the analysis of hybrid systems that uses multiple Lyapunov functions is employed in the stability analysis of the closed-loop system. The stabilizing hybrid control strategy is illustrated on two examples and their closed-loop stability properties are studied.